Business Aspects of the Internet of Things Seminar of advanced topics, FS 2011, Florian Michahelles (ed.) This report reflects on the business opportunities of an emerging Internet of Things. All articles have been prepared by students participating in the Seminar of advanced topics in spring 2011. http://www.im.ethz.ch/education/FS11/iot_sem The Internet of Things describes the technical implementation of connecting objects and devices from real-world processes for establishing multi-purpose services. In order to establish this distributed collaboration among things various kinds of communication infrastructures ranging from RFID tags to low-cost IPv6 network devices have to be brought together. Collecting data from physical things is believed to provide new insights into business processes, consumer actions and all kinds of human activities which should fertilize new business models and services. This report provides an overview of a selection of Internet of Things business ideas elaborated by 8 students as part of a research seminar held during Spring 2011. Students introduced their ideas in 15min talks to the class and lead a discussion with the other students. The results then were summarized in short reports. These proceedings present a selection of the research papers composed by the students as part of this course. The following articles provide concise summaries of related work in the field and aim at collecting useful sources to the Internet of Things for novices, practitioners and other students interested in this field. Thank you very much to all students visiting “Business Aspects of the Internet of Things” in spring 2011 at ETH Zurich, details to be found here: http://www.im.ethz.ch/education/FS11/iot_sem Florian Michahelles Zurich, Switzerland, July 20, 2011 Table of Contents Business Aspects of the Internet of Things Seminar of advanced topics, FS 2011, Florian Michahelles Some aspects about the internet of things, the advantages and challenges Yannick Erb 3 Impacts of Mobile Technologies on Travel Insurance Lukas Ackermann 11 Wireless sensor network for disaster prevention of tunnels built by New Austrian Tunnelling Method Ruzena Chamrova 16 Concept for a Basic Soccer Analysis Service Patrick Haas 21 The value of “the Internet of Things-mashup” for enterprises Dominique Mirandolle 27 Smart Cities and Internet of Things Oliver Haubensak 33 Hability - An integrated smart meter framework for home and mobility use Daniel Mauch 40 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) Some aspects about the internet of things, the advantages and challenges Yannick Erb Management, Technology and Economics ETH Zürich erby@student.ethz.ch consumption computers on the other side, here the difference clearly lies in the size of the products. In today’s world, we register about five billion devices (mobile phones, personal computers, MP3 players, cameras…) and a population of 6.7 billion people where only 1.5 billion are using the internet. Even if those numbers seem huge, compared to all things that are yearly produced (about 100 billion), it is only a tiny part of it. Now imagine that in the future those products might be equipped with minicomputers. Based on the above-mentioned facts, it seems clear that the people won’t be able and willing to communicate with all those smart things, that’s why a new network infrastructure might be required, such as the internet of things. The internet is being used today not only for communication reasons, more and more also for video streaming and other big file downloads. That’s why the last mile in the internet has been increased during the last years extremely. A household nowadays connects to the internet with a bandwidth of at least 1 Mbit/s. With new technologies such as fiber optics, the bandwidth will increase soon up to 50 – 100 Mbit/s. These are huge velocity dimensions compared to a RFID tag, where the transmission speed is only about 100 kBit/s. Assuming that in the future a lot of things will be tagged with a minicomputer or sensor, addressing schemes needs to be improved, because the actual protocol of addressing used for the internet requires too much capacity for those small devices. That’s why alternative technologies and standards such as IPv6 (new internet protocol), EPC, ucode and so on are generated. To ensure a complete compatibility between those smart things and the computers, a global standard protocol would be required. Another big difference between the IoT and the internet considers the service range they offer. While the internet-based services are targeted towards human beings as users, such as the World Wide Web, email, file sharing, chat, and rating, the attributed of the internet of things almost completely exclude humans from direct intervention. Those statements showed quickly the main differences between the internet and the internet of things. Abstract The internet of things (IoT) expands the internet through smart things. Nowadays, computers and mobile phones connect only via manual input from humans to the internet. The overall goal is to create through sensors and sensor networks a communication platform that allows independent interactions between those smart products, because in the future a huge amount of minicomputers and sensors are expected. Through the integration of new technologies, the gap between the real world and the digital world decreases which leads to a higher accuracy because of avoiding media breaks (see chapter 2.1). Problems occur regarding the privacy. Through the overall and free share of information to the whole world, it is nearly impossible to track and trace everything back and still have the entire control of information sharing. The overall gain of the internet of things still outbalances this risk of losing privacy and control. But in the end, everyone takes his own decision being part or not of the entire system. 1. Introduction The internet of things expands the internet by smart products. Smart products differ from usual items through their ability to communicate among each other. Looking at today’s internet, the typical procedure of using it happens through the manual input through a human. So taking all the mobile devices and computers, they are kind of isolated to the real world, because their interactions depend on a manual input from outside. Let’s compare the most important differences between the internet and the internet of things. Beginning with the hardware, the criteria for both technologies are very different [2]. Having the internet with high capacity computers on the nerve ends which require direct access to the power grid on the one side, and very small or almost invisible low-end and low 3 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) each other within local networks and, ultimately, connected to the wider network of networks – the Internet.” [17] Switching now to an IP point of view, here the focus lies mainly on the smart devices that are connected and communicate among each other [4]. A further point in this definition is the diminishing gap between the real world and the digital world. The technology would mainly bring both worlds closer together and enable smart things to interact freely. A fourth view about the internet of things gives us Prof. Dr.-Ing. Bernd Scholz-Reiter. He’s the managing director of the Bremer Institut für Produktion und Logistik GmbH at the University of Bremen [5]. The view he shares is the one that interactions between objects will emerge, but therefore the convergence of technologies necessary [6]. The definitions from the IP point of view and this one from Prof. Scholz-Reiter are quite the same. Both rely on the communication among smart things and about improved technologies. Prof. Dr. Elgar Fleisch adds another point to all previews arguments. Each thing should get its own minicomputer and a direct connection to the internet to enable the communication among them [2]. As seen, overall all definitions point out the communication through the internet between tagged things. In addition emerging technologies are indispensable to reach the goals. But still, while digging deeper in those point of views, differences become visible as mention above. The overall goal is to generate automatic interactions among products which are connected to the internet. The idea behind the IoT is that every real world object becomes a part of the internet whereby the gap between the digital and the real world gets smaller and smaller (see Fig. 1) [1]. Fig. 1: Diminishing gap through smart things between the real world and the digital world. (Source [1]) In the last years, the number of minicomputers increased dramatically and on the opposite, the cost for those minicomputers decreased. The consequence of this evolution is that the margin on the products will decrease. But based on this fact, the question arises, how to get back the “lost” margin? The key here is to change the product-based view to a service-oriented view, hence improve your service related to your product to improve margin and increase your competitive advantage. 2.1 Internet of things and what’s next? 2. What is the internet of things? Let’s now have a look how the internet of things could improve in the future. Trillions of smart things communicating with one another will challenge the technology and its capacity [16]. The digital and the physic world will fuse by bringing different concepts and technical components together: Pervasive networks Miniaturization of devices Mobile communication New models for business processes Business benefits such as the high-resolution management of assets and products same as improved life-cycle management can be achieved with the help of IoT. Even collaboration between enterprises will enhance remarkable. The following citation was not worthwhile to rewrite differently, because it shows perfectly what will be how connected: “The Internet of Things allows people and things to be connected Anytime, Anyplace, with Anything and Anyone, ideally using Any path/network As you may image, there is not “the” definition of the internet of things. It depends very much from which perspective you look at it, or more precisely, in what industry branch you’re involved. The term Internet of Things was first mentioned in the year 1999, by Kevin Ashton [12]. Following we compare four IoT definitions, beginning with two from the industry sector and ending with two from an academic point of view. The International Communication Union ITU focuses mainly on the definition, that through the IoT those things will disappear through upcoming technologies [3]. This statement very much insists on vanishing products. To get that, new and profound technologies are necessary. Now we move to one of the god fathers of IoT, Rob van Kranenburg. He states that “…increasingly large numbers of our everyday objects and gadgets will have some kind of simple communication technology embedded into them, allowing them to be connected to 4 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) Thereby the accuracy amounts to 97%. But this only step is just one of many others. The equations for calculating the accuracy or the failure rate of “x”-media breaks are the following ones: Accuracy = 0.97x or Failure rate = 1 – 0.97x and Any service. This implies addressing elements such as Convergence, Content, Collections (Repositories), Computing, Communication, and Connectivity in the context where there is seamless interconnection between people and things and/or between things and things so the A and C elements are present and addressed.”[16] All mistakes people do sum up to an average master data accuracy of about 70% (≈ 12 media breaks)! That’s why people and companies try to avoid media breaks as much as possible. This can be done through department-wide information systems e.g. the mentioned accounting business. Because in such a wide system, all needed information is saved and available in this system and no more on a sheet of paper. Having all data now online or at least on a computer, the media break between the written paper and the transformation into a computer system vanishes. Further introductions help in reducing media breaks: Company-wide enterprise resource planning systems Cross-company information systems (e.g. supply chain management) Every new generation of information management Relating to our earlier definitions of the internet of things, reducing the media breaks claims to reduce the gap between the real world and the digital world. Another very important point is the convergence of new technologies that allow us to introduce companywide systems that interact automatically without any external input from humans and provide all updated data to everyone. Fig. 2: The communication and connection power of the internet of things. (Source [16]) 2.2 Avoid media breaks through the IoT A media break describes a transformation of information between two medium [2]. When information is converted through human from a piece of paper into a computer, then we notice one media break. Because people are not made for doing such simple and boring work all over the time, they are prone to do mistakes which in the sum are an important factor. Since more than 60 years, people are trying to avoid as much media breaks as possible to enhance the overall accuracy. This error rate of humans amounts to 3% for each media break. Now having a quick look at a typical example, we’ll see how big this mistake can become. Imagine a worker in the accounting department of a company. His job contains mainly calculations and bookkeeping. The transformation from one calculation step (numbers are given on a sheet of paper and the calculation is done by typing it into a calculator) adds the first media break. 2.3 Required technologies and IPv6 The implementation of services in the internet of things relies on some key technologies which we’re going to discuss below [7]. The underlying technology is often a wireless sensor network, which relies on sensing, processing and communication technology. Sensor: The sensor is probably the most important part for the internet of things. He is used to collect all measurable information directly from the real world (e.g. temperature, pressure, speed, humidity, height, location, gravitation, heat radiation, brightness…). Those data can then be used to generate services and applications. The choice of the sensor depends on the required precision, value range, environmental conditions etc. Due to a wide amount of different sensors for specific applications it depends very much 5 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) which information can be measured by which sensor. The price of a sensor is even so an important indicator. Sensor network: Like there are a lot of different sensors, there are also a lot of different sensor networks which are application specific. It depends mainly on those factors which communication protocol will be needed [8]: How big the data rate needs to be How big or low the power consumption amounts to be In what medium (air, water) the sensor network will work Cost Complexity of the network Communication network: For the internet of things communication networks provide the data transmission channel. The main challenge today is to create and enhance the current networks to meet the service requirements of the internet of things (e.g. low data rate, low mobility). Internet of things platform: This platform is connected to several terminals as well as networks and systems. They provide the capabilities to different applications. The big challenge now is to create a unified service platform that is suitable for applications of all industries to support cross-sector unified information services. 2.4 Challenges After having considered those points mentioned above, the sensor network technology needs to be chosen among different ones [9]: Bluetooth (range 10 – 100m) IrDA (range 0.3 – 1m) Wi-Fi (range 30 - 100m) ZigBee (range 10 – 100m) RFID (range 0.5 – 10m) Ultra-Wide Band UWB (range 10 – 50m) Near Filed Communication NFC (range 0.1m) WirelessHart (range up to 3km) One of the main challenges for the internet of things and all the technologies are to transform connected objects into real actors of the internet [11]. Because for example a temperature sensor doesn’t measure a temperature, it measures physical changes occurring with temperature changes and then coverts the value to an electrical signal. This example is very simple but this scenario becomes even more complicated, the more complex a sensor becomes. Another challenge is to reduce the size and the costs of those minicomputers to a minimum, so that a lot of people can gain from this technology. The power of the internet of things only arouses, the more smart things exist. What about all the data that are generated and stored somewhere through using more and more cloud computing? The challenge here is try to keep the threshold of giving information away and getting service therefore somehow traceable. This risk in privacy losses needs to be evaluated by each person by themselves, whether the gain outweighs the loss or vice versa. Another very important challenge is the standardization through all industry branches. Avoiding this, cross-connections cannot, or only hardly, be managed. Fig. 3: Some radio options for wireless sensor networks. (Source [8]) Sensor networks will soon get the new internet protocol IPv6. Nowadays the recent internet protocol is IPv4 which offers 232 addresses (≈ 4.3 billions) [10]. Nearly all of them are assigned which would create a bottleneck in the future, especially for the internet of things, where smart things will be connected to the internet. That’s why the new internet protocol IPv6 is going to be introduced step by step. This one provides 2128 addresses (≈ 340 sextillions). One week ago, on 8th of June, the World IPv6 Day was launched [18]. More than 400 websites (Google, Facebook, Yahoo…) activated the “Dual-Stack-Mode” of IPv4 and IPv6. 2.5 For which branch of the industry is IoT important? This subchapter only sums up for which industry sectors the internet of things became or will become very important. Some examples will follow later on. Not every branch of the industry uses the IoT in the same way, even so the application varies. Below summed up in headwords the probably most important industry sectors using the internet of thing [1]: Medical industry 6 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) 3.2 New healthcare system Chemical industry Warehouse Mobile phones and computers Car industry Logistic and supply chain Food industry Libraries Promotions … The internet of things is also very important in the medicine. This example shows briefly what could be possible using this new technology for a new healthcare system. Small computers in clothes like T-shirts or sweater will be integrated. Those measure permanently the body temperature and the heart rate and synchronize all data ongoing with an external server [16]. As soon as something with your body would be wrong, you’d get a message to your mobile phone with the information what’s wrong. If something dramatically like a cardiac arrest occurs, an alarm including your position (with the help of a GPS signal) would be automatically sent to the hospital. Another example are new toilets that control your sugar level, blood pressure, body fat and weight in your urine every time before flushing it away [13]. This system is already available. A further example is an electric operated toothbrush that is connected to your “home healthcare system”. It would check the status of your teeth (plaque, caries) while your cleaning them. If the toothbrush would find some abnormalities the data would be transferred to your dentist, your system makes an appointment for you at your dentist (assumed your calendar in your mobile phone is synchronized with the system) and you get a message with the date and time of the appointment on your mobile phone. Imagine you need some medicine regular all the time, e.g. to lower your blood pressure. Now if the medicine gets empty, you need new ones and therefore have to visit a drugstore or your doctor. Basically this is a waste of time. Now the idea here is to implement in every package of medicines a small chip and a sensor in your garbage can at home. So now by throwing the empty box away, the sensor reads the information on the chip to know what medicine was thrown away and orders automatically a new one that arrives directly to your home within 24 hours. With the help of new technologies and new emerging markets, the industry sectors using IoT increases constantly. 