Overview and applications Vinod Kulathumani West Virginia University

Overview and applications

Vinod Kulathumani

West Virginia University

2

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

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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

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Networked embedded systemsCurrently

• 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 ?

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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

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New Class of Computing

year

log

(p

eo

ple

pe

r c

om

pu

ter)

streaming informationto/from physical world

Number CrunchingData Storage

productivityinteractive

Mainframe

Minicomputer

Workstation

PC

Laptop

PDA

Slide courtesy: Murat Demirbas

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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

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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

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A typical sensor node

• Telosb (2007)

8 MHz MSP430 processor

10kB RAM

250 Kbps data rate

Integrated temperature, humidity, light sensors

• Others

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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

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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?)

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Block diagram of a sensor node

Substitute any sensing / actuating modality

Actuator(Buzzer)

Processor

Application

NetworkInterface

PROCESSINGSUB-SYSTEM

COMMUNICATIONSUB-SYSTEM

SENSINGSUB-SYSTEM

POWER MGMT.SUB-SYSTEM

ACTUATIONSUB-SYSTEM

SECURITYSUB-SYSTEMSensor

(Light)

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Application category – Monitoring type

Environmental monitoring

Perimeter security

Infrastructure monitoringBody sensor networks

Object tracking

Camera sensor networks

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Emerging applications

• Combination of sensors with mobile devices

Social networking

Participatory urban sensing

• Assisted living – health monitoring

• Vehicular networks with variety of sensors

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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

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Challenges in sensor networks

• Energy constraint

• Unreliable communication

• Unreliable sensors

• Ad hoc deployment

• Large scale networks

• Distributed execution

• Ease of use

: Nodes are battery powered

: Radio broadcast, limited bandwidth, bursty traffic

: False positives

: Pre-configuration inapplicable

: Algorithms should scale well

: Difficult to debug & get it right

: All Scientists not programmers

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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!

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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!

Note

Applying control theory for network systems – has existed before (example: TCP congestion)

This is control systems designed on top of networks

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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







• Ease of use


: Wireless, limited bandwidth, bursty traffic

: False positives, negatives





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Add to these ....







• Ease of use


: Wireless, limited bandwidth, bursty traffic

: False positives, negatives





…. A control application that sits on top

Requires information guarantees from network below!

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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 fully-integrated hybridization of computational (logical), physical, and human action.”

- National Science Foundation

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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

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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

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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 Pre-Paid 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)

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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

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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

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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

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• 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

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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]

Project ExScal: Concept of operation

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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

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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

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One of ExScal sensors - PIR

PIR is a differential sensor: detects target as it crosses the “beams”

produced by the optic

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PIR signal: Frequency

Human at 10 m Car at 25m

Energy content for these two targets is in low frequency band

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Pir target detector

Person at 12 m

Bandpass: [0.4- 2 Hz]

[0-0.3 Hz]

Bandpass: [2- 4 Hz]

SUV at 25 m

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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]

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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

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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)

Documents

Overview and applications Vinod Kulathumani West Virginia University