The Internet of Things, or the IoT is a vision for a ubiquitous society wherein people and “Things” are connected in an immersively networked computing environment, with the connected “Things” providing utility to people/enterprises and their digital shadows, through intelligent social and commercial services. However, translating this idea to a conceivable reality is a work in progress for close to two decades; mostly, due to assumptions favoured more towards a “Things”-centric rather than a “Human”-centric approach coupled with the evolution/deployment ecosystem of IoT technologies. Estimates on the spread and economic impact of IoT over the next few years are in the neighborhood of 50 billion or more connected “Things” with a market exceeding $350 billion through smarter cities and infrastructure, intelligent appliances, and healthier lifestyles. While many of these potential benefits from IoT are real and achievable, the road to accomplish these may need an rethink. In the last few years, there has been a realization that an effective architecture for IoT (particularly, for emerging nations with limited technology penetration at the national scale) that is both affordable and sustainable should be based on tangible technology advances in the present, ubiquitous capabilities of the present/future, and practical application scenarios of social and entrepreneurial value. Hence, there is a revitalized interest to rethink the above assumptions, and this exercise has led to a more plausible set of scenarios wherein humans along with data, communication and devices play key roles. In this presentation, an attempt is made to disaggregate these core problems; and offer a trajectory with a set of design paradigms for a renewed IoT ecosystem.

1. Balancing the NEEDS vs. the WANTS
in the Internet of Things
Dr. Prasant Misra
W: https://sites.google.com/site/prasantmisra
Disclaimer:
The opinions expressed in this presentation and on the following slides are solely those
of the presenter and not necessarily those of the organization that he works for.

2. IoT 101
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3. History of Computing
1960 - 70
1980 - 90
2000 -10 and
beyond
Year
Size
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4. Trend-I: Data/Device Proliferation (by Moore’s Law)
Wireless Sensor Networks (WSN) Medical Devices
Industrial Systems Portable Smart DevicesRFID
http://www.onethatmatters.com/wp-content/uploads/2015/12/Internet-of-Things-why.png
Fixed/Mobile
Leaf/Edge
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5. Trend-I: Data/Device Proliferation (by Moore’s Law)
“Information technology (IT) is on the verge of another
revolution. Driven by the increasing capabilities and
ever declining costs of computing and communications
devices, IT is being embedded into a growing range of
physical devices linked together through networks and
will become ever more pervasive as the component
technologies become smaller, faster, and cheaper. “
“These changes are sometimes obvious—in pagers and
Internet-enabled cell phones, for example—but often IT
is buried inside larger (or smaller) systems in ways that
are not easily visible to end users. These networked
systems of embedded computers, …, have the potential
to change radically the way people interact with their
environment by linking together a range of devices
and sensors that will allow information to be
collected, shared, and processed in unprecedented
ways. The range of applications continues to expand
with continued research and development.”
Committee on Networked Systems
Council of Embedded Computers,
National Research Council
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6. Trend-II: Integration at Scale (Isolation has cost !!!)
(World Wide) Sensor Web
(Feng Zhao)
Future Combat Systems
Ubiquitous embedded devices
• Large scale network embedded systems
• Seamless integration with the physical environment
Complex system with global integration
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7. Trend-III: Evolution: Man vs. Machine
The exponential proliferation of embedded devices (afforded by Moore’s Law) is not
matched by a corresponding increase in human ability to consume information !
Increase autonomy (i.e., decrease the dependence on humans)
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8. Confluence of Trends
Distributed,
Information
Distillation and
Control Systems of
Embedded Devices
Trend-1:
Data & Device
Proliferation
Trend-3:
Autonomy
Trend-2:
Integration at
Scale
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9. Confluence of Technologies
CPS
Trend-1:
Sensing &
Actuation
Trend-3:
Computation,
Control
Trend-2:
Communication
A cyber-physical system (CPS) refers to a tightly integrated system
that is engineered with a collection of technologies, and is designed
to drive an application in a principled manner.
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10. Looks very familiar ….
What is new in the functional definition/characterization of CPS ?
Enormous SCALE : both in space and time
Functional Blocks of CPS

11. Functional Blocks of CPS
Enormous SCALE : both in space and time
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12. Casting CPS Technology into Application Requirement
Use Case: Adaptive Lighting in Road Tunnels
Problem: Control the tunnel lighting levels in a manner that ensures continuity of light conditions
from the outside to the inside (or vice-versa) such that drivers do not perceive the tunnel as too
bright or dark.
Solution: Design a system that is able to account for the change in light intensity (i.e., detect physical
conditions and interpret), and adjust the illumination levels of the tunnel lamps (i.e., respond) till a
point along the length of the tunnel where this change is indiscernible to the drivers (i.e., reason and
control in an optimal manner).

13. CPS and IoT : Are they the SAME ?
C1 C2 Cn
P1 P2 Pn
CPS
Internet
CyberworldPhysicalworld
NoT
IoT = CPS + People ‘in-the-loop’ (that act as sensors, actuators, controllers)
IoT = CPS + Hybrid (tight and loose) sense of control8/26/2016 13

14. IoT : Past Mistakes, Future Opportunities
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15. IoT: Vision and Value Proposition
Vision:
Build a ubiquitous society where everyone (“people”) and everything (“systems,
machines, equipment and devices") is immersively connected.
Value Proposition:
 Connected “Things” will provide utility to “People”
 Digital shadow of “People” will provide value to the “Enterprise”
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16. IoT : As of TODAY …
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17. Industrial
EnvironmentLocation
Smart Cities
SCADA @ “SCALE”
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18. Connected Universe
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Many Underpinning !!!