3. Four examples 3.1 Retail store The Galeria Kaufhof is a big German Warehouse where you can buy almost everything. There is also cloth sector in it with more than 30’000 pieces of clothing [1]. In the example, every piece was tagged with a chip. Sensors were installed in all dressing rooms to display all the try-ons. The goal of that experiment was to display at what opening hours the ratio of the try-ons and the corresponding sales was under proportional or over proportional. With that information the management could reorganize and optimize for example the time for the breaks of the sales persons. They also tried to figure out, what effect corresponds when putting clothes only in the shelves and when dollies wore them. So with this simple method and the use of sensors and mini chips, the sales can be increased and optimized. 3.3 Logistic and supply chain This example already exists in big medical retailers here in Switzerland. The idea is mostly the same like the example above with the medicine and the bin. The boxes that are filled with medicine in the stock are tagged with a little chip [1]. The workers take out as much medicine as they need to fulfill an order and then put the box back into the shelf. Now when the worker sees that the box is nearly empty, he simply turn the box by 180° when he puts it back into the shelf. A sensor at the shelf recognizes it and orders Fig. 4: On the horizontal axis you see the opening hours and on the vertical scale the try-on to corresponding sales ratio. Blue line: try-ons, red line: corresponding sales. Unexpected information was displayed, such as that the breaks of employees around 5 p.m. caused a smaller revenue/try out ratio. (Source [1]) 7 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) 1. Simplified manual proximity trigger: This simplifies the triggering and speeds up a transaction while the accuracy is increased. Some examples are self-checkout, stock-taking and access control in buildings. The business value is an increase in job satisfaction; it enables consumer-self-service and reduces labor costs. The self-service and the higher speed acts positively for the consumer. 2. Automatic proximity trigger: This driver is pretty much the same as the first one, but the main difference is that the self-talking ID automatically triggers a transaction in a certain room. Two examples here are asset tracking and car keys. The business values it creates are cost reductions in process failure and labor. For the customer it’s mainly an increase in convenience. 3. Automatic sensor trigger: Through the introduction of a sensor, the ID is expanded by any data smart thing can collect (e.g. temperature, acceleration, localization, humidity, noise, vibrations, brightness, life signals…). A good example here is this one from the food industry in chapter 3.4, where perishable goods are supervised. Through the prompt process control, process efficiency and effectiveness are increased same as the quality of products and services. 4. Automatic product security: This point adds the security component to the driver. Depending on how encrypted it should be, the price varies very much. In practice this method is used in the anti-counterfeiting industry or for complex access control. The business and customer value is the increase in trust and related services. 5. Simple direct user feedback: Smart things provide a direct feedback (audio signal [beep], visual sign [LED], haptic effects…) to the user which increases the local process control and the confidence. This can be used in digital games or again for perishable goods (green LED = temperature okay, red LED = not okay). Through that, processes become more accurate and faster which leads for the customer in an increase in convenience and entertainment value. 6. Extensive user feedback: This driver extends the output to rich services for the consumer. A good example here is a barcode scanner application for a mobile phone (freely available) where by scanning the product barcode, the app searches online the lowest price near your location. This offers new advertisement opportunities and additional service revenues for the business side. Deep product information and again an increase in convenience result for the customer. 7. Mind changing feedback: A combination of the real world with the virtual world can manipulate automatically new medicine at their supplier. This method is very simple and reduces the cost to order at the same time. Another example comes from SenseAware in corporation with FedEx [14]. The idea behind there, is a simple transportation box that informs you through an integrated GPS sensor where your item is. Further it tells you if the box was opened or exposed to light and through an integrated temperature sensor it also traces the temperature. 3.4 Food industry The last example comes from the food industry (implementation exists already) [1,15]. Food (here strawberries) reacts very different on small temperature changes, some are more perishable than other. Here the idea is to install temperature sensors in the packages of perishable food. Those measure permanently the actual temperature and as soon as the temperature crosses a certain threshold, an alarm is sent to the warehouse (or wherever the food is stored at the moment) to inform their workers to immediately correct the temperature. This method reduces waste material on the whole supply chain by almost 50% and increases the profit and quality each by totally 8%! Fig. 5: Changes on different factors through the implementation of temperature sensors among the whole supply chain. (Source [1]) 4. Value drivers In this chapter the focus will be on the value applications create to businesses and customers using the internet of things [2]. Every application relates to at least one or more of the seven main value drivers listed below. The first four drivers are based on machine-tomachine communication while the last three are based on the integration of users. 8 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) people’s behavior through the introduction of new technologies. Imagine an application that shows you how much water you used compared to your wife or husband or how much pollution you generated by doing something. The introduction of this driver enables new emotional product features and services. This can help to align business goals with green goals. For the customer, the benefit lies in the ability to improve life and act responsible in many different ways. 5. Conclusions The internet of things is undoubtedly going to gain more and more importance in the near future. The difference between the internet and the internet of things is that things become smart through technological components. Up till now, every action relies on a manual input through humans. The goal is to create cheap communication systems that enable the automatic interaction among those smart products. Through that, the gap between the real world and the digital world gets smaller and media breaks can be avoided. By providing information through the customers and sharing them for example one some social platforms, it’s feasible to create service applications. The success often depends on how many customers are using the service, the more the better. The generation of information depends mainly on what sensor and sensor network is used. Because all of them are different costly, it is therefore highly recommended to only build in those sensors and corresponding networks with features that also are really used. As we’ve seen, in almost every branch of the industry the internet of things is represented. In many of them, the IoT is even nowadays irreplaceable. With decreasing costs of the required technologies more applications are possible. Through the introduction of game-like applications (compare chapter 4, mind changing feedback) it is even possible, to change consumers behavior in a hopefully good direction. 10. References [1] E. Fleisch, Internet of Things, http://www.im.ethz.ch/education/HS10/MIS_2010 _VL06.pdf [2] E. Fleisch, What is the Internet of Things?, http://www.autoidlabs.org/uploads/media/AUTOID LABS-WP-BIZAPP-53.pdf 9 [3] Marc D. Weiser, ITU-T: Global Standards for the Internet of Things, http://www.itu.int/en/ITUT/techwatch/Pages/internetofthings.aspx [4] S. Karnouskos et al., The Internet of Things and the Convergence of Networks, http://www.rtcmagazine.com/articles/view/101879 [5] B. Scholz-Reiter, http://www.ips.biba.unibremen.de/staffhomepage.html?&no_cache=1&L= 2&staff=bsr [6] B. Scholz-Reiter et al., Bringing Agents into Application: Intelligent Products in Autonomous Logistics, http://www.sfbtr8.spatial-cognition.de/ ailog-2010/ailog-downloads/paper14.pdf [7] X. Xiaojiang, Services and Key Technologies of the Internet of Things, http://wwwen.zte.com.cn/endata/magazine/ztecom munications/2010Year/no2/articles/201006/t20100 609_186201.html [8] R. Chamrova, Wireless sensor networks in practice, http://www.im.ethz.ch/education/FS11/iot_2011_sl ides/03_wireless.pdf [9] http://de.wikipedia.org/wiki/Bluetooth http://de.wikipedia.org/wiki/Irda http://de.wikipedia.org/wiki/Wlan http://de.wikipedia.org/wiki/Zigbee http://de.wikipedia.org/wiki/RFID http://de.wikipedia.org/wiki/Near_Field_Communi cation http://de.wikipedia.org/wiki/UWB http://de.wikipedia.org/wiki/WirelessHART#Wirel essHART [10] S. Hollenstein et al., Migration to IPv6, www.csg.uzh.ch/teaching/ws0405/inteco/extern/tal k12.pdf [11] H. Sundmaeker et al., Vision and Challenges for Realising the Internet of Things, http://ec.europa.eu/information_society/events/sha nghai2010/pdf/cerp_iot_clusterbook_2009.pdf [12] http://de.wikipedia.org/wiki/Internet_der_Dinge [13] http://articles.cnn.com/2005-0628/tech/spark.toilet_1_toilet-totobathroom?_s=PM:TECH [14] http://www.senseaware.com [15] http://www.rfidjournal.com/article/view/5191 [16] http://sintef.biz/upload/IKT/9022/CERPIoT%20SRA_IoT_v11_pdf.pdf Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) [17] [18] http://eprints.mdx.ac.uk/2990/1/jisc_rfid.pdf 10 http://www.computerbase.de/news/allgemein/ computerbase/2011/juni/world-ipv6-day-am-8.juni-mit-computerbase/ Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) Impacts of Mobile Technologies on Travel Insurance Lukas Ackermann ETH Zurich, Swiss Federal Institute of Technology lackermann@ethz.ch to familiar people and sources of information. Nevertheless the basic concerns about risks of travelling are unchanged [1] / [2]. The internet channel has become the favorite channel for people of all ages to book holidays [2]. As a consequence also travel insurances are taken out on the same channel. The recent success of smartphones has changed the way people access information and services in the internet. This paper takes a closer look at the consequences of new technology applications and the changed customer behavior on the travel insurance business. Abstract Travel insurance is a commoditized insurance coverage usually sold through third party channels such as travel agents or online travel portals. New communication technologies do have a significant impact on sales processes, after sales services and claims handling. Case studies illustrate how technologies are applied and how they change the interface between insurer and customer. Based on new technologies innovative business models may be introduced in order to change today’s travel insurance market. 2. The Role of Technologies As in other industries information management and communication technologies are nowadays of crucial importance and have a great influence on business practice [3]. Fleisch [4] refers to the visionary concept Internet of Things (IOT) as a world of smart things connected to the internet. Tags and sensors are acting as nerve endings expanding the internet into virtually every object and turning it into an accurate copy of the real world. In the Internet of Things context the smartphone with its functionalities acts as an extended sensor for measuring human behavior as well as it offers access to information. This huge collection of data will be the basis for a variety of applications. Loukides [5] points out that these databases and their combination will lead to new services: “It's not just an application with data; it's a data product. Data science enables the creation of data products.” 1. Introduction Travelling for business or leisure reasons is a popular activity not only today but also in history. The economic prosperity of businesses and households, the globalization of commerce and the sinking costs for transportation lead to an ever increasing number of voyages. Leaving the familiar surroundings is linked to emotions of uncertainty and insecurity, but also to objective exposure of risks. The travel insurance industry has actually been around for quite some time. In 1864 the world’s first travel insurance agency started its business activities [1]. The Traveler’s Insurance Company was found “for the purpose of insuring travelers against loss of life or personal injury while journeying by railway or steamboat”. Since that time the face of the travel insurance industry has changed dramatically and there are all kinds of risks against which you can take out insurance. Nowadays clients see accidents, riots and terrorist attacks as well as illnesses as the most important risks while travelling as the survey of Mondial reveals [2]. Travelling has become a commodity for large parts of societies and new communication technologies allow ubiquitous access 2.1 The Smartphone is the Mass Computer of the Future The smartphone with its sensors, connectivity to communication infrastructure and availability acts in the same time as device collecting information and providing the access to content and services that run on the web. Smartphones not only allow an almost unlimited access to information in the web but also 11 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) give access to services which are not only personalized but also take a further context such as location or time into account. New sensors like cameras, microphones, accelerometers, GPS sensors etc. come along with a smartphone and the functionalities are expanded with each generation of hardware. This paper analyses the possibilities how the smartphone technologies can be applied in the travel insurance context. booking a trip and it covers exactly the duration of that trip. Travel insurers have streamlined their products to the needs of the third party distribution channels. Products of different providers are quite similar providing about the same benefits of coverage. The processes of fulfillment and underwriting are downsized to make distribution for the partners as convenient and simple as possible. Therefor travel insurers are highly depending on their distribution partners. The dependency even is aggravated by the fact that people purchasing travel insurance are not aware from which travel insurance company they are purchasing the product. This dependency has brought the third party providers in a favorable position for dictating commissions for sales efforts and lead falling profits for travel insurers on a long term perspective. 2.2. The Technology Push Smartphones have a significant impact on the way customer’s access information. The ubiquitous access to services via the internet becomes a routine for the majority of the users, especially when travelling and staying away from home or workplaces. From insurers point of view similar situation has arisen as in the early days of the internet. While the new technology is hyped by early adopters first success stories of innovative applications of this technology are spreading. Travel insurers and insurers in general do not belong to the early adopters of new technologies. Based on successful applications in different business field many companies ask themselves weather this technology should be adopted and if yes how the technology should be integrated into the existing business model and the subsequent value proposition. Customers’ demand for standardized and affordable insurance products that are combined with value-added services grows [6]. On the one hand, the Internet allows comparing insurance offerings at marginal search costs. On the other hand it enables customers to effect insurance contracts with little effort in an anytime-anywhere manner. Consequently, a growing number of insurance customers compares and purchases insurance plans online. Amongst other reasons, the easy access to competitive offerings and internet comparison services leads to increasing price sensitivity and decreasing customer loyalty. In 2007 the South African insurance company Metropolitan has created Cover2go [7] accidental death and funeral cover for the lower income market using non-agent based distribution channels. During holiday periods many South Africans who work in the cities travel far to spend time with their families. Common means of transportation are minibus taxis which have a high accident fatality rate. In order to purchase an insurance policy the new clients only have to send an SMS with his name and national identity number to a premium rated short code. By confirmation of an message of Metropolitan the contract is concluded and the premium is deducted from the prepaid airtime on the policy holder’s cellular phone. This service allows Metropolitan to set up sales points virtually everywhere and offer access any time. In a Japanese consortium consisting of the insurer Tokio Marine and the mobile service operator NTT Docomo provide the “One Time Insurance” coverage [8]. One time insurance is designed to provide needed coverage on a 24/7 basis. Purchases can be completed via the smartphone with some keystrokes. The premium is added to the mobile phone bill. The pricing considers the buying patterns of mobile phone users who are often led by the impulse to by a relatively low priced service immediately. Distribution is supported by a location based recommender system. Since the providers do know were the owner of a mobile phone currently is location and situation tailored offerings can be pushed to the clients. For example the system recommends travel insurance at airports and other pre-defined target locations. But the providers go even further. Based on an activity log specific behavior patterns are recognized. This allows not only to predict user 3. Technology Impact on Travel Insurers Value Chain A simplified Value chain of a travel insurer comprehends the steps of distribution, after sales services and claims management. The impact of up to date technologies on this value chain is examined in the next section. 3.3 Smartphone as a New Distribution Channel Travel insurance providers heavily rely on the distribution via third party providers such as travel agencies or online travel portals. Temporary travel insurance usually is bought as an add-on product when 12 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) activities in the near future but also to provide timely and useful information to mobile phone users. emergence of information technologies and the introduction of claims management systems insurers industrialized their processes and cut the costs to administer their claims dramatically. Maas [10] showed that insurance companies consider the industrialization of their internal value chain and processes as the most important strategic challenge for the years to come. However the first wave of industrialization affected mainly the internal way of processing information but left the interface to the customers untouched. Emerging technologies as in the field of ubiquitous and mobile computing drive innovation in claims management and can ultimately enable cost savings for insurers. Many customer-facing innovations will help to differentiate from competitors and enable increased service levels. But the growing adoption of smartphone technologies improves the control over claims management processes. 