AN APPROACH FOR TRACKING WILDLIFE USING WIRELESS SENSOR NETWORKS - - PowerPoint PPT Presentation

AN APPROACH FOR TRACKING WILDLIFE USING WIRELESS SENSOR NETWORKS

Francine Lalooses*† Hengky Susanto* Chorng Hwa Chang* * Tufts University

† MITRE Corporation

Approved for Public Release; Distribution Unlimited. Case Number 07-0512

Outline

• Overview

– Introduction – Tracking moving target – Related work

• Sensor network for habitat monitoring

– ZebraNet – Great Duck Island

• Distributed Predictive Tracking Algorithm
• Problem with Target Tracking
• Tracking Failure Recovery
• Quandary of Recovering from Failure
• Future Work
• Overview

– Introduction – Tracking moving target – Related work

• Sensor network for habitat monitoring

– ZebraNet – Great Duck Island

• Distributed Predictive Tracking Algorithm
• Problem with Target Tracking
• Tracking Failure Recovery
• Quandary of Recovering from Failure
• Future Work

Introduction: Wireless Sensor Networks

• Consist of sensors and base stations
• Purpose of tracking in sensor networks is

a necessity for many applications

– Including computer vision, tactical battlefield surveillance, perimeter security, emergency response, animal tracking

Analogy Illustration

Purpose of Tracking

• For wildlife habitat monitoring
• Sensors only monitor land targets (animals)
• Animals are tagged
• Sensors purposely placed at certain

locations

• Saves time finding target in the region
• Better understanding of region/animal

relationship

Tracking Moving Target

• Sensors:

– Hibernate to conserve energy – Awaken when target detected entering the monitored area – Sensors record information of the target – Relay information between sensors and follows target movement

Tracking Moving Target in Wildlife

Awake Hibernating

ZebraNet

• Track animals long term and over long

distances

• GPS enabled
• All nodes mobile
• Zebras are tagged with RFID
• Peer-to-peer routing and data storage

Great Duck Island

• Biologists put sensor devices on Maine's Great

Duck Island

– In underground nests – 4-inch stilts placed just outside their burrows

• Record data about the birds
• Sensors relay information to a gateway node

(the base station)

– Gateway node transmits information to

• a laptop
• then to satellite dish
• ultimately, to an Intel Research lab at Berkeley California

Great Duck Island

Distributed Predictive Tracking

A Protocol for Tracking Mobile Targets using Sensor Networks, RPI

• No central point
• Cluster based architecture
• Assumptions:

– Randomly distributed sensors – Default to normal beam – Hibernation mode

• Predictive mechanism
• Wakeup all sensors for recovery

Outline

• Overview

– Introduction – Tracking moving target – Related work

• Sensor network for habitat monitoring

– ZebraNet – Great Duck Island

• Distributed Predictive Tracking Algorithm
• Problem with Target Tracking
• Tracking Failure Recovery
• Quandary of Recovering from Failure
• Future Work

Problem Tracking Moving Target in Wildlife

What if . . .

Lost Target Conditions

• Network failure: When node that is currently

monitoring target fails to wake the next node

• Prediction failure: Failure predicting where the

target is heading

• Multiple sensors interaction: Failure to

recognize multiple targets at once

• Hardware malfunction: Hardware may

malfunction or the battery is weakening

Outline

• Overview

– Introduction – Tracking moving target – Related work

• Sensor network for habitat monitoring

– ZebraNet – Great Duck Island

• Distributed Predictive Tracking Algorithm
• Problem with Target Tracking
• Tracking Failure Recovery
• Quandary of Recovering from Failure
• Future Work

Approach in Tracking Failure Recovery

• Goal

– Finds the monitored target after failure occurs

• Purpose:

– Conserve energy – Quick and efficient method to recover from failure

How Does The Algorithm Work?

• Analogy of lost tourist in Marrakesh

– Keeping track the traveler – Lost the traveler in Hotel Kenzi Farah – Where to find the traveler

• Check the popular places around the hotel

– Casino, Jemaa El Fna, Mosque, Koutoubia

• Establish the search region

– Perform search for the lost traveler

Why This Approach

• Studies show:

– Animals tend to move in certain patterns

• Along river
• Tree

– Animals are sensitive to temperature and chemical elements

Algorithm Summary

• Establish search region

– To limit the search area – Take advantage of hierarchical cluster

• Finding popular place surrounding where

the animal last seen

• Perform search algorithm

Establish Search Region

• Computes the diameter of search region

– Uses approximate velocity of animal – Radius d = time t * V

• Uses hierarchical cluster to find popular

place in that region

– Place that is often visited by animals such as {River, Trees, etc}

Hierarchical Cluster

• Nodes form clusters after deployment
• Each cluster select a leader or a Cluster

Head (CH)

• Only CH communicate to each other
• Reduces traffic
• Eliminates network collisions

Hierarchical Cluster

• Cluster based algorithm
• Hierarchical approach
• Variables:

– Distance d = Velocity * time

CH CH d d CH First level CH Master CH

Search Algorithm

• x = CH of the target’s last seen position
• y = Identified CH popular place
• Computes distance y to x

y y y y X

Broadcast and Activate Nodes

• X = the object’s last seen position
• Broadcast from X
• Activate sensors
• Establish minimized region

X

Minimizing Search Region

• Calculation based on maximum hop and

popularity

• Variables:

– h = CH hop count

2d

1h 4h 2h

Lost region

Understanding Necessary Conditions

• Coverage area
• Sensor placement and terrain
• Sensor limitation
• Sensor reliability
• Multiple sensor interaction and

identification

Oops!!

• What if the animal is not in the desired

search region?

– Awake all nodes in the initial search region

Outline

• Overview

– Introduction – Tracking moving target – Related work

• Sensor network for habitat monitoring

– ZebraNet – Great Duck Island

• Distributed Predictive Tracking Algorithm
• Problem with Target Tracking
• Tracking Failure Recovery
• Quandary of Recovering from Failure
• Future Work

Quandary of Recovering from Failure

• Long description to describe a single target

– Due to limited information from sensor itself – Takes large amount of bandwidth – Requires processing power – Requires storage space in sensor – Not energy efficient

• Moving target’s speed

– Difficult to estimate the speed accurately

Outline

• Overview

– Introduction – Tracking moving target – Related work

• Sensor network for habitat monitoring

– ZebraNet – Great Duck Island

• Distributed Predictive Tracking Algorithm
• Problem with Target Tracking
• Tracking Failure Recovery
• Quandary of Recovering from Failure
• Future Work

Future Work

• More in depth understanding on

– Relation between animal’s behavior and accuracy of establishing search region – Performance analysis evaluation – Network traffic analysis during recovery process

In Progress

• Minimizing target description

– More efficient description to describe the target

• Improving the test bed in our sensor lab

Thank You Merci Shukran