dimension

Co-chairs:
Steve Jordan,Yorgos Marinakis and Steve Walsh
Additional Contributing Authors:
Inder Thukral, Robert Haak, Alec Dara Abrams and Flavio Bonomi
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T Sensors suggest a logarithmic growth in sensor applications and volumes.
This makes the current Internet infrastructure obsolete.
  Therefore, the TSensor Systems infrastructure is one of the major
hurdles to the Abundance that TSensor development promises.
We are capturing the inputs from a variety of sources including white
papers, popular journals, emerging academic journals and interview with
futurists in the field.
Then we are placing that information into the framework of a thirdgeneration-type technology roadmap.
The TSensors System Roadmap is a plan for accelerating progress, based
upon technological, market, business value systems, regulatory and political
drivers that are relevant to developing new IOT (E) infrastructure
subsystems, systems and designs.
This work is the product of the TSensor Systems Working Group, an adhoc group of Mancef members meeting at annual COMS conferences.
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We define TSensor Systems as the infrastructure required to support
the manufacture and operation of TSensors. Thus the TSensor Systems
Roadmap is currently divided into several chapters, corresponding
to multiple root technologies:
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3D printing infrastructure for low cost sensor manufacture
Energy harvesting as a source of power for the TSenor revolution
New technologies for energy storage
Ultralow power wireless communication technologies
New network protocols and standards/Operating Systems
Analytics
We also present critical dimensions and boundary conditions.
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addition to discussing technologies, we
would also like to evaluate technologies
using:
◦  Technological Readiness Levels
◦  Task-Technology Fit
  Problem: we
cannot properly evaluate
the adequacy of the current technology,
because we do not yet know enough
about the future!
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Technology readiness levels (TRLs)
are measures used to assess the maturity
of evolving technologies (devices,
materials, components, software, work
processes, etc.) during their development
and in some cases during early operations.
Generally speaking, when a new
technology is first invented or
conceptualized, it is not suitable for
immediate application. Instead, new
technologies are usually subjected to
experimentation, refinement, and
increasingly realistic testing. Once the
technology is sufficiently proven, it can be
incorporated into a system/subsystem.
http://en.wikipedia.org/wiki/
Technology_readiness_level
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“The task-technology fit (TTF) model is a widely used theoretical
model for evaluating how information technology leads to
performance and usage impacts. For an information system to
positively affect technology utilization, the technology must fit
the task it supports to have a performance impact.”
Computers in Human Behavior 34 (2014) 323–332
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3D printing technology is considered one of the exponential
technologies (in book Abundance).
3D printing technology promises disruption in deployment of sensors
and electronics, wherein sensor arrays and signal processing
electronics could be printed on flexible substrates, enabling unit prices
of the entire systems (e.g., printed on food packaging sensing freshness
and quantity of food and communicating with external readers) to
drop below $0.01, thus enabling disposability and trillion unit level
deployment.
3D printed electronics needs increased awareness in the sensor
community to accelerate its deployment. This Chapter’s objective is to
fill this gap with an overview what is becoming available, and to use
that information in the TSensor Systems Roadmap.
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  3D
printing of nanoscale objects by
depositing electrospun polymer
nanofibers. TRL 1.
  “Embedded 3D printing” of a carbonbased resistive ink within an elastomeric
matrix, for creating soft functional devices
for wearable electronics, human/machine
interfaces, soft robotics, etc. TRL 4.
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Microcapillary (Microfluidic) Interface Fabrication
using 3D printing; 3D printing allows for direct
generation of complex, three-dimensional
structures that are otherwise only achievable
using multiple processing steps and at significantly
higher costs. TRL 4.
  Direct printing of PDMS (polydimethylsiloxane)
on glass lab-on-a-chip (LOC) devices
implemented by micro stereo lithography. TRL 4.
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Massive deployment of sensing systems will not be
possible without the “power for life”: energy sources
generating energy from the environment such as light,
movement, heat and RF.
Sensor application often restrict the size, weight and of
course cost of energy harvesters.
Currently there is a gap between what current
technologies can deliver and what is needed by wireless
systems.
This chapter focus is on increasing awareness of
advancements in energy harvesting, with the objective of
accelerating their commercial deployment.
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Flexible electronic devices and storage using
nanowires. TRL 4.
  Fiber-like supercapacitors, assembled from
graphene/carbon nanotube fibers, having both
high power density and high energy density.
These energy storage devices can be woven
into clothing and thus can power devices for
the wearable market. TRL 4.
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As discussed under Energy Harvesting, there is a
gap between what current technologies can deliver
and what is needed by wireless systems.
  Improvement of Energy Harvesting technologies is
one approach to bridge the gap, but the other one
is lowering the power of wireless communication.