3.4 Technology application in after sales services In the insurance industry travel insurers were amongst the first to offer value added services complementary to the existing travel insurance core products. Travel insurers are said to be the inventors of assistance services as they realized that travellers face problems in case of an incident which go beyond the need of a swift reimbursement of the financial damage. In case of an incident travellers were often choosing inappropriate and costly solutions to solve their problems. These assistance platforms assist customers whenever and wherever facing problems. These services platforms were built up on basic telecommunication technologies such as telephone and fax. The running of the platforms on a 24/7 basis makes assistance services cost intensive and difficult to operate since the resources of the call centers have to be up- and downscaled according the seasonality of the traveling behavior. Assistance platforms are passive standby units waiting for the client to call. The intervention can be executed only after an incident has happened and often is more focused on regulating the access to the insurance benefits than on the salvation of the client’s issues. For these reasons preventive interventions to eliminate risks are difficult to introduce both from an operational and economic perspective. Baecker [11] analyzed potential innovations of the claims management process with the help of mobile smartphone applications. He identified process innovations both on the operational and on the management level. Improvements on an operational level are based on a timely notification of a loss, the collection of extensive data related to the incident, improvements in the quality and the completeness of the gathered data or the reduction of media breaks. The implementation of customer feedback in the processes handled by the mobile device has a significant impact on the management of processes and partners. To assess the effectiveness the claims management process, the response rate of feedback requests can be measured. Based on mobile technology and the integration between mobile devices and enterprise systems, insurers can request customer feedback after the claim settlement by leveraging the mobile communication channel. The feedback embraces a customer’s overall satisfaction with the claims management process, but also his rating of services provided by business partners such as repair shops or towing services. Feedbacks generated along the process are of high interest for insurers in order to raise customer satisfaction. The Canadian travel insurance branch of Zurich insurance company introduced a service called Nomadz illustrates how mobile technologies augment the assistance services [9]. Nomadz provides services such as travel, health and security alert advisories, as well as country and city destination information. The traveling employee receives the latest alerts which are relevant to his current location. Based on the travel route also alerts concerning the chosen destination are pushed to the employee. The employee can also retrieve information on their destination country or city through the Nomadz application. Technologies like smartphone application, web service, itinerary travel services and locating abilities are linked together. The proactive services are backed up with the classic assistance services mentioned above. 4. Conclusions The cases have shown that the Internet of Things and new communication technologies do have a significant impact on the way travel insurers deliver 3.5 Technology impact on claims management The claims management process is often referred as the moment of truth when the insurer can proof his capability to satisfy customer expectations. With the 13 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) services to their customers and design the business processes. Smartphones act as distribution channel which reveal new dimensions in place and time of selling using the potentials of context specific offerings. Product and service offerings may also be adjusted to these new dimensions as well as the pricing. Addressing these dimensions mobile technologies do have a positive impact on sales. Furthermore the new ways of distribution can offer a strategic alternative to the dependence in distribution on third party providers such as travel agents and online travel portals. On the other hand also the cost side of travel insurances can be addressed by mobile technologies. Proactive services such as early warning messages pushed to the client by the travel insurer reduce the number of claims. The smartphone makes it simpler for customers and insurers to get in touch with each other when they are confronted with an incident. Early notices of incidents enable effective interventions and lower the average costs per claim. Last but not least process automation and reduction of transaction costs cut down the expenses for administration. entitled to make use of these assistance services in case of an incident. Therefore the interaction with the insurer is limited to the claims scenario. This business model restricts the market potential only to a limited number of existing clients. Mobile technologies can help to turn this business model upside down. Information can be processed and distributed very efficiently due to the automation of processes and very low transaction costs. Services like a security alerts are pushed to an almost unlimited number of clients at lowest costs. Potential clients may are invited to test these services. They can make use of the services for free and get in touch with the insurers brand. The users of an early warning system get a positive brand experience by using these services. Many popular services in other industries are built successfully on this so called freemium business model. Unlike in the existing business model where access to services is limited to existing clients and the claims event a large proportion of the potential market can be addressed in the new model. The attracted customers can be converted into paying insurance clients with appropriate marketing activities. 4.1 Limitations 6. References: New communication channels and information technologies have evolved and established themselves recently. As the past has shown it takes quite a long time until they are fully adopted by the buying customer. In the travel insurance business it took more than ten years until the internet sales channel gained an major share as a distribution channel as the results of Mondial [2] show. The use of internet based services in order to access after sales services or claims settlement is still underdeveloped. Although the use of smartphones and ubiquitous access to internet services becomes a commodity in many markets the use of similar services as described in this paper will show rather slow adoption rates. [1] History of Travelers, http://www.travelers.com/about-us/flash/history.html [2] Mondial Assistance, Buchungsund Reiseverhalten der Schweizer Bevölkerung, Umfrage 2009, http://www.elvia.ch/firmen/images/Studie_Buchungs%20Reiseverhalten_CH_2009.pdf [3] A. Bereuter et. al., Erhöhte Sehschärfe Technologiebasierte Innovation in der Versicherungswirtschaft, Accenture, www.accenture.ch. 2008 5. Outlook [4] E. Fleisch, What is the Internet of Things? An Economic Perspective, Auto-ID Labs White Paper, www.autoidlabs.org, January 2010 New information technologies may change the existing business model fundamentally on the long run. As we have seen in today’s business model travel insurers offer low differentiated products via distribution channels in the control of third party partners. In the search of ways to differentiate from competition the travel insurance provider may offer additional services to his clients such as assistance in case of emergency. These additional services are tightly linked to the travel insurance products. Clients who have bought a travel insurance product are [5] M. Loukides, What is data science, O’Reilly Radar, 2010 [6] S. von Watzdorf and A. Skorna, How value added services influence the purchasing decision of insurance products. World Risk and Insurance Economics Congress 2010. Singapore. 14 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) [7] A. Smith, H. Smit, Case Study: Metropolitan Cover2go, www.cenfri.org, July 2010 [8] T. Makino, Providing New Customer Experience Using Mobile Technologies, I-VW Trendmonitor 4.2010, November 2010 [9] Nomadz, A mobile www.getnomadz.com. 2011 Zurich Helppoint, [10] P. Maas, B. El Hage, and A. Weigelt. Industrialisierung in der Versicherungswirtschaft: Eine empirische Studie in Deutschland, Oesterreich und der Schweiz. (P. Maas and G. Berner). St.Gallen, Switzerland: Institute of Insurance Economics. 2007 [11] O. Baecker, Mobile Claims Management: ITBased Innovation in Motor Insurance, Dissertation no. 3809, Harland Media, Lichtenberg. 2011 15 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) Wireless sensor network for disaster prevention of tunnels built by New Austrian Tunnelling Method Ruzena Chamrova Swiss Federal Institute of Technology MAS MTEC Raemistrasse 101, 8006 Zurich, Switzerland ruzenac@student.ethz.ch Abstract The safety of tunnels during their construction is an important issue. Tunnel collapse might often result in remarkable consequences, such as casualties, large recovery costs and substantial delays. It is essential to continuously monitor the tunnel during its construction phase. In this paper we propose a real-time monitoring system for tunnels constructed using the New Austrian Tunneling Method (NATM). The new system is presented as an alternative to the current manual convergence measurement, which is labor intensive and cannot provide continuous monitoring. The new system is based on a Wireless Sensor Network (WSNs) comprising of a set of sensors and actuators. The sensors measure the displacements in- and between the tunnel cross sections and communicate them to the base-station. An expert system evaluates the information and activates the actuators in case of acute danger. Technical and business aspects of the solution are discussed. 1. Introduction In the night of 20th October 1994, a section of a tunnel constructed at Heathrow airport collapsed. Eventhough there were no casualties, the recovery cost was 150 million £ and there was a 6 month delay to the project, which was a part London Jubilee Line Underground extension [5]. A similar case happened in Barcelona (2004), where thousands of people had to be evacuated from the district El Carmen, just above the tunnel, where ground subsidy occured. Both tunnels have been built by New Austrian Tunneling Method (NATM) [10], which is the most common method for building small and medium size tunnels. Yet the collapse cannot be attributed to the method itself but rather to a lack of early warning and subsequent measures. The leading idea of the method is ’Design as you go’, i.e. the final design of the tunnel is not known at the time of the construction and a set of measures is prepared and used in case of excessive deformations. Monitoring of the tunnel is an essential part of NATM, because it can either prevent the collapse of the tunnel or at least serve as an evacuation warning. Recently, wireless sensor networks have been on its rise thanks to the decreasing cost of hardware, sensing and communication technology [11]. Thanks to this availability they present an attractive solution for monitoring of transportation structures. This is also the motivation for the business proposal presented in this paper - a disaster prevention wireless sensor network for the construction phase of NATM tunnels. 2. State of the art 2.1. Primary lining The biggest interest during the construction phase of the tunnel lies in the deformations of the primary lining. Primary lining is a relatively thin layer of sprayed concrete (shotcrete), which is in direct contact with the rock. It is usually installed just after a tunnel section is excavated. The deformations of the primary lining are usually the highest just after it is installed and in time follow a convergent trend. Eventhough primary lining is not visible when the tunnel is operational, it is the crucial part of the tunnel during the initial phase of construction. This is when the system is at its weakest and monitoring of its deformations is crucial for safety and disaster prevention. 2.2. Conventional monitoring method One of the most common monitoring techniques which can indicate a possible threat of a collapse is a contactless 16 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) convergence measurement [2]. The tunnel is analysed in individual cross sections, which are regularly spaced (usually 5-30 m based on geological conditions). Each cross section contains a set of convergence bolts set in the shotcrete with a bireflex target (mirror) [2], Fig.2. These bolts are the reference point for measuring deformations by a laser tachymetry and usually there are 3 or 5 of them per cross section (based on the size of the tunnel), Fig.3. Laser tachymetry is performed for each section individually by a surveyor equipped with a laser tachymeter. The surveyor targets the mirrors of the convergence bolts with the laser. The measurement allows to reconstruct the deformations of the tunnel as the construction progresses. Three important trends need to be captured - the deformation of the cross section, the horizontal and vertical displacement. The deformation of the cross section can be obtained based on the mutual distances of the convergence bolts in a cross section. For horizontal and vertical displacement the surveyor needs to connect to the previous cross section of the tunnel. One cross section measurement takes ∼ 5 minutes. The measurements of the cross section are performed once per day, but only in the first three days after excavation. Once a convergent trend is visible, the interval between measurements increases (5, 7, 14, 28th day). The intervals are a result of a long-term experience. The measurements often have to be scheduled so that they do not interfere with excavation and construction work. Yet, performing the measurements in the abovementioned intervals is often insufficient in case of nonconvergent trends. It can lead to misinterpretations of the data and wrong conclusions regarding the measures. Moreover, as the measurement is conducted only for the sections close to the excavation face, it is hardly obvious how the tunnel behaves along its length. This can become important, when another civil engineering structure is close-by (another tunnel, buildings on the top of the tunnel etc). All in all, there is certainly room for improvement in the conventional system, especially in the ’real-time’ disaster prevention domain. 2.3. Wireless sensor networks in tunnels Wireless sensor networks can be used in tunnels both to ensure safe construction and enable smooth operations. Compared to standard wired electronical systems, WSNs offer several interesting advantages. Especially in dynamic environments, they can be easily deployed as they do not rely on existing infrastructure. WSNs by design provide redundancy to tolerate operation under harsh conditions, i.e. they do not suffer from an accidental disconnection. The maintanance of WSNs is somewhat easier as only standalone nodes have to be serviced, instead of a general overhaul of the entire system. Up to now, wireless sensor networks in tunnels have been mostly deployed for operational purposes. Currently their use include monitoring of the deterioration of the tunnel lining [4] and controlling the light intensity in tunnels [1]. While fire disaster relief is of great interest [8], the system is still far from being deployed. To the best knowledge of the author, a wireless sensor network has not been yet deployed during the construction phase of the tunnel, eventhough there had been some research going on for mines [6]. Tunnels constitute a special environment for WSNs, when compared to more traditional deployements as the shape of tunnel acts as a waveguide allowing communications over a longer distance than normally possible. This has both advantages and disadvantages and has drawn interest of the research community [7]. 3. Disaster prevention solution during construction of NATM tunnels 3.1. Vision A ’real time’ disaster prevention system for the tunnel construction would ideally work in four stages: 1. sense the deformations in the cross sections 2. communicate the deformations through a WSN 3. evaluate the deformations along the tunnel 4. actuate alarms in case of excessive deformations or non-convergent trends In the following, such a disaster prevention system will be presented and discussed with regard to the requirements and possible limitations. 3.2. Deployment The deployment of the WSN in the tunnel is closely connected to the excavation cycles. Once a section of the tunnel is excavated and the shotcrete layer is constructed, a node of the WSN is deployed. This node automatically connects to the base station at the beginning of the tunnel. As the construction progresses, more and more nodes with the selforganization capability are deployed, Fig.1. More denser deployment might be needed for tunnel portal, junctions or close to excavation face. As excavation face moves further away from the problematic cross section, a lower density of nodes becomes sufficient and the redundant nodes can be removed without any change to the system. 17 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) Figure 1. Disaster prevention system in a NATM tunnel (longitudinal section) 3.3. Sensing The purpose of sensing is to obtain mutual distances of selected points in the cross section and their displacements. In order to do so, a device capable of measuring distances is needed. In the conventional system this requirement is represented by a laser tachymeter operated by a surveyor. The surveyor is usually standing approximately in the middle of the tunnel and has to move the device everytime a measurement of a new cross section is required. In the proposed system the laser tachymeter is replaced by a distance sensor node located on one of the walls of the tunnel. Unlike the surveyor who has to move, each cross section has its own sensor node, Fig.3. The required measurement accuracy of the distance is ∼ 1mm. The most common methods capable of achieving this accuracy is laser ranging and ultrasonic ranging. The sensor node will be equipped to perform continuous distance measurements between the node and the reference points attached to the shotcrete lining. Figure 2. Convergence bolt (left) with a bireflex target-mirror (right) Figure 3. Disaster prevention system in a NATM tunnel (cross section) municated in regular intervals (0,5 hours sufficient). which represents the sampling frequency of ∼ 0.001 Hz. This qualifies for a very low frequency communication and thus poses no significant challenges in terms of energy consumption [3]. Moreover, the radio of the node does not communicate when there is no change in displacement. In case of a node failure in a particular cross section, the network can reroute the information through the further cross section. The expected communication range of a typical WSN node in a tunnel environment is known to exceed 100 m, which is sufficient to provide the required communication redundancy in this project. 3.5. Evaluation of the deformations 3.4. Communication The communication in the tunnel is accomplished through node self-organization. The displacement is com- Postprocessing of the acquired data is performed on the node (to save communication energy) as well as in the base station outside of the tunnel. An expert system is responsi- 18 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) ble to check for the anomalies along the tunnel, which are acquired from the evaluation of the displacements and convergence trends in the individual cross sections. A visualisation software helps to highlight the type of problem faced and enables to take the correct measures. • development cost of the expert system, visualisation software and sensing technology 3.6. Actuation of alarms • operational variable costs based on the duration of the construction Wireless actuator nodes are added to the existing network at 200 m intervals to warn the construction workers in case of acute danger detected by an expert system. The acute danger represents a node displacement of 30-50 mm (based on the geological conditions). The actuator node consists of an alarm light and a horn and connects to the existing WSN through standard communication protocols. 