wireless sensor network with mobile integration

WIRELESS SENSOR

NETWORK WITH MOBILE

INTEGRATIONSubmitted by

Shashank Agarwal

Umangjeet Pahwa

Ashish Anand

SANDEEP TAYAL(PROJECT GUIDE)

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WSN: A link between the sensory world and the digital world

Earliest: In 1994 DARPA funded research on ‘Low Power Wireless Integrated Micro sensor’

In 2003, Technology Review from MIT, listed WSN on the top, among 10 emerging technologies that would impact our future

Base Station

InternetCloud

Sensor Nodes

Aggregator

A Typical Architecture

InformationProcessing

CenterWSN

HUMAN

HUMAN-SENSES

TELOSB-MOTE

MOTE SENSES

Temperature Humidity Infrared

LOCATIONAnd much more..

• “A sensor network is a deployment of massive numbers of small, inexpensive, self-powered devices that can sense, compute, and communicate with other devices for the purpose of gathering local information to make global decisions about a physical environment”.

THE SENSOR NETWORK

NodesSink NodesTo server

SENSOR NETWORKCOMMUNICATION

HOW DOES IT WORK

Base Station

InternetCloud

ARCHITECTURE

Client Machine

MOTE SERVERCOMMUNICATION

WEB VIEW OF THE DATA

MOBILE VIEW OF THE DATA

Structural Health Monitoring

Precision Agriculture

Mobile Urban SensingWildlife sensing

Smart Buildings

APPLICATIONS

APPLICATION CASE 1

WSN IN

MEDICAL DIAGNOSIS

Real-Time Patient Monitoring

Data Capture Mobile Device

Mobile Gateway

Real Time Patient Monitoring

Wireless Body Area Network

APPLICATION CASE 2

LANDSLIDE DETECTION

• Bases on research paper by Amrita University for landslide detection.

• Implemented at  Munnar, Idukki, Kerala, India.

• Collects data such as moisture, vibration and movement .

• Embedded 15 meters beneath the earth at different points.

LANDSLIDE DETECTION SYSTEM

Multi-Sensor Deep Earth

Sensor

Meter Sensor Column (during deployment)

Field Data

APPLICATION CASE 3

HABITAT MONITORING

Great Duck Island Experiment• Leach's storm petrels spend much of

their lives out on the waters of the South Atlantic, heading north and to shore in the springtime to mate.

• Once on dry land, the male digs a shallow, narrow burrow, 2 to 6 centimeters below ground, 3 to 6 cm across, and anywhere from 30 cm to 2 meters long.

• Here the female will lay just one egg. Both parents will occasionally leave the nest to fly back out to deep waters to feed.

David Culler and his team at UC Berkeley have deployed since 2002 a network of more than 20 motes on the Great Duck Island to monitor the island’s habitat and the breeding habits of Leach Storm Petrels

• Passive infrared (PIR) sensors directly measure heat from the seabird

• Temperature/humidity sensors measure variations in ambient conditions resulting from prolonged occupancy

Sensors used

Extreme Scale Wireless Sensor Networking

• In December 2004, the OSU DARPA-NEST team headed by Anish Arora completed the first demonstration and experiments of ExScal.

• Demonstration covered an area 1.3km by 300m with about 1000 sensor nodes and around 200 backbone nodes

• One possible application: detection & classification of multiple intruder types over an extended perimeter.

General structure of a Ex-scale WSN for oceanographic monitoring

RESIDENTIAL/LIGHT

COMMERCIAL CONTROL

securityHVAClighting controlaccess controllawn & garden irrigation

PC & PERIPHERALS

INDUSTRIALCONTROL

processcontrolasset &

environmentmanagement

PERSONAL HEALTH CARE

BUILDING AUTOMATION

lighting controlaccess control

patient monitoringfitnessmonitoring

mouse keyboardjoystick

SENSOR NETWORKS

Sink

SED

SED SED

temperature monitoringenvironmental monitoringM2M communications

OTHER APPLICATION OF WSN

FUTURE

‘Smart dust’ to explore planets:

Tiny “smart” devices that can be borne on thewind like dust particles could be carried in space probes to explore other planets, UK engineers say. The devices would consist of a computer chip covered by a plastic sheaththat can change shape when a voltage is applied, enabling it to be steered. Details were presented at the National Astronomy Meeting in Preston. John Barker, from the University of Glasgow, said the particles could use wireless networking to form swarms.

REFERENCESI. “Landslide Detection & Early Alarm system” by Amrita

UniversityII. “Great Duck Island project petrel habitat analysis” by UC

Berkeley.III. Stephan Olariu, “Information assurance in wireless sensor

networks”, Sensor network research group, Old Dominion University.

IV. C. Chong and S. P. Kumar, “Sensor Networks: Evolution, Opportunities, and Challenges”, in Proceedings of the IEEE, vol. 91, no. 8, Aug. 2003.

V. G. Anastasi, M. Conti, M. Di Francesco, “The MAC Unreliability Problem in Duty-cycled IEEE 802.15.4 Wireless Sensor Networks (Extended version)”, DII-TR-2009-04, available online at: http://info.iet.unipi.it/~anastasi/papers/DII-TR-2009-04.pdf

VI. Network Simulator Ns2, http://www.isu.edu/nsnam/nsVII. ON World Inc, “Wireless Sensor Networks – Growing Markets,

Accelerating Demands”, July 2005, http://www.onworld.com/html/wirelesssensorsrprt2.htm

VIII.IEEE Standard for Information technology, Part 15.4; Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area

IX. Networks (LR-WPANs), IEEE Computer Society, 2006J. Hui and P. Thubert. Compression Format for IPv6 Datagrams in 6LoWPAN Networks. Internet Draft (Work in Progress), December 2008.

X. IPv6 over Low power WPAN (6lowpan) Working Group. Internet Engineering Task Force (IETF). http://www.ietf.org/html.charters/6lowpan-charter.html.

XI. M. Harvan. Connecting Wireless Sensor Networks to the Internet - a 6lowpan Implementation for TinyOS 2.0. Master’s thesis, School of Engineering and Science, Jacobs University Bremen, May 2007

THANK-YOU