autowitness : locating and tracking stolen property while tolerating gps and radio outages

AUTOWITNESS: LOCATING AND TRACKING STOLEN PROPERTY WHILE TOLERATING GPS AND RADIO OUTAGES

Santanu Guha, Kurt Plarre, Daniel Lissner, Somnath Mitra, Bhagavathy Krishna, Prabal Dutta, Santosh Kumar

ACM SenSys 2010- Sowhat 2010.11.23

OUTLINES Motivation Objectives & Challenges Related Works System Overview Hardware Design

Theft detection Estimating distance & Turns

Evaluation Conclusion

OUTLINES Motivation Objectives & Challenges Related Works System Overview Hardware Design

Theft detection Estimating distance & Turns

Evaluation Conclusion

Property crimes17.2 billion

Burglary, 22.7%$2079 / $4.6 billion

90% un-recovered

Larceny-theft, 67.5% $925 / $6.1 billion

90% un-recovered

Motor vehicle theft, 9.8%$6751 / $6.4 billion 80% recovered

MOTIVATION According to the FBI Uniform Crime Report,

2008an estimated losses resulted from…

OUTLINES Motivation Objectives & Challenges Related Works System Overview Hardware Design

Theft detection Estimating distance & Turns

Evaluation Conclusion

OBJECTIVES & CHALLENGES

Objectives Detection of theft Tracking of the stolen tag Pinpointing of the location

Challenges - Cost & Energy Hardware selection Theft classifier Tracking method

OUTLINES Motivation Objectives & Challenges Related Works System Overview Hardware Design

Theft detection Estimating distance & Turns

Evaluation Conclusion

RELATED WORKS Traditional home security systems

Deter or detect burglary only Unable to track or recover

Traditional asset tracking and vehicle recovery systems detected Not tolerate in-transit cloaking High power

LoJack, the most common stolen vehicle recovery systems A device to receive the activation signal needed High-power transmissions once actived Cost, $695

OUTLINES Motivation Objectives & Challenges Related Works System Overview Hardware Design

Theft detection Estimating distance & Turns

Evaluation Conclusion

SYSTEM OVERVIEW

SYSTEM OVERVIEWEmded tag

Dormant

Motion

Vehicular movement

Distance / turn estimate

(Accelerometer / Gyro)

Transfer to server(GSM / GPRS)

Path reconstruction

Motion detection(vibration dosimeter)

Sufficient time & RF power available

Classification(Accelerometer)

SYSTEM OVERVIEW

OUTLINES Motivation Objectives & Challenges Related Works System Overview Hardware Design

Theft detection Estimating distance & Turns

Evaluation Conclusion

HARDWARE Vibration dosimeter

– Motion detect 3-axis accelerometer

– Theft classification & Distance estimation 3-asix gyroscope

– Turns estimation GSM/GPRS modem

– Transfer Epic Core platform

OUTLINES Motivation Objectives & Challenges Related Works System Overview Hardware Design

Theft detection Estimating distance & Turns

Evaluation Conclusion

DESIGN – THEFT DETECTIONFLOW DIAGRAMDeep sleep Accelerometer sampling 1.05sec,

@200Hz

Accelerometer sampling 4.2 sec, @200Hz

Variance >

threshold

Compute variance ofmedians of every 15

samples

Partition 5.25 sec worth of data in 5 intervals

Decision tree classifier appliedMajority rule

vehicular movemen

t

Tracking

N

N

Y

Y

Collecting data in different scenarios Walking person car trolleys Rolling chair

Activity classification workUsing mobile phones to determine transportation modes[23]

Feature – energy & standard deviation

DESIGN – THEFT DETECTIONCLASSIFIER

Design - Estimating distance & TurnsAngle estimate Gyro rotation speed single integration

change in the attitude

Absolute value of 1st difference

Thresholds, Dh & Dl

Activation time

DESIGN - ESTIMATING DISTANCE & TURNSDISTANCE ESTIMATE 2nd order Butterworth Filter to remove noise

Median of 20 samples mean of 10 such medians

Accelerometer Double integration Distance

Curved roads – angular rotation info. From gyro

OUTLINES Motivation Objectives & Challenges Related Works System Overview Hardware Design

Theft detection Estimating distance & Turns

Evaluation Conclusion

EVALUATION – THEFT DETECTION 15000 samples (210 acc. readings/sample)

vehicle vs. person

EVALUATION – TURN ESTIMATION 120 turns for 6 values of angles

Ground truth – GPS on Android G1 phone

EVALUATION – DISTANCE ESTIMATION 300 different road segments (0.2 ~ 1.5miles)

Ground truth – GPS on Android G1 phone

OUTLINES Motivation Objectives & Challenges Related Works System Overview Hardware Design

Theft detection Estimating distance & Turns

Evaluation Conclusion

CONCLUSION Design & evaluation of the AutoWitness

systemDeter, detect, and track personal property theftLow-costUltra-low energy

Item PerformanceTheft detection No false negative / 1.45% false positiveTurn estimation Percentage error = 6.92 in averageDistance estimation >95% percentage of error < 10

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