3.7. Technical challenges In order to be successfully deployed, several technological challenges need to be solved. These include improvement of the sensing technology, addressing physical security of nodes, developing expert systems and gaining acceptance in the field. One of the biggest challenges is the sensing technology. While distance sensor units exist as off-the-shelve components, a custom laser or ultrasonic sensing unit might be necessary for the required precision, distance range and environmental conditions (dust, dirt, humidity). Secondly, physical security of the nodes might pose a challenge. The nodes are often exposed to water, blasts from excavations or a damage by tunnel vehicles. Robust casing is thus essential. Thirdly, a significant amount of knowledge in the expert system is required to correctly evaluate the situation and not to cause false alarms. Cooperation with research groups might be required. Last, civil engineering is a traditional field and wireless sensor networks is a relatively new technology. A significant amount of tests and comparisons to conventional methods will have to be performed before the system can be deployed. 4. Business aspects Tunnel collapse often represents severe consequences with regard to recovery costs, delays and company reputation. Last but not least, no money can be put on the value of the human life. In the following, the business aspects of the proposed disaster prevention system will be discussed. The business idea is to make a company which will sell or lease the full solution for the disaster prevention system. For this idea to be realized the following costs need to be considered. • variable costs based on the length of the tunnel (sensor and actuator nodes, convergence bolts with targets) The development cost for the sensor nodes, expert system and visualization software is estimated to be 5 man years of work, thus represents ∼ 500’000 CHF. Cost per one sensor and actuator node can be estimated from the price of a prototype which could be made out of off-the-shelf components. The cost of a prototype for a sensor node is expected to be in 1’000 - 2’000 CHF range. According to my estimations ∼ 70% of the cost could be attributed to the distance sensing unit. With the mass production the cost is expected to drop into the range of 500 1’000 CHF. The cost of the prototype of the actuator node is expected to be ∼ 500 CHF, while the mass production costs are expected to be between 150 - 250 CHF. The cost of convergence bolts with targets per cross section is ∼ 150 CHF. Operational costs represent one fully employed person throughout the duration of tunnel construction. Under the assumption of no delays and a speed 3m/day that would result in ∼ 100’000 CHF/year. The cost for 1m of a tunnel constructed by NATM varies between 10’000 and 90’000 CHF [9]. The variable costs of the disaster prevention system based on the length of the tunnel would be ∼ 50 CHF per 1m of tunnel and thus constitutes max of 0.5 % of the total tunnel cost. It is expected that the system will be sold and leased to multiple tunnel constructions, thus the development costs can be retrieved through several projects as licensing fees. 5. Conclusions and next steps In the paper, we presented a disaster prevention system for the construction phase of NATM tunnels. The wireless network comprising from sensor and actuator nodes would act as a real-time monitor for non-convergent trends and excessive deformations and would allow to warn the construction workers in case of acute danger. Technical aspects, challenges as well as business aspects were presented. Before the system can be rolled out, several major issues need to be addressed further. The first of them is the development of a sensor prototype. This involves testing of the prototype on a few tunnel cross sections in different conditions. Results of this should then be compared to the traditional measurement. Secondly, thorough tests of the whole 19 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) WSN are needed with regard to the sensing, communication and environmental exposure. This phase would require high cooperation from the tunnel personnel. Last but not least, development of the expert system is necessary. This phase is critical for the correct danger identification and requires the support of the research community. Provided all these issues are addressed, I believe the system can be successfully deployed in NATM tunnel construction. References [1] M. Ceriotti et al. Is there light at the ends of the tunnel? wireless sensor networks for adaptive lighting in road tunnels. In 10th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN/SPOTS), April 2011. [2] GIF. Convergence measuring instruments. http://www.gifettlingen.de/engl/html/geotechnical instruments.html, retrieved 13.4.2011. [3] M. Hempstead et al. Survey of hardware systems for wireless sensor networks. Journal of Low Power Electronics, 4:1–10, 2008. [4] N. Hoult et al. Wireless sensor networks: creating smart infrastructure. In Proceedings of ICE Civil Engineering 162, pages 136–143, August 2009. [5] HSE. Collapse of natm tunnels at heathrow airport. a report on the investigation by the health and safety executive into the collapse of new austrian tunnelling method (natm) tunnels at the central terminal area of heathrow airport on 20/21 october 1994. Technical report, Health and Safety Executive, 2000. [6] L. Mo et al. Underground coal mine monitoring with wireless sensor networks. ACM Transactions on Sensor Networks (TOSN), 5:10:1–10:29, April 2009. [7] L. Mottola et al. Not all wireless sensor networks are created equal: A comparative study on tunnels. ACM Transactions on Sensor Networks (TOSN), 7(2):15:1–15:33, September 2010. [8] RUNES. Reconfigurable ubiquitous networked embedded systems. http://www.ist-runes.org/, retrieved 13.4.2011. [9] TAV. Brief description of tunnelling technologies. http://www.tavbrasil.gov.br/Documentacao/Ingles, retrieved 13.4.2011. [10] L. von Rabcewicz. The new austrian tunnelling method. Water Power, pages 511–515, 1964. [11] J. Yick et al. Wireless sensor network survey. Computer Networks, 52(12):2292–2330, 2008. 20 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) Concept for a Basic Soccer Analysis Service Patrick Haas Swiss Federal Institute of Technology Department of Management, Technology and Economics phaas@student.ethz.ch Kill-a-Watt [1] monitoring device counts your amount of consumed electricity, the Sleep Cycle [2] mobile app analyzes your sleep patterns and the Happy Factor [3] software regularly asks you how happy you currently are via a text message. Possible applications are vast, and the amount of products and services which enable you to log your life steadily increases [4]. From the granular information being now gathered, we can derive instructive patterns; gain new insights by data visualization, analysis and comparison. In general terms, quantitative and qualitative assessment of our activities leads to an increased awareness of the way we live our lives. Personal statistics provide feedback, and the provision of additional information, being finally accessible, helps us to improve our behavior: the Kill-a-Watt connector helps us… yes… to kill a watt (or even more than one), i.e. it supports the reduction of energy consumption costs with a simple cumulative Kilowatt-Hour monitor. The sleep cycle app determines our sleep statistics and wakes you in the lightest sleeping phase; for a pleasant start of the day. Happy Factor enables us to “learn how to have more happiness” [3] in our life. Abstract People more and more track and quantify themselves and their activities. The trend is enabled by new technologies and tools, making it trivial to aggregate data. Subsequent analysis derives instructive patterns and helps us to improve our behavior. The clear purpose of performance improvement makes tracking systems also common in sports, where athletes act as pioneers in the field of self-quantification. Even in soccer, coaches and players become increasingly aware of the power of statistics for performance assessment. Several highend tracking systems and performance analysis services are available, but are too sophisticated and expensive for the large market of ambitioned amateur teams. To fill this market gap, I propose a concept for a basic soccer analysis service at comparatively low cost. The service uses GPS devices to track players during practice and provides a post-game performance analysis. The aim is to optimize game preparation and training methods resulting in a competitive advantage. Scientific studies which quantify and analyze Australian Football League player demands during the last years serve as a basis for the proposal. 2. Monitoring Systems Conquer Sports 1. Introduction 2.1. Pioneers and Commercialization “All is number” was the vision of Pythagoras, a Greek philosopher and mathematician. The interpretation of the sentence remains vague, but it accurately describes a new and all-pervasive meta trend. People are excited to track their activities and to break them down into numbers; they gather and evaluate data about themselves. How high is my current energy consumption at home? How many hours of sleep did I get last week? Or even: How did I feel during the day, rated on a scale from 1 to 10? Today, new technologies and tools provide answers in a highly convenient way. Tracking yourself is trivial now and this is boosting the trend of self-quantification. The Few areas of human activity illustrate the trend to quantify better than sports. “Athletes have kept training logs to quantify and analyze” [5] their activities, i.e. their workouts. Systems to record and evaluate “physical movement and physiological response to exercise” [6], such as video analysis software and heart rate monitors are common among professional sportsmen. They are pioneers in the field of selfquantification. The widespread use is based on the obvious purpose of self-tracking in professional sports: to increase performance. The power of data monitoring, analysis and feedback provision supports the achievement of this goal. Scientific investigations 21 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) and national teams also rely on performance analysis tools to optimize their game preparation. “People in soccer have historically paid little attention to statistics” [18]. Also, there is a general attitude against technology directly influencing the sport. A fear that technology might ruin soccer is noticeable and illustrated by the long-lasting discussion about the implementation of a goal detection system. Nevertheless, the power of numbers is also slowly taking over the so called “beautiful game”. Staffs and coaches start to recognize the benefits of analytics in soccer [18] [19]. But data capturing and analysis soon becomes difficult and the comprehensive approach of current service providers makes systems and services expensive – and therefore exclusive. confirm that performance and skill acquisition tends to increase when relevant feedback is provided in an appropriate manner [7]. Therefore, systems which accurately monitor data and provide proper feedback clearly deliver value to athletes. The commercialization of tracking systems let the trend of self-quantification spread among the whole sports community, including the mass of amateurs. Very popular examples are tracking systems for runners from large sport equipment suppliers (Adidas [8] or Nike [9]) or specialized companies like Fitsense [10], Fitlinxx [11], and many others. Depending on the product, these systems integrate one or more sensors to measure running distance, pace, heart rate and location of the athlete and provide real-time feedback as well as possibilities to visualize and evaluate your data after workouts. Beyond pure data visualization and analysis, product-augmenting services like the possibility to share and compare the gathered data among an online community emphasize the social and fun dimension of sports and tailor the product to the hobbyist‟s needs. Sharing and comparison enrich the sports experience and make it more tangible and enduring. Numerous examples can also be found in less basic forms of individual sports. Applications are not that popular (yet), but cover a wide range from golf [12] to tennis [13]. 2.3. What About an Affordable Solution? Usual prices range from € 20‟000 to € 100‟000 [20] per season for currently available analysis services and are therefore only affordable for professional soccer clubs. Less expensive offerings for adapted services targeting the market of ambitioned amateur clubs are rare. Statzpack [21] offers one of the most basic solutions: a simple iPhone app for easy manual entry of soccer statistics during a game, not considering automatic capturing technologies. Following the simplest approach, it nevertheless provides value to coaches and players. In the area of low cost football analysis tools, German-based Master Coach International markets a stand-alone video editing software named PosiCap [22]. Some similar competing products are on the market. Previously, there have been implications that the development of “a relatively cheap football analysis tool” [23] would meet positive market conditions, at least in northern Europe. Considering also the recent development in the market of running and an emerging positive attitude towards monitoring systems in the soccer community, one can conclude that an increasing market potential for solutions to quantify and evaluate soccer performance at low investments is present. Competitive amateur level teams are interested in investing in technology for performance enhancement. This encourages the development of a respective concept, as presented in this paper. 2.2. Few and Expensive Systems for Soccer “Team sports have probably been the most difficult sporting area to [quantitatively] assess” [6], due to the sheer number of players, their complex interactions and the different positional demands. Focusing on soccer (this is European football for the rest of the world; I call it like this to better differentiate it from Australian football), there are only few commercial systems and services on the market: mainly high-end solutions from premium suppliers. Impire [14], Amisco [15], Prozone [16] or Match Analysis [17] provide comprehensive performance analysis systems and services with individual player tracking and a mass of positional and physical information for live or post match analysis. Video footage from up to twelve cameras is combined with data captured by scouts: people who precisely observe the game and record additional statistics such as touches, passes, tackles, fouls, shots, goals, cards and more. Deliverables range from simple graphical representation of data (e.g. pace of a player during gameplay) to 2D and 3D animation of in-game situations. Customers are television channels and other news organizations which augment their sports coverage. More recently, top soccer clubs 3. Concept for a Soccer Analysis Service 3.1. Using AFL Research as a Basis Extensive investigations into the physical demands of playing Australian Football League (AFL) have been carried out since 2005 by Wisbey et al. [6] [24]. 22 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) shorter distances at high speed” [24] when applied to AFL movement patterns. I assume that errors are of similar order when devices are applied in soccer sports. Especially for sprinting distances, further development has to be considered to reduce errors. The fact that the GPS tracking systems are extensively used in Australian Football, a full-contact sport, implies accurate wearing comfort, no increased risk of injury and no or only marginal influence on player agility. The research is based on GPS data collected in both game and training environments. GPS has proven to be an effective means of player tracking for outdoor team sports [6]. Other researchers conclude similar results, but also show limitations in the “assessment of short, high speed straight line running and efforts involving change of direction” [25]. As training benefits from player workload statistics are recognized, GPS devices are now extensively used among all sixteen AFL teams. The systems record positional variables and speed. From the collected data, several performance indicators are determined. The present concept partially adopts ideas, approaches and conclusions of the work of Wisbey et al. But while these researchers conducted scientific studies as a project funded by the AFL Research Board, I aim at defining a commercial soccer analysis service. 3.4. Core Service The only thing players of a customer‟s team have to do is to wear the GPS devices. After the match or the training, they return the devices to the service provider, which downloads the data and imports it to a custombuilt analysis software. The steady state and movement pattern variables are computed from the data files and are listed in table 1 and 2. All analysis is done after the end of the recording. No analysis in real-time is provided, because this would require additional moveable infrastructure and therefore increase cost. 3.2. Proposal I am proposing a solution to provide a soccer performance analysis system for clubs with ambitioned amateur or semi-professional teams or for clubs which professionally promote young talents. The target group is characterized by the common need for a tool to accurately assess a player‟s performance demand during game play. The aim is to optimize game preparation and training methods resulting in a competitive advantage. At the same time, investment capabilities of possible customers are constrained; high end solutions from premium suppliers are not affordable. The way the target group is approached is therefore the delivery of a basic soccer analysis service, comprising a monitoring system with reduced complexity. In an overall growing market of products assessing performance in sports, the service addresses the almost “untouched” market segment of ambitioned mass sports in soccer, assuming an evolving business potential. Being aware of the limitations of the monitoring system, the focus lies on the provision of a clean and valuable performance analysis, which delivers immediate benefits to the customer. Table 1. Analysis variables for work profile Work Profile Total Distance Average Speed Total Time Exertion Index Exertion Index per Minute Units of Measurement km km/hr mins /mins Table 2. Analysis variables for movement pattern profile Movement Pattern Profile Time Spent in Speed Zones Longest Continuous Time Above a Specified Speed Surges Above/Below a Specified Speed Number of Accelerations 3.3. Monitoring System Number of Decelerations To minimize costs, the monitoring system deliberately omits the setup and operation of camera systems and the evaluation of visual data. The data sensing unit is a commercial GPS device, fitted to the upper back of each player using a harness, similar to the configuration of Wisbey et al. The devices record speed, altitude, latitude and longitude at 5 Hz throughout the duration of practice and store the data internally. The sampling rate results in a GPS error ranging “from 2% for long distances up to 5-20% for Units of Measurement s s # times >/< x km/hr (x to be defined) # Accelerations > x km/hr in 1s (x to be defined) # Decelerations > x km/hr in 1s (x to be defined) Table 1 and 2 take over most of the variables from investigations of Wisbey et al. Definitions of the variables are given in the appendix. The values accurately describe AFL player workloads and are a reasonable first choice to evaluate soccer player demand. Running distances and moving patterns of the two sports are similar to a certain degree. Nevertheless, further investigations have to be undertaken in order to verify this assumption. Of special interest is the 23 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) exertion index, an estimate developed by Wisbey et al. “to quantify the level of physical work completed by players”. Combined with the exertion index per minute, which serves as a measure of game intensity, the two variables clearly provide deeper insight in the physical challenges of soccer. Each data file is associated with information about the player (position, team, etc.) and the game (exhibition or championship game, opposition, type and dimensions of pitch, date and time, etc.). The analysis is done on the level of players, but can be consolidated for position, group or team evaluation. Provision of processed data happens via a web interface. A login function distinguishes different users. Depending on their user role, coaches, staff and players can look at different levels of the analysis. As a default, players might only be able to access their own data and the statistics they are involved in, and coaches can look at the complete analysis. Simple charts and tables, but also more sophisticated visualized analyses are provided. Examples, illustrated with figures 1, 2 and 3, are: (1) histograms of Exertion Index levels, (2) pie charts representing the distribution of Time Spent in Speed Zones across different positions and (3) heat maps, which graphically represent a player‟s positional variable for a whole game. In addition, 2D illustration of the movement of the back four, the midfield or the forward line could be presented. Various ways of data processing and visualization are possible, and the most beneficial and educational analyses have to be evaluated with possible customers before product launch. Insights into physiological demands, but also into tactical behavior of players and of the whole team enable implications for training methods and game preparation. In addition, an increased awareness of the behavior on the pitch is likely to lead to an adaption and improvement of the player‟s performance. Figure 2: Pie chart showing the distribution of Time Spent in Speed Zones across positions [6] Figure 3: Heat map [27] Interfaces to social networks enable players to share their personal statistics with others, if they want to do so. A distribution functionality enriches the sports experience, as illustrated by the tracking systems for runners. Sharing the soccer performance data among an online community reinforces the experience by making it comparable, tangible and enduring. This effect creates considerable additional value. The possibility to compare personal data with figures of top-level players might also be of great interest, especially for young players. For the moment, comparison is mostly limited to the distance covered during a game, since no other values are normally provided during TV broadcasts of soccer games. For certain important international games, additional statistics are provided in the internet [27] [28]. 