Overview and applications
Vinod Kulathumani
West Virginia University
Outline
• Vision for sensor actuator networks

Networked embedded systems

Enabling technology

Application areas
• Sensing-only systems

Monitoring related applications

Application examples

Challenges and design space
• Sensing + actuation

Examples

Challenges and design space
• ExScal, an example surveillance application
2
Embedded systems
• Found in variety of devices

Aircraft, radar systems, nuclear and chemical plants

Vehicles, TVs, camcorders, elevators

> 90% of CPUs used for embedded devices
3
Networked embedded systems
Currently
• Embedded processors - part of a larger system
• Application known apriori

Little flexibility in programming
What if?
• embedded processors were connected – preferably wireless?
• there was greater flexibility in programming ?
• sensing and actuation capabilities were included ?
4
The Vision for WSANs
• Combine wireless networks with sensing / actuation
 Ubiquitous computing / pervasive computing
• Fine-grained monitoring and control of environment
• Network and interact with billions of embedded computers
Reasons
• Wireless communication - no need for infrastructure setup
• Drop and play
• Nodes are built using off-the-shelf cheap components
• Feasible to deploy nodes densely
5
log (people per computer)
New Class of Computing
Number Crunching
Data Storage
Mainframe
Minicomputer
productivity
interactive
Workstation
PC
Laptop
PDA
streaming
information
to/from physical
world
year
Slide courtesy: Murat Demirbas
6
Opinions
Tiny computers that constantly monitor ecosystems, buildings,
and even human bodies could turn science on its head.
- Nature, March 2006
The use of sensornets throughout society could well dwarf
previous milestones in information revolution.
- National Research Council report, 2001
Reinventing computer science
- David Tennenhouse, Intel, 2000
7
Enabling technology
• Powerful microprocessors

Small form factor

Low energy consumption
• Micro-sensors (MEMS, Materials, Circuits)

acceleration, vibration, gyroscope, tilt, motion

magnetic, heat, pressure, temp, light, moisture, humidity, barometric

chemical (CO, CO2, radon), biological, micro-radar

actuators (mirrors, motors, smart surfaces, micro-robots)
• Communication

short range, low bit-rate, CMOS radios
8
A typical sensor node
• Telosb (2007)

8 MHz MSP430 processor

10kB RAM

250 Kbps data rate

Integrated temperature, humidity, light sensors
• Others
9
Application areas for WSANs
• Science

Environmental and habitat monitoring

Oceanography, seismology, water management, …
• Engineering

Precision agriculture

Industrial automation

Control systems, …
• Daily life

Detecting emergencies and alerting, disaster recovery

Health care

Traffic management and many more
10
Sensing only systems
• Popular as wireless sensor networks
• Useful for monitoring based applications
• Large scale networks of embedded sensors

Connected to a remote base station

Self-configuring

Typically resource constrained (Why?)
11
Block diagram of a sensor node
Application
Processor
Sensor
(Light)
Actuator
(Buzzer)
Network
Interface
SENSING
SUB-SYSTEM
PROCESSING
SUB-SYSTEM
COMMUNICATION
SUB-SYSTEM
ACTUATION
SUB-SYSTEM
POWER MGMT.
SUB-SYSTEM
SECURITY
SUB-SYSTEM
Substitute any sensing / actuating modality
12
Application category – Monitoring type
Environmental monitoring
Infrastructure monitoring
Object tracking
Body sensor networks
Perimeter security
Camera sensor networks
13
Emerging applications
• Combination of sensors with mobile devices

Social networking

Participatory urban sensing
• Assisted living – health monitoring
• Vehicular networks with variety of sensors
14
Specific examples
• Detect and track intruders in a secure area
• Detect chemical or biological attacks
• Detect building fires and set up evacuation routes
• Monitoring dangerous plants
• Monitoring social behavior of animals in farms and natural habitats
• Monitoring salinity of water
• Monitoring cracks in bridges
• Tracking dangerous goods
• Shooter Localization
• Epilepsy monitoring and suppression
• Camera networks for urban surveillance
• Monitoring traffic on a highway
15
Challenges in sensor networks
• Energy constraint
: Nodes are battery powered
• Unreliable communication
• Unreliable sensors
: Radio broadcast, limited
bandwidth, bursty traffic
: False positives
• Ad hoc deployment
: Pre-configuration inapplicable
• Large scale networks
: Algorithms should scale well
• Distributed execution
: Difficult to debug & get it right
• Ease of use
: All Scientists not programmers
16
Sensing + actuation systems
• Not simply monitoring events, objects

Combined with actuation
• Traditional control applications

Decouple information availability

Control assumes information is instantaneously available
• What if information is transmitted over a sensor network?

