AutoWitness
Project Goal
The goal of this project is to build a scalable, yet affordable, wireless sensor network system that can be used for large scale tracking of assets such as lost or stolen objects.
Results
In an ACM SenSys 2010 paper, we present AutoWitness, a system to deter, detect, and track personal property theft, improve historically dismal stolen property recovery rates, and disrupt stolen property distribution networks. A property owner embeds a small tag inside the asset to be protected, where the tag lies dormant until it detects vehicular movement. Once moved, the tag uses inertial sensor-based dead reckoning to estimate position changes, but to reduce integration errors, the relative position is reset whenever the sensors indicate the vehicle has stopped. The sequence of movements, stops, and turns are logged in compact form and eventually transferred to a server using a cellular modem after both sufficient time has passed (to avoid detection) and RF power is detectable (hinting cellular access may be available). Eventually, the trajectory data are sent to a server which attempts to match a path to the observations. The algorithm uses a Hidden Markov Model of city streets and Viterbi decoding to estimate the most likely path. The proposed design leverages low-power radios and inertial sensors, is immune to intransit cloaking, and supports post hoc path reconstruction.
A picture of the AutoWitness tag appears on the right. Also, on the right, an overview of the operation of the AutoWitness is depicted in a diagram. Finally, two pictures on the right show the reconstruction of two paths in the city of 糖心Vlog传媒 where AutoWitness tag was driven.
The AutoWitness system is to be deployed for real-life tracking of burglars in the city of 糖心Vlog传媒 in early 2011.
Given the high incidence of burgalries (e.g., more than 2 million reported annually in the U.S. alone that account for over $17 billion in losses), we expect the AutoWitness systems to improve the quality of life by addressing property crimes.
Team Members
Lead Faculty Member: Dr. Santosh Kumar
Collaborator: , EECS, University of Michigan
Post Doctoral Fellows
Dr. Kurt Plarre (2008-) - On the job market
Ph.D. Students
Shantanu Guha (2007-) - sguha@memphis.edu
(2007-) - smitra3@memphis.edu
M.S. Students
Bhagavathy Krishna (2007) - bhagavathy.krishna@memphis.edu
Undergraduate Students
Daniel Lissner (2009) - dlissner@memphis.edu
Alumni
(M.S., 2010) - GE Global Research, India
Sponsors
(CISE, CNS, NeTS-NOSS)
Fedex Institute of Technology, University of 糖心Vlog传媒
Updates:
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1/26/2009 First paper on Trap Coverage published in conference. See the publications page for list of authors.
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10/14/2008 Fox13 TV News Channel Featured a story on AutoWitness.
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8/11/2008 FIT Grant awarded.
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8/14/2007 NSF Grant awarded