3.5. Offers for Service Packages Since one-time data capturing makes little sense due to lack of comparable data, the service is generally provided in packages. The customer can buy the evaluation of three distinct units (trainings or games) during the preparation phase for the championship, focusing on the progress of individual players. Another package including the evaluation of five or more successive units illustrates the development of player fatigue and helps prevent injuries. Further configurations are possible. Figure 1: Histogram representing total Exertion Index across all positions [6] 24 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) provided to date, but will considerably influence the long-term success of the proposed service. To maximize probability of success, early prototype deployment and customer involvement is important. 3.6. Additional Services Additional services extend the core service and might or might not be included in a service package. Additional consulting as a “follow-up service” serves as an example. Starting from the findings of the initial analysis, the service supports the development of tailored training methods and preparation scenarios before a game. Cooperation with medical specialists and the experience of the service provider thereby leverage the results of the core service. 4.2. Opportunities Considering the tracking devices, combined accelerometer/GPS units could offer a greater accuracy and resolution in data capturing. In addition, development in sensor technologies, Local Positioning Systems and Near Field Communication technologies could soon completely replace the GPS system. The GPS devices, being a drawback because of their size, might therefore soon become redundant. As long as the new technology provides similar or even more accurate data, the service quality is not affected. Of course, such technologies come at considerable cost, which have to be evaluated in advance. The service follows a basic approach and is therefore easily extendable. Once the technology is accepted (and maybe also allowed in official games) and benefits are shown, product and service development in various directions is possible. 3.7. Price and Promotion The price range for the service packages is clearly below the one of premium suppliers, who charge between € 20‟000 and € 100‟000 per year for the system and for data evaluation [27]. The focus on postmatch analysis, together with the abandonment of cameras and video footage keep costs of the service low. Reusable and only little infrastructure and relatively low running cost for the service provider make this assumption reasonable. Promotion is focused on, but not limited to, shirt advertising. An initial approach is to provide the soccer sports analysis service to a team for free. In return, the team wears jerseys with the advertisement of the service provider. Local newspapers or other media might be interested in data of games of lower leagues and junior leagues. They are possible customers and have to be addressed as well to create further revenue streams. 7. Appendix: GPS Definitions Analysis Variable The following definition are taken from [24]: Total Distance: Measures the total distance travelled during the playing period. Measured in kilometers. Average speed: Total distance divided by total playing duration in hours. Measured in km/hr. Total Time: The total on field playing duration. Measured in minutes. Exertion Index: Exertion index is a quantifiable level of physical load developed by FitSense Australia. This measure allows a relationship to be drawn between game load, fatigue, and the total load between players. The exertion index used to assess GPS data in this project was based on the sum of a weighted instantaneous speed, a weighted accumulated speed over 10 seconds, and a weighted accumulated speed over 60 seconds. This ensures both short sharp efforts, and long sustained efforts are analyzed equally. The weighting is based on a polynomial relationship in which high speeds achieve a higher exertion value than lower speeds. Exertion index is measured in arbitrary units. Please refer to the paper for further details. Exertion Index per Minute: This is a measure of game intensity and is determined by dividing exertion index by playing time. 4. Discussion and Conclusion 4.1. Risks Currently, wearing technical devices during official soccer games is prohibited. From personal experience, I know that regional soccer federations, at least in Switzerland, can adapt the rules. But if they are able to allow GPS devices remains unclear. However, first analyses are constrained to friendly matches, which might hinder a reasonable market penetration. It is of course also possible that soccer players do not accept GPS devices worn during game play. This uncertainty is present until the launch of the service, but might obviously prevent the whole concept from being a success. The general questions remain, whether the trend of quantification will further develop and if the soccer community will finally and entirely accept technology in the game. Answers to these questions cannot be 25 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) [9] [Online] www.nikerunning.com. Access: 09.04.2011. Time Spent in Speed Zones: Time spent between the speeds of x and y km/hr. Provides information on the dispersion of speed throughout the session. Longest Continuous Time above a Specified Speed: The longest period of time the player stays above this speed, without dropping below this speed. Time is recorded even when the player enters a higher speed zone. Provides an indication of the longest continuous effort at varying speeds. Surges above/below a Specified Speed: The number of times the player goes from below (above) this speed to above (below) this speed. Gives an indication of the intermittent nature of the session, and the intensity at which speed peaks occur. Number of Accelerations: The number of times the speed increases by more than x km∙hr-1 in a 1 second time period. This gives an indication as to the accelerations undertaken and how frequently these occur. Accelerations are categorized as moderate (4 km∙hr-1) or rapid (10 km∙hr-1). Number of decelerations: The number of times the speed decreases by more than x km∙hr-1 in a 1 second time period. This gives an indication as to the decelerations required and how frequently these occur. Decelerations are categorized as moderate (4 km∙hr-1) or rapid (10 km∙hr-1). [10] [Online] www.fitsense.co.uk. Access: 09.04.2011. [11] [Online] www.fitlinxx.com. Access: 09.04.2011. [12] [Online] www.thegolfsystem.com. Access: 14.04.2011. [13] [Online] http://www.xtremesportsmachines.com/ contents/enus/d31_Xtreme_Tennis_Software.html. Access: 14.04.2011. [14] [Online] www.bundesliga-datenbank.de/de/home/. Access: 10.04.2011. [15] [Online] www.sport-universal.com. Access: 10.04.2011. [16] [Online] www.prozonesports.com/product-prozone3. Html. Access: 10.04.2011. [17] [Online] www.matchanalysis.com. Access: 10.04.2011. [18] T. Kaplan, „When It Comes to Stats, Soccer Seldom Counts”, New York Times, 08.07.2010. [19] N. Deleon, “Why are we so afraid of technology „ruining‟ soccer? It‟s not like technology hasn‟t been all over the sport since its inception.”, Crunchgear, 03.08.2010. [20] M. Drauz, “Die Bundesliga im Datenrausch”, Frankfurter Allgemeine Zeitung, 18.05.2009. 8. References [21] [Online] www.statzpack.com/overview.php. Access: 10.04.2011. [1] [Online] http://www.p3international.com/products/ special/P4400/P4400-CE.html. Access: 10.04.2011. [2] [Online] 10.04.2011. http://mdlabs.se/sleepcycle/. [22] [Online] www.mastercoach.de. Access: 10.04.2011. Access: [23] D. Setterwall, “Computerised Video Analysis of Football – Technical and Commercial Possibilities for Football Coaching”, Stockholm, 2003. [3] [Online] www.howhappy.dreamhosters.com. Access: 10.04.2011. [24] B. Wisbey, B. Rattray, and D. Pyne, “Quantifying Changes in AFL Player Game Demands Using GPS Tracking – 2010 Season”, AFL Research Board Report, University of Canberra, Canberra, 2010. [4] G. Wolf, “Know Thyself: Tracking Every Facet of Life, from Sleep to Mood to Pain, 24/7/365”, Wired Magazine, 17.07.2009 [5] M. McClusky, “The Nike Experiment: How the Shoe giant Unleashed the Power of Personal Metrics”, Wired Magazine, 17.07.2009. [25] D. Jennings et al., “The validity and reliability of GPS units for measuring distance in team sport specific running patterns”, International Journal of Sports Physiology and Performance, Victoria University, Melbourne, 09.2010, pp. 328-341. [6] B. Wisbey, P. Montgomery, “Quantifying AFL Player Game Demands Using GPS Tracking – 2005 Season”, AFL Research Board Report, FitSense Australia, Canberra, 2005. [26] P. Gastin and K. Williams, “Accuracy of 1 Hz and 5 Hz GPS devices to measure movement patterns in team sport activities.”, Deakin University, Melbourne, 2010. [7] D.G. Liebermann et al., “Advances in the Application of Information Technology to Sport Performance”, Journal of Sports Sciences, Taylor & Francis Ltd, London, 2002, pp. 755-769. [27] [Online] http://wwos.ninemsn.com.au/article.aspx? id=830454. Access: 16.05.2011. [8] [Online] www.micoach.com. Access: 09.04.2011. [28] [Online] http://de.uefa.com/uefachampionsleague/ statistics/index.html. Access: 16.05.2011. 26 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) The value of “the Internet of Things-mashup” for enterprises Dominique Mirandolle mirandod@student.ethz.ch they want the data to appear in their own application. An example is the combination of articles from The New York Times and Flickr, in which pictures are shown automatically according to the news by selecting key words from the selected article. One specific category of mashups is valuable for enterprises in specific, namely the business process mashup [2][3]. Many enterprises invest in large information systems that serve the overall goals of the company. However, in a dynamic environment the need arises for smaller applications for specific business needs that do not fit in the architecture of the overall information system. Such business problem solving applications can also be regarded to as „situational applications‟ [4], and could in most cases very well be developed in the form of a mashup. This tendency supports the need for Service Oriented Architectures, where each business process individually can (re)use specific information technology services based on their own requirements [5]. The enterprise mashup in specific can be defined as “a Web-based resource that combines existing resources, be it content, data or application functionality, from more than one resource in enterprise environments by empowering the actual end-users to create and adapt individual information centric and situational applications” [6]. Next to mashups, we elaborate on a second topic in this paper, namely the Internet of Things. This concept entails the phenomenon in which every object in our world can be made „smart‟ by adding a tiny computer to it with a connection to the internet [7]. By measuring specific data, for example location, temperature or altitude, information of value can be obtained from each „thing‟ and additionally from all the „things‟ in relation to each other. The obtained data can be used in numerous ways, and also in the form of a mashup. An example is the combination of live tracking data of the public transport in Zurich and Google maps by local.ch, which creates an overview of the city with moving trams on a map. Now that it is discussed what (enterprise) mashups entail, and how they can come forth from the Internet of Things, the main question of this paper is proposed as follows: Abstract Mashups appear more and more in the enterprise domain ever since the need for specific business applications started to arise. This paper discusses mashups and more specific their appearance in enterprises. The second topic of this paper is the Internet of Things, a phenomenon which entails „smart‟, internet connected, objects in the physical world. By bringing these two topics together, it is described how the development of mashups can be supported by the Internet of Things and how this leads to the creation of even more interesting applications. Additionally, it is discussed what the value of “the Internet of Things-mashup” can entail for enterprises. 1. Introduction The mashup is one of the latest concepts to appear in the Web 2.0 domain. A mashup is “a way to create new Web applications by combining existing Web resources utilizing data and Web APIs” [1]. This has turned out to be especially useful for end users who are aware of the specific requirements they want an application to contain. An example of a mashup is the Microsoft Outlook Social Connector, which combines data from various social networks (e.g. LinkedIn, Facebook, MySpace) with your personal address book in Microsoft Outlook. Numerous mashups exist based on Google Maps, for example the crime map. This mashup uses the publicly accessible data from a police department in a specific area to mark which neighborhoods are safe and which have a high rate of crimes. This could even go as far as rating what type of crime is most likely to appear in certain areas. Instead of crime rates, maps can also be mashed with for example data from real estate agents, to show potential buyers in which areas houses are available. Since the introduction of the mashup, many platforms, for example the IBM Mashup Center, have been developed to make it as easy as possible for the end user to take part in the „mashing up‟ of various web sources. Another mashup platform is Yahoo! Pipes, which offers a graphical interface in which users can combine various web feeds, web pages or other web sources through a „pipe‟ and define exactly how 27 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) In what way can mashups, based on the Internet of Things, be of any value for enterprises? By answering this question it is illustrated how mashups, based on the Internet of Things, can be used in enterprises. Additionally, some possible future applications of the usage of these two concepts combined are described. This paper is structured as follows. In the second section related work regarding mashups and the Internet of Things is discussed. The third part elaborates on the usefulness of these concepts for enterprises. Additionally, an example of a future application is given. Finally, the conclusion summarizes in what way “the Internet of Thingsmashup” can be of value for enterprises. to the changing needs of the dynamic business environment. Guinard et al. [8] present a resource oriented approach to develop enterprise mashups while integrating the Internet of Things. They discuss that implementing „smart things‟ (e.g. Wireles Sensor Networks) into an information system requires a substantial effort and is therefore most suitable for static environments. However, most enterprises operate in a dynamic environment. This is the reason why Guinard et al. propose the Representational State Transfer (REST) approach, in order to “increase interoperability for a looser coupling between parts of distributed applications” [8]. One of the basic rules of REST is that every „thing‟ becomes data-centric instead of operation-centric and thus turns into a resource. This diminishes the footprint of the application on these resources. Moreover, the internet is used as an application platform in which all the resources are accessible through web browsers. This loose coupling makes it possible to integrate new devices or „things‟ on a regular basis and makes the information system light weighted and more simple. As an example Guinard et al. [8] describe a composite application in which a sensor node updates the temperature status of a shipment in an Enterprise Resource Planning (ERP) system. According to REST rules, the sensor that measures the temperature is a resource and will send data only when this is requested through a web browser. In order to integrate this step into the enterprise‟s ERP system, SAP MII was used. This mashup editor allows end users to easily select resources and create applications for their specific business needs. By describing this example, the authors show that by reusing existing web standards and the REST approach, physical objects can become part of information networks in a simple way. Gershenfeld et al. [9] also recognize the need for limiting the „footprint‟ of an application when it comes to smart things as resources. They discuss the „less is more‟ attribute of the Internet of Things and give an example of a smart medication shelf. Each bottle of pills contained a tag that channels data to a network regarding how many pills are still left in the bottle and whether the owner is on schedule with taking his medication. Instead of programming a specific tag reader to acquire data from the bottles, the data is send to the network first and handled there. This method of operating requires more bandwidth, but according to the authors speed should be sacrificed for interoperability. Another research in the domain of simplifying the use of data measured by sensors in „things‟, like Guinard et al. [8] describe, is that of Le Phuoc [10]. He proposes a platform, called SensorMasher, to give 2. Related work In this section previous research on how mashups can be applied in enterprises is discussed. Additionally, previous research on business aspects of the Internet of Things is looked into, in order to bring the two topics of this paper together. De Vrieze et al. [2] discuss various criteria for enterprise mashups. They single out the business process mashup as being the most valuable for enterprises. According to this research enterprise mashups should support the end user in creating and customizing the application, making it as end user friendly as possible. Additionally, they describe how the mashup should be customizable to any other situation of individual within the same enterprise information system context. A final characteristic they discuss is the new insights that mashing up the data should offer. De