  The objective of this Chapter is to increase
awareness in sensor community on advancements in
wireless communication, with the objective of
accelerating their commercial deployment.
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  Flexible
passive organic and MEMS RFID
tags (Zhan et al. 2014).
  Gogotsi (2014) reports that professor
Jayan Thomas and his student Zenan Yu
have developed a way to both transmit and
store electricity in a single copper wire
using nanowhiskers. TRL 4.
  Ho et al. (2014) report technology to
wirelessly charge devices implanted inside
the body. TRL 4.
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Network connectivity is the area which receives the largest funding ($
billions) from multiple organizations and Governments.
The disruptive advances in Internet Network architecture has been
either deployed or is under deployment by major network providers:
◦  Addition of the Fog network layer under Cloud.
◦  Addition of Swarm network layer under Fog for edge devices.
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These changes create dramatic simplification for network connectivity of
sensors.
◦  For example, deployment of parking sensors by Streetline
http://www.streetline.com/ was estimated (by Cisco speaker at 2013 TSensors
Summit at Stanford University) to cost less by $10s million and reached market
several years earlier, if it would happened today.
The objective of this Chapter is to increase awareness in sensor
community on network infrastructure advancements, with the objective
of accelerating their commercial deployment in sensor based systems.
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Micro-electrical-mechanical systems technology
(MEMS) have enabled the creation of wireless
sensor networks (Gubbi et al. 2013).
  Linear Technology’s Dust Networks has more
than 30,000 networks installed in 120 countries
(SmartMesh WirelessHart and SmartMesh IP;
http://www.linear.com). TRL 9.
  TerraSwarm wireless sensor dust nodes. TRL 2.
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Sensor generated data are forecasted to reach 1 BB (bronto Byte) in less than 10
years.
Extracting useful information from such “information overload” becomes essential
for all applications, ranging from medical to pollution control and personal life
management.
Advanced data processing technologies and algorithms reach maturity, e.g., machine
and deep learning (AI), promising revolutionary changes in our day to day lives.
◦  Google estimated (personal communication with Janusz Bryzek), that automatic
on-spot interpretation of medical images (e.g., ultrasound) could be developed in
6 months using machine learning, if large enough data would be fed to
computers.
The objective of this Chapter is to increase awareness in sensor community on
Analytics and Big Data advancements, with the objective of accelerating their
commercial deployment in sensor based systems.
It has been suggested that analytics on streaming data is key to the IoT (McNeill
2014). In addition to stream processing, other technologies include Hadoop
systems, NoSQL databases, in-memory data grids and real-time data integration
tools (Stedman 2014).
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Linear Technology’s Dust Networks’ WirelessHART (IEC 62591)
standard (http://en.hartcomm.org/hcp/tech/wihart/
wireless_overview.html).
Open Interconnect Consortium (http://www.openinterconnect.org).
Thread Group (http://www.threadgroup.org) - Thread is an IPv6
networking protocol built on open standards and designed for lowpower 802.15.4 mesh networks, such that existing popular application
protocols and IoT platforms can run over Thread networks. The nonprofit Thread Group seeks to makeThread the foundation for the
Internet of Things in the home. TRL 4.
AllJoyn protocol (https://www.alljoyn.org).
IEEE's 802.11ah standard (http://www.ieee802.org/11/Reports/
tgah_update.htm).
IETF 6TSCH working group is working to fuse Time Slotted Channel
Hopping (TSCH) technology with IETF 6LoWPAN standards (https://
www.ietf.org/mailman/listinfo/6tsch).
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Swarm-OS (http://www.terraswarm.org/
swarmos, https://swarmlab.eecs.berkeley.edu/
projects/4524/swarm-os).
  Contiki (http://www.contiki-os.org). Contiki
connects tiny low-cost, low-power
microcontrollers to the Internet. It supports
IPv6 and IPv4, as well as the recent low-power
wireless standards 6lowpan, RPL, CoAP TRL 9.
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Trends in data privacy laws can be determined
by analyzing proposed laws and new laws:
◦  EU draft General Data Protection Regulation (De
Hert and Pappakonstantinou 2012, Castro-Edwards
2013,Victor 2013)
◦  Proposed changes to United States
communications law (e.g., Kerr 2013)
◦  Singapore Personal Data Protection Act (Chik
2013).
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Security is rapidly becoming the hot issue for sensor
based systems, with frequent news on security
breaches.
There is a need for embedding security at the sensor
layer, in addition to the node security.
The objective of this Chapter is to increase awareness
in sensor community on Data Security advancements,
with the objective of accelerating their commercial
deployment in sensor based systems.
Data and network security – See Hamlen et al. 2010.