Losses, delays in information
• New tools needed for programming, reasoning about such
systems
• Building blocks for Cyber-physical systems - recent
buzzword!
17
Sensing + actuation systems
• Not simply monitoring events, objects

Combined with actuation
• Traditional control applications Note

Decouple information availability

Losses, delays in information
Applying control theory for network
 Control assumes information is instantaneously
available
systems – has
existed before
(example:
congestion)
• What if information is transmitted
over aTCP
sensor
network?
This is control systems designed on
top of networks
• New tools needed for programming, reasoning about such
systems
• Building blocks for Cyber-physical systems - recent
buzzword!
18
Example sensor actuator networks
• Robotic systems

Self-configuring structures

Robotic surgery
Self-configuring table
http://www.youtube.com/ssrlab0/#p/u/24/5uR34U1qc-Q
• Autonomic vehicular platoons

Use in UAV swarms

Autonomous driving – Google Car!
• Distributed vibration control
• Distributed illumination control, irrigation, process control
• Smart power grid
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We saw all these challenges for sensor networks
• Energy constraint
: Nodes are battery powered
• Unreliable communication : Wireless, limited bandwidth, bursty traffic
• Unreliable sensors
: False positives, negatives
• Ad hoc deployment
: Pre-configuration inapplicable
• Large scale networks
: Algorithms should scale well
• Distributed execution
: Difficult to debug & get it right
• Ease of use
: All Scientists not programmers
20
Add to these ....
• Energy constraint
: Nodes are battery powered
• Unreliable communication
: Wireless, limited bandwidth, bursty
traffic
• Unreliable sensors
…. A control application that sits on top
: False positives, negatives
Requires
information guarantees from network below!
• Ad hoc
deployment
: Pre-configuration inapplicable
• Large scale networks
: Algorithms should scale well
• Distributed execution
: Difficult to debug & get it right
• Ease of use
: All Scientists not programmers
21
Relation to CPS
“Cyber-physical systems are physical, biological, and
engineered systems whose operations are integrated,
monitored, and/or controlled by a computational core.
Components are networked at every scale. Computing is
deeply embedded into every physical component,
possibly even into materials.
The computational core is an embedded system, usually
demands real-time response, and is most often
distributed.
The behavior of a cyber-physical system is a fullyintegrated hybridization of computational (logical),
physical, and human action.”
- National Science Foundation
22
Characteristics of CPS
• Cyber capability in every physical component
• Interaction at large scales with wired or wireless networks
• Dynamically re-organizing
• Novel computational substrates (bio / nano)
• Tight integration of computation, communication and control

High degree of automation

Operation must be dependable and certified
Sensor nets + control + distributed computing + real-time systems
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Example: Automotive Telematics
• Intra-vehicular sensing and control

Engine control, Break system, Airbag deployment system,
windshield wiper, Door locks, Entertainment system
• V2V networks

Cars are sensors and actuators

Vehicular safety

Autonomous navigation
• Future Transportation Systems

Incorporate both single person and mass transportation vehicles, air
and ground transportations.

achieve efficiency, safety, stability using real-time control and
optimization.
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Example: Health Care and Medicine
• Electronic Patient Records

Records accessible anywhere, any time
• Home care: monitoring and control

Pulse oximeters, blood glucose monitors, infusion pumps,
accelerometers, …
• Operating Room of the Future

Closed loop monitoring and control; multiple treatment stations,
plug and play devices; robotic microsurgery

System coordination challenge
• Progress in bioinformatics: gene, protein expression,
systems biology, disease dynamics, control mechanisms
25
Example: Electric Power Grid
• Current picture

Equipment protection devices trip locally, reactively

Cascading failure
• Better future?

Real-time cooperative control of protection devices

Self-healing, aggregate islands of stable bulk power

Green technologies

Coordinate distributed and dynamically interacting participants
26
Assignment 1
•
Choose a WSAN application paper and prepare a report and ppt

Prepare a 2 page report
 11 point font
 Latex typesetting preferred
 Conference style formatting
 Prepare list of references
 Text in your own words