Vrieze et al. [2] also define some key issues in the area of enterprise mashups. Developing a mashup is more than just selecting different sources of data. An important aspect is defining how the data can be used as a service and in which form (e.g. widget, feed, web service) it should be offered. Often the individual services turn out to be too „small‟ to offer significant value to the entire set of business processes. According to De Vrieze et al. [2] the services need to be „elevated‟ in order to be useful for the business process as a whole. Hoyer et al. [6] propose a concept in which they describe how mashups can be used by enterprises. This concept focuses on commons-based peer production, and sees users as “knowledge workers who work primarily with information or develop and use knowledge in the democratized workspace” [6]. One of the main characteristics Hoyer et al. [6] describe is that mashups should be a group effort instead of an individual achievement, in order to respond efficiently 28 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) extension of the first paradigm. Decomposition of the business processes leads to an increase of scalability and performance and allows better decision making. The decentralization of the processes gives way to local decision making, which makes it easier to implement actuators (smart things that influence the real world), that can become active participants in the business process. Even though various benefits are described, Haller et al. conclude that the industry is currently still reluctant to widely adopt the Internet of Things. The main reasons behind this include technical challenges and the unclearness of real business cases. (non-technical) users easy access to data obtained by sensors. Through a graphical interface, users can select those data sources applicable to their (business) needs. The interesting aspect of this platform is that it not only combines sensor data with static data on the web, but also sensor data amongst each other. Le Phuoc refers to this specific type of mashup as a Sensor Mashup. A given example is the combination of sensor data from a weather station and a traffic camera in a particular area, and additionally the data from a chest strap that measures a person‟s heartbeat. Interesting analyses can be made when combining these three data sources into one application. Williams [11] discusses the „real business case‟ of the Internet of Things, since according to him the promises that the concept made already ten years ago did not come true. He debates whether the concept is of any business value for the current market. One of his arguments is that the Internet of Things is a concept invented by academics, while there is no demand from the market (yet). Additionally, he stresses the importance that has been put upon the prices of RFID tags, which were supposed to decrease much more according to predictions than they did in reality. The real business case for the Internet of Things according to Williams lies within the need for specific real time data in information systems from real time items. Having said this, he concludes that for some things there will never be a need to make them smart. For other things, it will suffice to make them interrogatable. Out of all objects in our physical world a pyramid can be created as a structural hierarchy, which describes the need for objects to be smart and / or connected to a network. His final remark is that for the foreseeable future there is no need for most items to be connected. Haller et al. [12] also discuss the business value of the Internet of Things and more in specific for enterprises. According to this research, the Internet of Things fits into the future development of a web-based service economy. Haller et al. describe the „future internet‟ in which a platform offers the combination (mashing up) of numerous services and data resources. The Internet of Things has a role of filling in the gap between the virtual data and the physical world. Two major paradigms are described that can establish economic benefit from the Internet of Things. The first one is Real World Visibility, and can deliver an enterprise a competitive advantage by increasing accuracy and timeliness of information about business processes. The better these processes are monitored, the easier it is to improve or reshape them. Fleisch [7] refers to this as „high-resolution management‟. The second paradigm described by Haller et al. [12] is Business Process Decomposition, which is an 3. The Internet of Things-mashup in enterprises In this section I discuss the valuable characteristics of the Internet of Things-mashup for enterprises, as well as some key issues that enterprises have to deal with, according to the previously discussed related research. Keeping these values and issues in mind, I propose a possible application of an Internet of Things-mashup for an enterprise in the manufacturing domain. 3.1. Value The value of the Internet of Things-mashup lies, according to the discussed related research, in the following areas: - Business process management support. Each business process in an enterprise requires different information and data. With an Internet of Thingsmashup, specific, accurate and timeliness data about real live situations and business processes can be monitored. The value of the mashup in particular here is the support of the loose coupling of services in a Service Oriented Architecture. Each department or function in an enterprise is able to select those applications required for their business and mash them back together in a useful IT product. - Decision making support. Since the Internet of Things-mashup is easy to adapt or reshape for each end user in the enterprise, decision making becomes easier from a low level in the enterprise on. Decisions can be based on accurate measurements and observations and will be therefore more efficient. Additionally, decisions will not necessarily have to be carried out by human interaction, since „things‟ are able to communicate among each other (and in specific to actuators) to initiate a following step in the business process. - Easy access to new insights. Since platforms make it easy for users to query the data that they require, new insights can be easily offered. When 29 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) manufacturing plant products are assembled by various activities, conducted by different employees. In the plant, the following „things‟ are being measured: 1. Temperature; 2. Air humidity; 3. Intensity of the light; 4. Noise level; 5. Movement of the employees; 6. Identity of specific employee by RFID tag in a badge that employees carry around; 7. Identity of the product by RFID tag; 8. Number of incorrectly assembled products; 9. Number of correctly assembled products. Figure 1 shows a schematic overview of the implementation of the smart things in a manufacturing plant that could measure the above mentioned data. The application behind the mashup combines all these data objects in order to establish in which conditions the employees work most effective and the least products are rejected because of incorrect assembly. Since the products and employees can be identified individually, it can exactly be seen which employees contribute to the most correctly assembled products. The sensors that measure the movements of these employees can therefore identify the most effective movements and techniques for a specific part of the assembly. Employees that outshine in effectiveness can give training to others, in order to improve their skills. Additionally, the influence of temperature, air humidity, light intensity and noise can be measured on the number of correctly assembled products. By doing this, an optimal combination of these factors of the assembly products can be identified. Once it is clear which these optimal conditions are, they can be set as a standard and the „things‟ can act as actuators to self regulate these conditions. In order to make this application a true mash up, the data could be shared among other partner companies. By combining data online about the work environments, combinations can be measured and a predicting algorithm on optimal working conditions could be established of plants in a certain domain. Additionally, (supplying) partners could make use of the data stream in order to verify how much material should be delivered or what type of material match the temperature and air conditions best. This could be of particular importance in processing food. The above described Internet of Things-mashup delivers value in all three elements described in section 3.1. It supports the business process since accurate data about real live „things‟ is added to it. The application also supports decision making, since information is given on what conditions lead to the most optimal outcome. Decisions on the design of the assembly combining for example sales numbers of an ice cream stand with measurements of temperature and location, interesting new insights can be found. 3.2. Key issues The key issues that can be defined according to the discussed related research are the following: - Granularity and relevance. When an Internet of Things-mashup supports a very local fragment of a business process, the significance of the improvement on the total business process might be questioned. The service that is delivered should therefore not be too individualistic or detailed. Additionally, there should be a clear need for the data that is generated with the Internet of Thingsmashup. In other words, it should be relevant to the business. - Design. It is important for an application to have a usable layout and interface that can be used by any end user. Since the Internet of Things-mashup within companies can be created by the end users themselves, and not by software designers, they might struggle with the form and shape they should give to the application to have efficient usability. - Technology. The technology for the Internet of Things should be well thought out, since the „computers‟ placed on the things will be small and have a small capacity. A „light‟ network that connects all „things‟ and is easily accessible should be designed in order to support the use of the data in a dynamic environment. Figure 1. Smart things in a manufacturing plant 3.3. Possible application: “Optimal assembly process identifier and regulator” In this section I propose a possible Internet of Things-mashup in the manufacturing domain. In this 30 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) process are supported. The application also offers new insights thanks to combination of various data. It can now become clear for example, that the increase of incorrectly assembled products in the summer time is not due to the higher temperatures, but because of the absence of a certain combination of employees. The application should also take in mind the three areas of key issues that are defined in section 3.2. The granularity of the mashup should be established in such a way that the improvement is relevant for the overall business process. Since this is an assembly process, each fragment of the process is important. Even though the mashup combines data on a low level in the process, the influences on the overall process are of importance and make the application thus relevant. Since the data is available throughout the entire enterprise, higher up managers can also consult the application to acquire their own relevant information. Buyers in the enterprise can for example measure the efficiency with the use of certain parts. The design of the Internet of Things-mashup is in this case done by the managers of the assembly process. Their experience in designing these processes should give them enough knowledge to design an interface that gives them the data that they require. Since the data is available throughout the entire enterprise, higher up managers can also consult the application to acquire their own relevant information. Buyers in the enterprise can for example measure the efficiency with the use of certain parts. The technology used in this application, consists mostly of „regular‟ hardware (e.g. thermometers, RFID tags, decibel meter, cameras). In order to keep the network „light‟, the data should be sent to a server first before it is analyzed or edited. By doing this, the „things‟ do not need much capacity to function. For example, the images that the cameras make of employees can be analyzed into patterns with specialized software after the images have been captured. The camera only sends out raw data. have to do with granularity and relevance, design and technology. After answering the research question I have proposed an Internet of Things-mashup for a manufacturing plant, called “Optimal assembly process identifier and regulator”. With this example I have illustrated the three main areas in which value can be created for an enterprise with an Internet of Thingsmashup and how the key issues can be overcome. It has to be noted, that due to lack of time and space, the literature research in this paper is quite limited. Therefore, future research can be conducted more elaborately in both the domains of this paper in order to establish a framework which „guides‟ enterprises to the creation of valuable Internet of Things-mashups conform to their business needs. 5. References [1] D. Benslimane, S. Dustdar, and A. Sheth, “Services mashups: The new generation of web applications,” IEEE Internet Computing, vol. 12, no. 5, 2008, pp. 13-15 [2] P. de Vrieze, L. Xu, A. Bouguettaya, J. Yang, and J. Chen, “Process-oriented Enterprise Mashups,” 2009 Workshops at the Grid and Pervasive Computing Conference, 2009, pp.74 – 71 [3] T. Hermanns, D. Mirandolle, “Improving communication in real estate project initiation: an explorative case study using a mashup”, Proceeding of the 20th Annual Conference of the International Information Management Association, Utrecht, 2010 [4] A. Jhingran, Enterprise Information Mashups, Proceedings of the 32nd international conference on Very large data bases, VLDB, 2006, pp. 3-4 [5] B. Büchel, T. Janner, C. Schroth, and V. Hoyer, Enterprise Mashup vs. Service Composition: What fits to reach the next stage in End-User Development?, Wissensmanagement, vol. 145 of LNI, 2009, pp. 260-269 4. Conclusion [6] Hoyer, V., & Stanoevska-Slabeva, K. Design Principles of Enterprise Mashups. Wissensmanagement, 2009, 242-253 In this paper I have reviewed literature in the domains of enterprise mashups and the Internet of Things, in order to find out what the value is of the “Internet of Things-mashup” for enterprises. By exploring related research in both domains I have found three areas in which an Internet of Thingsmashup can add value to an enterprise. These are: business process management support, decision making support and easy access to new insights. Additionally, I have found three key issues of applying such a mashup in an enterprise domain. These issues [7] E. Fleisch, “What is the internet of things?: an economic perspective”, ITEM-HSG, Auto-ID Lab St. Gallen, 2010 [8] D. Guinard, V. Trifa, T. Pham, O. Liechti, Towards Physical Mashups in the Web of Things, Sixth International Conference on Networked Sensing Systems (INSS), Pittsburgh PA, 2009, pp. 1-4 [9] N. Gershenfeld, R. Krikorian, D. Cohen, The Internet of Things, Scientific American, vol. 291, 2004, pp. 76 - 81 31 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) [10] D. Le Phuoc, SensorMasher: publishing and building mashup of sensor data, Digital Enterprise Research Insitute, National University of Ireland, 2009, pp. 1-5 [12] S. Haller, S. Karnouskos, C. Schroth, The Internet of Things in an Enterprise Context, Lecture Notes in Computer Science, vol. 5468, 2009, pp. 14-28 [11] B. Williams, What is the real business case for the internet of things?, Synthesis Journal, ITSC, 2008, pp. 127135 32 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) Smart Cities and Internet of Things Oliver Haubensak ETH-MTEC oliver.haubensak@gmail.com April 14th, 2011 projects being in their starting phase. Masdar City and PlanIT Valley will once built, produce more renewable energy than they consume, as well as recycle most of the water used. Furthermore, I am presenting an already installed smart solution: monitoring the traffic in Zaragoza, Spain. Abstract Smart city is still a fuzzy concept and being broadly used. In this paper I am going to elaborate opportunities and challenges as well as explain the reason why there is an urge for smart cities. Smart city concepts will be presented, among them Masdar City, a city entirely built in the desert, which will once be home for 50’000 inhabitants and claims to produce entirely renewable energy for the whole consumption need as well as recycle 80% of the used water. 2. Opportunities and Challenges Quickly we can see that there is an opportunity of many applications in the field of the internet of things in any of the mentioned fields. “The internet is extending its reach to the real world trough innovations” [3]. Where opportunities exist we can also expect challenges [4]. In order to have increased returns and a successful system, we require an important number of devices / users and interactions. Devices and platforms need to be somehow heterogeneous to reach interoperability. A coming challenge will be the mining and processing of the data as well as providing secure access and continuously control privacy. Unified enriched and interoperable data description models need to be provided. A further challenge will be mobility. Ad-hoc access and service continuity will be important. 1. Introduction Smart City is a term used in many publications and articles. It seems that this label is somehow still a fuzzy and inconsistent concept and needs to be clarified for this paper. The concept discussed in “Smart cities Ranking of European medium-sized cities” [2] seems appropriate for the first attempt. Smart cities can be slit up in six dimensions: Smart economy, smart people, smart governance, smart mobility, smart environment and smart living. These dimensions are based on competitiveness, social and human capital, participation, transport and ICT, natural resources and quality of life. This definition was used in order to rank cities in their “smartness”. For example, innovative spirit is part of the Smart Economy dimension, which is in turn measured by patent applications per inhabitant. After looking a little bit further, this definition could be found: A city can be called smart,” when investments in human and social capital and traditional (transport) and modern (ICT) communication infrastructure fuel sustainable economic growth and a high quality of life, with a wise management of natural resources, through participatory governance”[17]. This definition defines exactly the projects I am going to present in this paper. In the next sections, I will introduce the reader to opportunities and challenges, why we need smart cities and the path towards them. Finally I will present Masdar City, PlanIT Valley and Smart Santander. All 3. Smart Cities – But why? The question arises - why do we need smart cities? The answer is closely connected with our today‟s society. In many countries we can see the development that younger people move for education or better work prospects to urban areas and most of them are not willing to give up these advantages. The result is that already today almost 60% of the world‟s population lives in urban areas [1]. Cities account for 75% of greenhouse emissions, while only occupying 2% of worlds surface [6]. It is expected that the amount of people living in urban areas will double until 2050 and by 2015 1.2 billion cars will be on the road – making 1 car per 6 people [6]. Another factor is demographics. The population is aging and living longer due to 33 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) they can alter collectively to get a more efficient and flexible system [5]. advance in medicine and many other areas. This factor is letting the population further grow and the need of more space becomes obvious. Cities become increasingly more competitive. Success criteria‟s are attracting business, creating jobs, offer a rich culture and attract tourism. All this also brings draw-backs, as citizens become more demanding trough this competition. The most obvious problems arise out of the main infrastructures such as electricity networks, transport networks and waste management. These infrastructures need to be well planned ahead in order not to collapse within time. Resources are getting scarcer in the coming years, looking for alternative and sustainable use becomes a core importance. This brings us to the last and maybe the most important drivers for Smart Cities: Climate Change. As we all know, our live is locked-in to carbon technologies. We ship fruits around the world, use cars, take planes, outsource whole productions to Asia and produce electricity with coal. Green house targets have been set, but it seems that reaching these goals will be a big challenge in the coming years. We are locked-in to a huge system between industries, government and society. Many Smart cities try to elaborate new systems and technologies for a sustainable development. Many Information and Communications Technologies (ICT) improved services on department levels such as mobility, eGovernment and such. These technologies make services more efficient and lead to a better informed citizen. Many cities try now to push this concept of smart cities further and search for solutions over the limits of the departmental level to a city wide approach. Such approaches will create economies of scale and scope. This resulting in running the city more efficiently, providing a more interesting place to work and live, encouraging resource efficiency towards climate change mitigation and creation of jobs [5]. Key of many applications will be measuring and sensing. Systems will adapt and learn from infrastructures and activities reporting their state and behavior [5]. A famous quote1 says that „if you can‟t measure it, you can‟t manage it” and can be applied in this framework. Managing of for example infrastructures can reach new levels through gathering data and constant learning from millions of nodes reporting their state and/or behavior in real-time. A set of development areas is presented in the table shown below. 