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Wireless Sensor Networks COE 499

Introduction to Sensor Networks

Tarek SheltamiKFUPMCCSECOE

http://faculty.kfupm.edu.sa/coe/tarek/coe499.htm

Outline

Introduction Application Areas Systems Involved Communications Challenges in SNETs Unique constraints Power Issues

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Involved Technologies

ComputationalPower

SensorTechnology

NetworkTechnology

SensorNetwork

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Application Areas Military Infrastructure security Environment & Habitat Monitoring Healthcare Industrial Sensing Traffic Control Seismic Studies Life Sciences

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The Systems involved Sensor Node Internals Operating System Physical Size

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Sensor Node Internals

SENSOR

POWERSUPPLY

CPU

COMMUNICATION

NODE

INFRARED

ACOUSTIC

SEISM

IC

IMAGE

MAGNETIC

…

ELECTRO-MAGNETICINTERFACE

Some Current Node Platforms:

1. Sensoria WINS

2. Smart Dust – Dust Inc. Berkeley

3. UC Berkeley mote – Crossbow (www.xbow.com)

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Operating System - TinyOS

Custom built at UC, Berkeley for wireless sensor nodes

Component-based architecture: ensures minimum code size

Component library includes: Network protocols Sensor drivers Data acquisition tools Distributed services

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Physical Size

AWACS

LWIM III AWAIRS I

WINS

NG 2.0

Berkley

Motes

A Few Smart Sensor Implementations

Tiny Heart

Smart Its Project

Capsule Endoscope

Finger Tip Sensors

JPL Sensor

A Bee Tracker

Smart Sensor Example in Health Care

Can be taken just like a capsule

It moves through the intestinal track due to contraction and relaxation

Excreted naturally and is disposed off

Safe to the body Future: Remote control

Pills and Micro-surgery

Duodenal Bleeding

Sensor Network in Health Care..

In-Home Health Care Solution from Intel In-home technology prototypes illustrate how tiny

silicon-based sensing devices discreetly embedded in objects such as shoes, furniture and home appliances

It can make it possible for elders, Alzheimer's disease patients and others with disabling conditions to continue to live at home

Intel and university researchers determined that wireless sensor networks, combined with powerful computing and complex algorithms, can effectively send prompts through various household devices to assist the elderly and inform, as well as ease the workload of caregivers.

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Biomimetics Living organisms use sensory abilities for all activities This is in spite of lot of noise in the environment The science of such sensory fusion is available in

Biology Biomimetics – Mimic the available knowledge in Biology

to design robust sensor fusion algorithms A few preliminary applications are shown below

Electronic Tongue Electronic Nose04/18/23

In-Home Health Care Solution from Intel

Intel Research Seattle uses postage-sized wireless radio frequency identification (RFID) tags affixed to household objects

To monitor and record the daily activities of an elder

The tags wirelessly communicate the data back to a central system that could help manage everyday activities so that the elders' independence is maintained while relieving some of the burden of around-the-clock care by caregivers

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California Institute of Technology - MicroBat

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Water wheel at farm gate.

Water level sensor.

Solar panel.

Cabinet with radio sender, micro processorand digital and analog I/O.

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Central Goulburn no. 2 channel.

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Mulwala canal.

Largest irrigation channel inthe southern hemisphere.

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Communication

Network Protocol Network Discovery Network Control & Routing

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Network Protocol

For wireless sensor networks: IEEE 802.11 standards

Personal Area Networks (PAN): IEEE 802.15 standard Radius of 5 to 10m Ideal application in short-range

sensors

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Network Discovery Knowledge of identity and location of

its neighbor Ad hoc protocols can be used GPS system can be used as well

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Network Control & Routing Network adapts dynamically to

conserve resources like energy and available nodes Make optimum use of bandwidth and processing

power Connectivity must emerge as needed from

algorithms Directed Diffusion routing

Data identity is separate from node identity Promotes adaptive, in-network processing

Sensors

Passive elements: seismic, acoustic, infrared, strain, humidity, temperature, etc.

Passive Arrays: imagers (visible, IR), biochemical

Active sensors: radar, sonar High energy, in contrast to passive

elements Technology trend: use of IC technology for

increased robustness, lower cost, smaller size

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Event Driven Model

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On-Demand Model

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TinyOS is an open-source operating system designed for wireless embedded sensor networks. It features a component-based architecture which enables rapid innovation and implementation while minimizing code size as required by the severe memory constraints inherent in sensor networks. TinyOS's component library includes network protocols, distributed services, sensor drivers, and data acquisition tools – all of which can be used as-is or be further refined for a custom application. TinyOS's event-driven execution model enables fine-grained power management yet allows the scheduling flexibility made necessary by the unpredictable nature of wireless communication and physical world interfaces. TinyOS has been ported to over a dozen platforms and numerous sensor boards. A wide community uses it in simulation to develop and test various algorithms and protocols. New releases see over 10,000 downloads. Over 500 research groups and companies are using TinyOS on the Berkeley/Crossbow Motes. Numerous groups are actively contributing code to the sourceforge site and working together to establish standard, interoperable network services built from a base of direct experience and honed through competitive analysis in an open environment .