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War of Standards

20. Category Assumption
System Scale Hundreds of devices (tightly coupled)
Device Cost $5-500
Connectivity Always available
Data Collection Centralized (Cloud based)
Data Analysis Centralized (Cloud based)
Data Search Centralized (Cloud based)
Control Centralized (Cloud based)
Ecosystem Closed ( a single vendor owns the platform, Cloud services,
data and other pieces of the ecosystem)
Data Sharing Closed / Mechanisms are highly cumbersome
Data Ownership Operator / Vendor-centric
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Many Assumptions

21. IoT : INTROSPECTION …
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22. Reality
Thousands of devices in immediate
vicinity, and millions more further out
$0.01-3
Intermittent (never a guarantee)
Centralized + Distributed
Centralized + Distributed
Centralized + Distributed
Centralized + Distributed
Open (without vendor lock-in)
Open (seamless flow between apps)
User-centric
Category Assumption
System Scale Hundreds of devices
Device Cost $5-500
Connectivity Always available
Data Collection Centralized
Data Analysis Centralized
Data Search Centralized
Control Centralized
Ecosystem Closed
Data Sharing Closed
Data Ownership Operator-centric
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A Reality Check

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Human and Device Proxemics
Smartphones:
 A well qualified (featureful and low cost)
Edge / IoT Gateway device
 Inevitably carried by people
 People take care of charging … reduced
energy worries

24. IoT : Design Paradigms
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25. Application
Sensors & Actuators
Analytics & Logic
Networking
We need Rs 50-100
sensors & “lots" of
them
We don’t have good
coverage.
Everybody has their
own standard.
Is this really from my
sensor ?
What does 25.6 mean ?
Why is everything only
partially correlated ?
Data mules
Sensor/Network as a Service
Big-Little Data
Complex Event Processing
Model Driven Analytics
Plug-and-Play - USB for IoT
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IoT Design Paradigms : A Possibility

26.  Human-centric rather than Thing-centric
 People are the Sensor/Network
 Manage an immersive system with more emphasis on locality rather than centrality
 Humans become part of the ecosystem (will acts a data sources/respond to control)
 Human-Things interaction spans Virtual and Physical worlds
 “Big-Little” Data
 Device Cloud vs. Conventional Cloud
 Distributed data and Peer-to-Peer Federation
 Provide information security and ownership
 Identify, locate, authenticate, control access, and audit the data source
 Analytics from the Edge to the Cloud
 Leverage local processing capabilities (in addition to Cloud infra) to minimize
latency, bandwidth, energy
 Bring the Network to the Sensor
 Simplify networking
 Piggyback on existing and widely adopted standards and techniques
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IoPT Design Paradigms

27.  How “Low” can we go ?
 Reusable devices and sensors used in novel ways vs.
Custom solutions with cutting edge capabilities
 Whose “Data” is it anyways ?
 Transparency in data ownership, sharing and usage
 Data brokering for clear returns on data investment
 When “good enough” is enough ?
 Cheap sensors -> Questionable data;
Humans -> Difficult to model;
Physical systems -> Complex;
Data privacy -> Limit data availability
 Decision making has to be probabilistic
 Systems should not fail in absence of perfect behavior
 Context determines Action
 Context binds People and Things to a common scope, given their uncertainties
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IoPT Design Paradigms

28. Huge hidden costs of execution:
 Cultural awareness and user centric design
 Communications and infrastructure
 Economics and Execution
 Building for the real world
 Hostile environments, Limited power, Failed networks, “Big-Little” data
 Managing channel, deployment and support at scale
 OTA, Replacement, Service, etc.,
 Security
 No physical boundary or firewall
 Non intuitive attack surfaces – re-think the model
 Metrics & monetization
 Opportunity for nano-payment to facilitate shared information eco-systems
 Key issue: Who owns the data ?
This technology gives you the ability to look more broadly, deeply and over
extended periods of time at the physical world and our interactions with it than
ever before.
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IoPT: Challenges for Translation

29. One Simple Example …
LBS: From Commercial Flop to Pervasive “on-the-go” Service
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30. Commercial Flop -> Pervasive “On-the-Go” Service
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The Evolution of LBS (E911-Recent Past)

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The “Big Bang” of LBS

32. Event How did it help ?
LBS: Reactive -> Proactive Requires less user attention
LBS: Self -> Cross-referencing User has better access control for privacy
protection
LBS: Single -> Multi Target Development of community spirit
LBS: Content -> Application
Oriented
Richer “man-machine” interaction
LBS: Operator ->User centric  Individual “Data” ownership and management
 Decentralized positioning
 More peer-peer interaction
 Reduced privacy concerns
Giving more control to the “user” was pivotal to the success of LBS !!!
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The “Big Bang” of LBS: Lessons Learnt

33. Is the Internet of Things disruptive?
OR
Are they repackaging known technologies
and making them a little better?
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What is your take ?

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References
 P. Misra, Y. Simmhan, J. Warrior, “Towards a practical architecture for the next
generation Internet of Things” [http://arxiv.org/abs/1502.00797]
 P. Misra, Y. Simmhan, J. Warrior, “Towards a practical architecture for Internet of
Things: An India-centric View”, IEEE IoT Newsletter, Jan 2015
• P. Misra, L. Mottola, S. Raza, S. Duquennoy, N. Tsiftes, J. Hoglund, and T. Voigt,
“Supporting Cyber-Physical Systems with Wireless Sensor Networks: An Outlook
of Software and Services”, Special Issue on Cyber Physical Systems, Journal of the
Indian Institute of Science, 93(3):441-462, Sep. 2013
• P. Bellavista, A. Küpper and S. Helal, "Location-Based Services: Back to the Future"
in IEEE Pervasive Computing, vol. 7, no. 2, pp. 85-89, April-June 2008.
 Other info graphics from the web !!!