30% of carbon emissions could be reduced in London just trough behavior change and a project in Helsinki states that even 50% of a citizens carbon emission are due to their lifestyle choices [5]. Two main drivers for behavioral change are social proof and active learning [5]. Trough new development like social media this becomes available. Smart Metering is a broadly discussed topic within the internet of things and many new developments are already on the market. Those devices are measuring the consumption and through the real time feedback, stimulating its user to adapt his behavior. This might be with comparing to himself or over social platforms and interfaces with the rest of the world. This confirming the statement of the two main drivers for behavioral change. City System Example Smart Solution Transportation Public transport monitoring Traffic monitoring and routing Municipal fleet management Parking information Electronic Records Management Remote Monitoring Systems Hospital Asset Management eLearning Connected Campuses Video Surveillance: video analytics/workflow Enhanced Emergency Systems Smart-Meters Monitoring heating, lighting, security systems, water management, structure Electronic sensors to detect toxicity in landfills Waste-tracking Improve the efficiency of waste collection Facilitate automation of city processes eGovernment Healthcare Education 4. The path to a smart city Public Safety and Security Building Management Today most of us carry a smartphone. These phones are equipped with internet connection, positioning systems, accelerometers and some with RFID readers. With the already today existing well developed fast broadband network in urban areas, we have the already important necessary tools towards a smart city. It is fundamental that cities need to provide the architecture for future innovations, so that companies can innovate. Also citizens need to realize the real value of future innovations and contribute their part. Smart cities help to make urban systems clear, simple and responsive trough modern technology. The citizen shouldn‟t see the city anymore as rigid and inflexible, but should start and be engaged to interact - finally to realize that Waste Management City Administration Development Areas, adapted from Forrester [18] In some papers we can already find the term City 2.0 which consists of the vision of a city where the urban environment‟s constantly changing dynamics can be monitored [7]. This includes but is not restricted to 1 34 Source is controversial discussed Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) Masdar City, an entire new city for 50‟000 inhabitants which should run carbon-free as well as the SmartSantander project, PlanIT Valley and two concrete applications. snow/rainfall, traffic, movement of citizens and usage of resources (electricity, water, gas and sewage systems). The idea behind is to be able to act before problems arise. Changing the traffic pattern dynamically might be one of these advantages. 5.1. Masdar City Monitoring the streets of a city and measuring environmental figures is already reality in many cites. Already in 1995, Redwood City in California started to deploy acoustic sensors in their streets, able to detect gun shots. The police are then able to respond without an emergency call and know immediately where to go. This system is now deployed in more than 30 U.S. cities [7]. Many cities also have a vast network of video surveillance of streets on public infrastructures such as public transport. Also cities start to install sensors, measuring environmental factors, like emissions. Private companies gather data from citizens - let us just think at mobile phone operators. All those already existing sensors and its data together mashedup give us already huge opportunities. Let us assume that almost every citizen is in the possession of a mobile phone. Movements of citizens walking, in public transport or in private cars could be tracked and patterns analyzed. This could be used for planning and future decisions for example adaptions of public transport. Also traffic jams could be spotted immediately, citizens informed and traffic rerouted. All this are excellent ideas, but in reality a real challenge to realize. First there are the privacy concerns of users which need to be considered. A citizen probably doesn‟t mind pollutions sensors, but might be more sensible to cameras and sensors which detect their motion or follow their use of resources. Also barriers can be seen in the law of each country and how the government and the industry have to handle the data regarding privacy concerns. We have seen in many countries that cities departments working poorly together and such ideas in general need a rethinking of the rigid patterns existing within cities administrations. Masdar City [8] is planned in the desert outside of Abu Dhabi, covering 6 square kilometers and will be home to 50‟000 inhabitants, up to 1‟500 businesses and a new university. The aim of the Masdar City is clear: Fossil fuel free zone, 100% renewable energies and zero waste. 80% of the used water will be recycled onsite. Proposed Masterplan of Masdar City [8] Private vehicles will be prohibited in the city. Modes of transport will be, electric vehicles, cycling, a so called Personal Rapid Transit (PRT) system and a Light Rail System (LRT). The transport concept is as such that there is a maximum distance of 200 meters to the next station. An artificial basement will be created so that the pedestrian level will be raised to accommodate the various systems and transport infrastructure. In the final stage there should be 3‟000 PRT vehicles ( for 4 adults + 2 children each) installed serving over 85 stations and making 130‟000 trips a day. The longest journey should take no longer than 10 minutes. A PRT vehicle can run up to 60km on a 1.5 hour charge with its Lithium-Phosphate batteries. On the same basis a Rapid Transit System (RTS) will be deployed, able to transport 2 pallets up to 1‟600kg per trip [9]. Although it seems that the PRT System has been partly In the field of smart cities there is a lot of development and research going on at the moment. In the next section I will introduce you to some of the most important projects at the moment. 5. Current Projects As already stated earlier in this paper is that the term “smart city” is used broadly. There are plans for entire cities, business parks as well as many single projects which can contribute to the efficiency of a resource. In this section I like to introduce the master plan of 35 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) abandoned at this time and buses or trams might be implemented in the plan as well. The first phase was planned to be finished by 2009, but now rescheduled to 2015 due to the financial crisis and missing funds. Finalization of the whole project should be 2025 [10]. At the time of writing, the first buildings are finished and the Masdar Institute is running since last year. There is also a small network of PRT already running. In terms of Internet of Things not much is outlined within this project, but a lot is imaginable. Most can be found in a promotional video: «During the planning and design of Masdar City, the engineers identified more than 25 software applications that would be required to create and maintain a sustainable city. These applications tie into and control the smart grid, smart appliances, smart buildings, transportation systems and the city wide public information systems. Many of these systems relay real-time sustainability and energy consumption information to the engineers of Masdar City. » [11] Further research gives us some clearer and more profound insight into those plans. Masdar City will test the new smart appliances from General Electric (GE) for example. These appliances include refrigerators, stoves and washer/dryer machines which will be equipped with smart meters and connected to the cities smart grid. This will allow transmitting real-time consumption data and allows that non-essential functions can be run during off-peak usage hours [12]. Planned architecture of SmartSantander [13] A big difference to common research facilities is that this project will be deployed in the real world and not just within the walls of a laboratory. Parking monitoring has been chosen to be the first application within this framework. Parking is a big issue in almost every city. The application will not only focus on parking availability, but also on a wider approach like traffic situation and environmental issues [14]. Other coming projects might include environmental monitoring where users can see a dynamic map of the environment (actual pollution), Control of buses and taxis stops and monitoring of public bicycles and Urban waste management. Those projects will face a couple of common challenges as all these sensors need to be theft- and weatherproof, need to be connected and probably the biggest issue that they need power [14]. Almost none of the subprojects is known yet as the program just started. During this 36 month program, SmartSantander will provide two Open Calls where external users can run experiments using this framework and also be funded. 5.2. Smart Santander Maybe one of the most important projects in respect of Internet of Things and Smart Cities is the SmartSantander Project in Spain. The city in the north of Spain counts 180‟000 inhabitants. This year already 8000 sensor should be installed and up to 20‟000 for completion of the project. This project is supported by many important companies and universities as well as supported by the EU with 8.7M Euros [14]. The aim is to create the world‟s first and unique experimental research facility for applications in the field of Internet of Things. Key functions will be to validate approaches to the model of Internet of Things. Evaluating management protocols and mechanisms, device technologies, security and identity management will be of high importance. Finally also the assessing of social acceptance of Internet of Things Services and Technologies within a real population will be the aim of this project [13]. 5.3. PlanIT Valley In parallel of Masdar City there are similar plans in Portugal. In the next years, they will build a city, called PlanIT Valley [15], on 1700 hectares of land outside of Porto. The aims are high as for Madar City: the city should produce 150% of energy needed, reducing waste and recycle most of the water. In this project, financing will come entirely from private equity. This is particularly interesting as companies can become partners when paying a yearly membership fee. This entitles them to be part of the PlanIT Network and help to develop the city. The planners see this city as an open test bed where companies can develop new services. Some new developments will be successful, some won‟t. 36 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) existing electricity grid. Without a robust infrastructure, this concept won‟t work. Basically the problems in a grid are the different consumption and production patterns during the day and seasons. Consumption has their peaks at midday and evenings. Depending on the type of power production, for example solar or wind power can be pretty inconstant. This can be solved through an intelligent system, where appliances can send and receive data. We discussed those examples for Masdar City and their cooperation with GE and their new appliances. Before the idea of this project was born, one of the initiators saw the problem of purchasing in the building construction. Every company has their own supplychain and too much waste accrues. For example it took 5 years to build an airplane factory and assembly line and for the more complex airplane it just takes 3 month to fully assemble it. Those learning‟s from other industries should now be applied on the traditional construction industry which is becoming outdated with the new techniques, designs and processes. Through these improvements, the initiators hope to save up to 40% of building cost and hope to construct buildings up to 50% faster. It is obvious that Internet of Things will help these processes for example trough supplymanagement, for example RFID tagging. PlanIT have important partners such as Microsoft, Cisco, Massachusetts Institute of Technology and McLaren Electronic Systems onboard. The idea is to implement an Urban Operating System (UOS), a common platform for enabling a smart city to evolve in each aspect. The system will be fed by a vast sensor network spread out over the whole city and in every function of the urban environment. Data will be collected, combined and analyzed in order to derive better knowledge over different parts of the urbanization. Data is planned to be stored indefinitely. This helps the city to continuously optimize its system and to predict possible outcomes. The system will be able to react real-time, for example avoid outages of electricity or water before it even happens, or traffic control. In case of an accident, the system can predict impacts of the coming hours by merging different data such as time, season or weather. Traffic will be rerouted and means of public transportation made available. New features and applications can be added at a later point of time to the UOS. This is leading to new developments and business plans for the partners of the PlanIT project. On the base of this plan, a reliable and vast sensor network is needed. Those nodes need to sense physical states, properties and/or events in the environment and finally send the acquired data to the UOS. Data also needs to be received by the nodes (houses, traffic control, heating, lighting…). Lightning control should be highly intelligent. The system will analyze the user in such an extent that it will recognize its patterns and merge it with the knowledge of weather and sunlight status. Finally the system will be able to overtake and knows the needs of its user, even the preferences when cooking or watching television. Whatever smart city project we are looking at, smart grid is playing an important role. It sounds like it is something new, but it‟s just an enhancement of the 5.4. Smart Applications As you probably recognized, there is not much information of complete projects. Before coming to the conclusion of this paper, I like to introduce the reader to two running concepts in the field of sensing which we can well imagine becoming part in the already mentioned smart city projects. Android-Application showing Zaragoza’s real-time traffic [16] One of them is the traffic monitoring system in Zaragoza, Spain [16]. 150 sensors set up all over the city can monitor up to 90% of the urban routes. The data is collected by sensors which are able to detect mobile devices (Bluetooth, WIFI frequencies). The data is then forwarded to a server for processing. The traffic patterns will be displayed at the traffic control center. Also displays within the city are used to display 37 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) average travel times and warnings. Citizens can access the real-time status of the roads by internet over their smartphones or at home. 6. Conclusions As defined in the introduction, we can think about many new applications to come in every of the six dimensions of a smart city. Mostly concepts focus on scarce resources, but we shouldn‟t just restrict us to that field. There are many applications making daily life more interesting and opens new fields of businesses. You probably already found out, that within these master plans of smart cities, there isn‟t much information on Internet of Things developments. We can just imagine how it might look like. Architecture of Zaragozas Traffic System [16] The data serves the city to manage better their traffic wardens and to learn the dynamics of their city. Further they will help the government to implement new adequate policies. Another important discussion is sensors build into the infrastructure, mainly buildings. Already since some years, larger bridges are equipped with sensors and are monitored for oscillations. The Fraunhofer institute and MPA Braunschweig in Germany developed a new sensor, able to sense rusting parts and cavities in bridge structures. Mainly in the northern hemisphere, salt is used to defrost roads in the winter. This salt can reach important metal structures in bridges and create cavities. Also bridges close to the sea are affected by the harsh environment. In the worst case bridges can collapse due to these impacts. There will be many obstacles to overcome. Does the citizen actually need to give up a part of his privacy? Does he want that the city knows when he left home or boarded a bus? Privacy concern will play an important role in this field, so that a smart city doesn‟t converge to a censored and over controlled area. The developers and initiators of such projects need to think a little bit further than just the building and initiation phases. What will be years after the completion of the project? The wireless networks and its application need to be open-source and compatible with new applications, so developers can continuously improve the network and its appliances. There is a need of common language, i.e. protocols. Let us just think at all the different companies developing smart appliances for the smart grid. To keep such a network open for new innovations, keep it stable and reliable and finally consider privacy will be a major challenge. New Sensor, able to detect rust in bridges – developed by the Fraunhofer Institute and MPA Braunschweig [16] This sensor isn‟t equipped with a power source. In order to read the data, power is applied trough induction and the data acquired. With this data, the structure of the bridge can be monitored constantly and maintenance coordinated accordingly. At the time the institute is testing the system on a test bridge. Those are just two “little” applications how we can make a city smarter and we can imagine that there are endless of ideas possible to develop and implement in the future. 