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Amount of data that can be streamed in a
wireless network (wireless standards, gateways;
Nilsson 2014).
  Amount of data that can be streamed in a
wired network (IP protocols).
  Sensor manufacturing costs.
  Sensor capabilities for data transmission,
storage and processing.
  Sensor energy storage capacity.
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There are six ways in which the nature of many new innovations and products differ from earlier
products and innovations:
1. 
These innovations are created at the interface of multiple root technologies.
2. 
These innovations often do not have a unit cell such as the transistor does for the semiconductor
roadmaps.
3. 
Differing applications drive innovations that will require differing and often multiple critical
dimension development for each technology being utilized.
4. 
The boundary conditions constraining today's innovations and products are much stricter than ever
before .
5. 
Drivers are much more important to these new innovations.
6. 
New business models such as focused consortia are driving technological development without
benefit of predetermined architecturally stable product process platforms.
Tierney, R. and Hermina, W. and Walsh, S.T., (2013),The pharmaceutical technology landscape: a new form
of technology roadmapping.Technological forecasting and social change, 80 (2), 194 - 211.
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For those who are interested, in your
own time you can watch our animated
video “Introduction to Roadmapping.”
http://bit.ly/1yWl5Kh
Also of note: Walsh, S.T., (2004), Roadmapping a disruptive technology: a case study: the emerging
microsystems and top down nanosystems industry. Technol. Forecast. Soc. 71 (1–2), 161–185.
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Tierney, R. and
Hermina, W. and
Walsh, S.T.,
(2015), The
pharmaceutical
technology
landscape
MANCEF
roadmap
www.mancef.org
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Drivers from Mancef
roadmap effort, TSensors
and TSensor systems efforts.
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TSensor
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Architecture
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TSensors – The TSensors themselves.
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5 major world challenges of the 21st century world identified by the World Health Organization:
sustainable energy,
affordable healthcare,
food to meet the needs of the world population,
the environment most specifically global warming, and
potable water.
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Internet of Things (IoT) –The IoT comprises IP-enabled (Internet protocol) devices, RFID tags,
wireless sensor networks, machine-to-machine (M2M) communications, mobile devices and apps,
white space TV spectrum and cloud computing. It connects these devices and entities through new
network architectures to enable low latency control.
Variants:
Internet of Everything (IoE) - http://www.cisco.com/web/about/ac79/innov/IoE.html
Swarm at the Edge of the Cloud: https://swarmlab.eecs.berkeley.edu
Mobile Market – This market is transitioning to an unPad infrastructure in which the (key)Pad/
mobile device goes away but its functionality remains. It will be implemented by opportunistically
interconnecting sensors and actuators (https://swarmlab.eecs.berkeley.edu).
Wearable Market - The four end-user segments of the wearable technology products comprise:
fitness and wellness, Infotainment, healthcare and medical, and industrial and military.
Digital Health - Improving health diagnostics and therapeutics while reducing cost.
Context Computing - Deriving information about us (such as feelings) and around us.
CeNSE (Central Nervous System for the Earth) - Building global environment monitoring (http://
www8.hp.com/us/en/hp-information/environment/cense.html).
5-in-5 - Five senses for computers in five years (http://www.ibm.com/smarterplanet/us/en/
ibm_predictions_for_future/ideas).
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-Open Interconnect Consortium (http://
www.openinterconnect.org)
-Thread Group (http://www.threadgroup.org)
-Allseen Alliance (https://allseenalliance.org)
-Industrial Internet Consortium (http://www.iiconsortium.org)
– The industrial internet combines physical machinery,
networked sensors and software.
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-3D printing for manufacturing sensors and sensor
components. TRL 4.
-Energy harvesting/storage for operating sensors.
TRL 4.
-Ultralow power wireless communication for sensor
communication (MEMS).
-Network protocols and standards.
-Operating Systems
-Analytics
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-Amount of data that can be streamed in a
wireless network (wireless standards, gateways).
-Amount of data that can be streamed in a wired
network (IP protocols).
-Sensor capabilities for data transmission, storage
and processing, e.g., M2M protocols.
-Sensor energy storage capacity.
-Sensor manufacturing costs.
-Availability of skilled engineers.
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-Privacy laws.
-Data and network
security.
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Note:
this
roadmap
is a
work-inprogress.
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- Construction of the TSensor Systems Roadmap is an
ongoing project.
- We welcome your input. Please send your updates and
feedback to Steve Walsh <swalsh91@comcast.net> or
Yorgos Marinakis <ymarinak@unm.edu>.
- You are also invited to contribute a white paper to the
TSensor Systems Roadmap.
- TSensor Systems Working Group is hosting an
academic, peer-reviewed journal Special Issue through
COMS 2014.
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