State system requirements and challenges

List enabling technologies

Discuss how wireless networking of embedded devices play a role

Discuss scalability and robustness of solution

Discuss improvements and extensions

State one new application of your choice for WSNs
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Assignment 1
•
Samba: A Smartphone-Based Robot System for Energy-Efficient
Aquatic Environment Monitoring [ipsn 2015]
•
LookUp: Enabling Pedestrian Safety Services via shoe Sensing
[mobisys 2015]
•
Contactless sleep apnea detection using smartphones [mobisys
2015]
•
AccelWord: Energy Efficient Hotword Detection through
Accelerometer [Mobisys 2015
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Assignment 1
•
A System for Fine-Grained Remote Monitoring, Control and PrePaid Electrical Service in Rural Microgrids (CMU, IPSN 2014)
•
Aquatic Debris Monitoring Using Smartphone-Based Robotic
Sensors (MSU, IPSN 2014)
•
Airplanes Aloft as a Sensor Network for Wind Forecasting
(Microsoft Research, IPSN 2014)
•
One Meter to Find Them All - Water Network Leak Localization
Using a Single Flow Meter (Penn state, IPSN 2014)
29
Assignment 1
•
Magneto-Inductive NEtworked Rescue System (MINERS):
Taking sensor networks underground(Oxford, IPSN 2012)
•
Sensing Through the Continent: Towards Monitoring Migratory
Birds using Cellular Sensor Networks (Nebraska, IPSN 2012)
•
Non-invasive Respiration Rate Monitoring Using a Single COTS
TX-RX Pair (Aalto university, IPSN 2014)
•
Using wearable inertial sensors for posture and position tracking
in unconstrained environments through learned translation
manifolds (Edinburgh, IPSN 2013)
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Other previous applications
SLEWS: A Sensorbased Landslide Early Warning System
Power grid monitoring
Embedded systems for energy-efficient buildings (eDIANA)
Water quality monitoring
Sensor networks for UV radiation control
Precision agriculture and Agricultural applications
Indoor environmental monitoring systems
Damage detection in civil structures
Participatory urban sensing
31
Other previous applications
Micro-strain sensor network for monitoring shuttle launch
Smart room using camera networks
Active visitor guidance system
Analysis of a habitat monitoring application
Smart-tag based data dissemination
Meteorology and Hydrology in Yosemite
Continuous medical monitoring
ZebraNet
Virtual fences
32
Other previous applications
SenseWeb
CarTel
Assisted Living
Wearable wireless body area networks (Health care)
Adaptive house
House_n project
Responsive Environments
Counter-sniper system
Self-healing land mines
33
Other previous applications
•
Take a look at Libelium Top 50 applications

These are some of the potential application areas for sensor actuator
networks: mostly non-military

http://www.libelium.com/top_50_iot_sensor_applications_ranking/
•
AN APLICATION THAT I JUST SAW TODAY

•
SMART DIAPERS!
THE IOT SPACE IS BOOMING

LOTS OF APPLICATIONS

CREATIVITY AND IMAGINATION IS THE LIMIT
34
Project ExScal: Concept of
operation
Put tripwires anywhere—in deserts, other areas where physical
terrain does not constrain troop or vehicle movement—to
detect, classify & track intruders [Computer Networks 2004,
ALineInTheSand webpage, ExScal webpage]
35
Application design choice
•
One large powerful sensor vs many distributed sensors
•
Distribution favours
•

Robustness

Overall coverage

Overall cost
Focus is on distributed computing and networking
37
ExScal summary
•
Application has tight constraints of event detection scenarios: long
life but still low latency, high accuracy over large perimeter area
•
Demonstrated in December 2004 in Florida
•
Deployment area: 1,260m x 288m
•
~1000 XSMs, the largest WSN
•
~200 XSSs, the largest 802.11b ad hoc network
38
One of ExScal sensors - PIR
PIR is a differential sensor: detects target as it crosses the “beams”
produced by the optic
39
PIR signal: Frequency
Human at 10 m
Car at 25m
Energy content for these two targets is in low frequency band
40
Pir target detector
[0-0.3 Hz]
Person at 12 m
SUV at 25 m
Bandpass: [0.4- 2 Hz]
Bandpass: [2- 4 Hz]
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A distributed classification approach
Assume a dense WSN
– Concept: each target type has unique influence field
– Multiple sensors which detect target coordinate,
potentially each with multiple sensing modalities
– Classification is via reliable estimation of influence field size
[Computer Networks 2004]
42
Further reading

The Computer for 21st Century

Next century challenges: mobile networking for Smart Dust

Connecting the physical world with pervasive networks

D. Tennenhouse, Proactive computing

Energy and performance considerations for smart dust
Interesting Links on Sensor Networks

www.wsnblog.com
43
Further reading
Some good advice for graduate students:
• Edsger Dijkstra, The Three Golden Rules for Successful Scientific Research
• Edsger Dijkstra, To a New Member of the Tuesday Afternoon Club
• Jim Kurose, Ten Pieces of Advice I Wish My PhD Advisor Had Given Me
• Andre DeHon, Advice for Students Starting into Research
• S. Keshav, How to Read a Paper
• Philip W. L. Fong, How to Read a CS Research Paper?
• William Strunk Jr., E. B. White, The Elements of Style. (Recommended book
on writing)
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