38 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) 20-000-sensoren-ueberwachen-spanische-stadtsantander.html Retrieved 23-03-2011 [15] “Living PlanIT”, Living PlanIT SA, Retrieved 0404-2011, http://living-planit.com [16] “Bitcarrier, Wireless real-time traffic solutions”, Bitcarrier S.L., Retrieved 04-04-2011, http://www.bitcarrier.com [17] Caragliu, A., Del Bo, C., Nijkamp, P.: Smart cities in Europe. Series Research Memoranda 0048. VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics (2009) [18] “What's new in Smart Cities”, Bélissent Jennifer, Forrester Research, Retrieved 11-05-2011, http://www.amr.ru/upload/iblock/392/Smartcities.pdf 7. References [1] “People Statistics: Percentage living in urban areas by country”, Rapid Interlligence, Retrieved 22-032011,http://www.nationmaster.com/graph/peo_per_liv_ in_urb_are-people-percentage-living-urban-areas [2] Giffliger et al. 2007. Smart cities - Ranking of European medium-sized cities. Final Report [3] “Real World Internet - Position Paper”, European Future Internet Portal, Retrieved 22-03-2011, http://www.futureinternet.eu/fileadmin/documents/madrid_documents/ses sions/Real_World_Internet_Position_Paper_vFINAL.p df [4] “Real World Internet, Smart City and Linked Data”, Presser et al., 2010, Retrieved 22-03-2011, http://linkeddata.futureinternet.eu/images/b/bf/Presser_Linked_Data.pdf [5] “Smart Cities - Transforming the 21st century city via the creative use of technology”, ARUP Corp., 2010, Retrieved 22-03-2011, http://www.arup.com/~/media/Files/PDF/Publications/ Research_and_whitepapers/ARUP_Smart_City.ashx [6] “SmartSantander - a Smart City example“, Krco Srdan, Ericsson, 2010, Retrieved 23-03-2011, http://www.smartsantander.eu/downloads/Presentations /smartsantander1.pdf [7] “Sensors Make Cities Smarter”, Patton Zach, 2010, Retrieved 23-03-2011, http://www.majorcities.eu/pics/download/1_127839842 3/Governing___Sensors_make_cities_smarter.pdf [8] “Masdar City”, Retrieved 23-03-2011, http://www.masdarcity.ae [9] “Masdar PRT Application”, 2getthere B.V., Retrieved 23-03-2011, http://www.2getthere.eu/?page_id=10 [10] “Öko-Stadt Masdar City vorerst gestoppt “, Hahn Melanie, Daily Green, Retrieved 23-03-2011, http://www.dailygreen.de/2010/03/12/oko-stadtmasdar-city-vorerst-gestoppt-4032.html [11] “Masdar City Design” (Video), Retrieved 23-032011, http://en.com/Masdar_City_City_Design# [12] “Masdar City to test GE 'smart' appliances“, Lombardi Candace, cnet news, 2009, Retrieved 23-032011, http://news.cnet.com/8301-11128_3-1036727954.html [13] “Smart Santander – Future Internet Research & Experimentation”, Retrieved 23-03-2011, http://www.smartsantander.eu/ [14] “Projekt Smart City: 20.000 Sensoren überwachen spanische Stadt Santander”, Hemmerich Lisa, 2010, Retrieved 23-03-2011, http://www.netzwelt.de/news/83222-projekt-smart-city- 39 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) Hability An integrated smart meter framework for home and mobility use Daniel Mauch, D-MTEC mauchd@student.ethz.ch June 15th 2011 depleted in the near future, energy usage has not declined. In spite of the awareness of public consciousness and unaffected by technological progress in energy efficiency a change in this trend has not been noticed. Increasingly numbers of small devices add to the overall rising electricity consumption in private households and sum up to an overproprotional increase over the last decades. Electricity remains percepted as relatively cheap, abundant, and unaffected by consequences. 0 Abstract Transportation and electricity use in households are responsible for half of the energy use of our society. Despite the common knowledge on environmental implications of habits, little economic nor social incentives exist to change acquired behaviour patterns. Automated data collection, processing and exhibitation of decision relevant information can close this perceptional gap. Intelligent devices become ubiquitous through institutional functions of innovation systems: Smart meters are being deployed at home and high-performance phones – equipped with a variety of measuring elements – are gaining market share. Alignment of various sensors at home and abroad, data logging on a small server, information processing and instantaneous and attractive display can lead to learning effects leading to change of usage habits. In this paper I will try to give an introduction to drivers of behavioural decision making, a market overview of existing smart meter technologies and applications and develop an example for an integrated approach. Transportation occupies the largest share on primary power and thus conceals the highest challenge and also chance to contribute to sustainable energy usage. In the motorized transportation sector we can distinguish between private individual, private public and individual human powered mobility. Efficiency has become an increasing factor in motorized mobility, consumption figures a selling argument – even a legally prerequisited label. And cars are getting more efficient, unfortunately this progress is thwarted by additional weight of built-in convenience and comfort solutions. 1 Introduction Reduction in energy usage is one of the human society biggest challenge towards an equilibre and sustainable development. In 2008, total world energy consumption was 474 exajoules. This is equivalent to an average annual power usage rate of 15 terawatts (1.504·10 13 W) [1]. While the total energy consumption decreased in 2009 for the first time in 30 years (as a result of the economic crisis) [2], the share of the private household part is constantly increasing [3]. In Switzerland the total energy consumption in 2009 is about 900'000 terajoules, with mobility and households occupying the largest shares (35%, 29% respectively) [4]. Electric appliances are responsible for 60% of the electricity use in Switzerland [7]. The societal challenge of energy consumption reflected in institutions such as government, media, public cognition, technology and functions like information and incentives to energy efficiency has nevertheless not yet found translation into behavioural transitition. But why? 3 The behavioural gap Predominant explanations of drivers of decision patterns can be found in behavioural economics and environmental psychology. The approach of environmental economics extends economics with insights of the fields of psychology to give an integrated answer to phenomena and selective choice observed in reality contradicting classical market mechanisms. Thus not only price but also social, cognitive and regulative factors are used to explain the variety of different products, solutions and the respective choice. 2 Institutional Arrangement At the end of 2006 the EU pledged to cut its annual consumption of primary energy by 20% until 2020 [5] and subsequently has adopted this policy by passing a Directive (2006/32/EC) named “Energy end-use efficiency and energy services” demanding “individual metering and informative billing that shows [..] actual energy consumption”[6]. Theories in environmental psychology build upon two most commonly used models, the rational choice and norm-activation to support pro-environmental behaviour [36]. The first, rational choice models, explain decision making by maximizing marginal utility in terms of cost and benefit. Knowledge in Despite the fact, that consumption has increased and given the natural resources of non-renewable energy is 40 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) correlation of cause – effect tuples leads to concern about environmental issues which in turn is followed by energy-conserving behaviour. The latter, normactivation models, derive behaviour by collective or personal morale. Awareness of consequences of personal actions to the collective guides decision making towards pro-environmental behaviour, which in extreme even might supersede subjective, rational utility. The process of electricity consumption is in most cases a mute, silent event. If one could hear energy usage distinctively – as eg. when vacuum-cleaning the floor or hair drying – perception would be different and other usage patterns emerge. A feedback loop is clearly missing in this context. 3.2 Transportational energy usage awareness The energy consumption of the mobility sector with a share of one third of primary energy is by the means of automated usage information processing barely tapped. Automotive development has a longstanding tradition with highly spezialized fields, in fuel efficiency as well as in consumer electronics. Convergence of car computing and personal devices has nevertheless not been considerably and commonly supported. Based on these theories we can derive that decision making is primarily driven by insights, facts. We commonly are unable to derive implications of our actions, because energy consumption is usually a mute process. Informational feedback is the key behavioural driver next to personal know-how or to a collective normative. Elucidation in environmental terms has arrived in the institutional structures, but the gain to pro-environmental behaviour is marginal in the case of presenting the the information only. Not only the content, but even more the the context: specificy, timing and placement als well as the design are critical to the effectiveness of the message [23]. Governmental strategies to reduce energy efficiency, as eg. Energie2000 in Switzerland with its fuel saving programs [27] was a great success and raised public awareness, but remains unpursued in its extent and is thus not sustainable over the long term. 4 Personal Feedback systems On May 19th 2011 Toshiba has announced to buy Swiss Landys+Gyr, which has a longstanding tradition of meter fabrication and were recently chosen to supply the worlds largest Smart Grid in China with intelligent power meters [34]. With Google Power Meter [32] and Microsoft Hohm [33] two other major technology players have started their program of commercial smart sensor systems. 4.1 Measuring home electricity Within the last years a vast variety of home electricity displays have entered the market. On a technological basis we can separate single-sensored from multisensored or per-device systems. The former approach places the sensor on the main incoming feed (usually the fuse box or the meter itself). The latter solution uses smart power outlets or intelligent chips for each connected device. The communication to a central server can either be through the powerline itself, a dedicated separate wiring or wireless protocols (Bluetooth, WiFi, Zigbee). Figure 1. Examples of eco-feedback displays on smartphones (left: Google Power Meter [38], right: eMeter interface of Bits to Energy Lab project, ETH Zürich [37]) 3.1 Electricity consumption is unperceivable Through political regulations like eg. labelling of consumer appliances as well as significant increase in the efficiency of household appliances (refridgerator, oven, standby drawing) the electricity usage of households should be expected to decline, but instead rised over the last years, thus is increasingly dependent on consumer behaviour. Similar households can vary up to 2.6 times from the least to the most energy using in terms of energy consumption [29]. But even people willing to change their behaviour and save energy cannot get access to detailed usage information, it's simply not available or easily accessible. Commercial products with a single, central sensor have been made available eg. by Wattson [17], Wattcher [18] or Onzo [19]. A single, central sensor offers lower costs and easier integration into existing installations. Considerable research in this field has been conducted lately by M. Weiss [24,25,26]. Power consumers in this operating scheme are recognized using load patterns and operationalized through an user interface on an iPhone. As a personal example from my own experience: I do receive a bill from my electrical power provider in my mailbox regularly. But four times a year its only a quarterly “on account” bill with an extrapolated number, and once a year a settlement containing a number representing my consumption compared to the previous period. On this information base it is impossible to derive a decision driven learning. Another inititative aims towards a standardization of a per device powerline chip [28]. This multi-sensor setup allows for each device to identify itself autonomously to the server and bilateral communication. The drawbacks are on the cost side. First commercial 41 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) The approach of determining the usage of public or individual transports by tracking Global Positioning System (GPS) data and activity inference has been already conducted by applications like UbiGreen [13], or ecorio [14]. The possibility to infer from movement patterns to transportation means is appealing, as it doesn't require any user interaction – as long as it has learned individual characteristics of a persons preferences and possibilities. It is technically viable to refine accuracy by combining GPS with accelerometer and map data. Figure 2. Electric power home sensing system setup model with different configuration options (from left to right, top row to bottom): A local display, local database, central server with sensor, power consumers; mobile display, remote database, local server, distributed sensors and electricity consumers. Various combinations of hardwiring/wireless, single-sensor/central-sensor, local/remote database and displaying device are possible. 5 Hability We have seen that several solutions for measuring, storing and displaying electric home power usage exist. It is now up to the market to emerge a standard. The institutions have been set up and smart meters are started being deployed widely. In the following I want to present a convergency approach for a device which covers feedback for home electricity use and energy use on transportation. available components and solutions were available by the end of last month [30, 31]. This solution directs more towards home automation. 4.2 Measuring transportation energy consumption Several approaches exist to collect transportation data and energy consumption. I will briefly introduce some examples and applications. Modern vehicles nowadays measure the fuel use on a short and long term basis accurately and might even communicate the consumption via the on-board display. Ususally this information is displayed instantaneous on the basis of current and average usage. Interfaces for further processing exist through the on-board diagnostics bus (OBD-II) [8] and its interface, which is mandatory for every new car sold since 1996. There are applications on the market, which simply write all available data to a memory chip [9], or transmit wireless to a smartphone [10,11,12,21]. But all these solutions need a connector hardware, plugged to the OBD-II outlet, which at least is usually conviently located in the passengers cabinet, but it is an additional investment and a barrier to usage. Figure 3. Definition of “hability” according to Merriam-Webster [35]. Our setup exists of a home appliance, preferably a single sensor central server solution, and a smart phone. Electricity usage is continously measured, stored and displayed on demand on the handset. This scheme has been already developed and can be deployed immediately. But what about mobility? Detailled information about private transportation would technically available, it's just a question of motivation, convenience and cost to set up car-data tracking and a respective feedback system. With the approach of GPS-tracking of the movement the transportation mean can be determined by pattern recognition, and tracked on maps with high resolution in an automated way. In the case of private motorized transportation theres just one little crucial piece of information missing: the amount of fuel consumption. Common solution are based on assumptions or generic car types and thus provide only estimated numbers. As the process of refilling the gas tank is a discrete task and has to be proceeded manually, we have a discontinuum in the process. Now if we have this interruption, how can we provide the information to flow? Of course all gas stations or meters could be equipped with wireless emitters or NFC chips, transmitting the amount and the cost of the purchase to the customers smart device, but besides economic and security drawbacks of setting up this kind of infrastructure, there would still be the need of manual An alternative to measure the fuel consumption would be the use of the internal accelerometer on a mobile device [15]. With this solution it is still necessary to adapt the application to the individual efficiency of the transport means – be it private or public – and calibrate the readings. For manual recording of fuel data there are already several applications [20,22]. Because they rely on accurate off-line transcription of mileage and energy consumption and are solely manual feed, they aren't further discussed within this context. The energy usage of people using public transport can only be estimated. Even though trains, trams and some busses are electrical driven, no information on a per user or per ride level is publicly available. 42 Business Aspects of the Internet of Things, Seminar of Advanced Topics, ETH Zurich, FS2011, Florian Michahelles (ed.) interaction for the selection of the right meter – device pair. 6 Conclusions Smart electricity meters are or being installed in households in large numbers in the US by now and in the EU in the coming years because of governmental requirements aiming to reduce power usage by providing detailled information. With the technology of Optical character recognition (OCR), which is able to extract processable data from images, we have the possibility to offer a more convenient way and lower the entry barrier of the manual interaction at the gas station: just take a picture of the meter at the station after the refill: Information on energy use of individual mobility can be revealed through the use of integrated sensors be it in cars or indirectly via hand held devices. To refine accuracy of motorized mobility energy usage, a semiautomated fuel usage data capturing application is developped. This lowers the barrier of collaboration, eases information flow and allows real efficiency to be computed. Our personal computerized daily companion – the smart phone – is the perfect platform for a interactive feedback system. Combined with added services for personal fun and challenge we create an ecological worthwile application. Figure 4. Gas meter showing figures for cost, amount and prices after a refill. These numbers, once electronically interpreted, are fed into automated processing application. It remains to further investigate whether an in situ processing of imagery by an OCR algorithm is technically feasible [40, 41]. Another problem could reside in the security aspect of the application, as it logs sensitive information about ones daily life and thus needs special protection. The application translates the amount and cost into machine-readable numbers, which then can be further processed automatically by the smart device. By the combination of actual consumption of fuel and movement data we have a very detailled description of power usage for private mobility. Accelerometer date can be used to further refine the accuracy of measurement. By combining home and mobility energy usage: data gathering and storing, an appealing and intelligently designed interfaces to provide instantaneous feedback, we are able to interfere common habits and shape decisions towards a more rational and normative choice in favour of the environment. An alternative option to OCR could be a QR-code on the bill you receive when refueling. On the positive side we would have a physical reminder, but for this solution we need a third party to cooperate, plus we wouldn't be able to cover customers which have monthly bills. 7 1. For the remaining transportation means – public transport, biking and walking – they would be covered by GPS and estimated energy usage, as they cannot be measured accurately. 2. 3. 4. The user-interface would be able to show electricity and mobility, a simple power gauge at default but detailled on an per device level on demand.It would be geared towards an intuitive yet powerful surface, which hides all device based details unless wanted. 5. 6. 7. 8. 9. 10. With this setup we cover the two major energy consuming sectors and lower the barrier of data gathering significantly. Further incentives for continued data collection might be given by add-on services which use the collected data and compare it with other users to compete for fun [39, 42]. 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