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Co-chairs: Steve Jordan,Yorgos Marinakis and Steve Walsh Additional Contributing Authors: Inder Thukral, Robert Haak, Alec Dara Abrams and Flavio Bonomi 1

Co-chairs: Steve Jordan, Yorgos Marinakis and Steve Walsh … · Co-chairs: Steve Jordan, Yorgos Marinakis and Steve Walsh Additional Contributing Authors: Inder Thukral, Robert Haak,

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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 third-generation-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 ad-hoc 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: ◦  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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  In 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

  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 carbon-based 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.

  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). 18

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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 low-power 802.15.4 mesh networks, such that existing popular application protocols and IoT platforms can run over Thread networks. The non-profit 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). 19

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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. 27

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 Systems Architecture

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TSensors – The TSensors themselves.

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-in-progress.

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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 <[email protected]> or Yorgos Marinakis <[email protected]>. - 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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