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AutoWitness: Locating and tracking stolen property while tolerating GPS and radio outages

Published: 25 September 2012 Publication History

Abstract

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. Our prototype demonstrates technical viability of the design; the volume market forces driving machine-to-machine communications will soon make the design economically viable.

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      Published In

      cover image ACM Transactions on Sensor Networks
      ACM Transactions on Sensor Networks  Volume 8, Issue 4
      September 2012
      292 pages
      ISSN:1550-4859
      EISSN:1550-4867
      DOI:10.1145/2240116
      Issue’s Table of Contents
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Association for Computing Machinery

      New York, NY, United States

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      Publication History

      Published: 25 September 2012
      Accepted: 01 August 2011
      Revised: 01 May 2011
      Received: 01 December 2010
      Published in TOSN Volume 8, Issue 4

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      Author Tags

      1. Theft detection
      2. burglar tracking
      3. inertial navigation

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      • (2020)Intelligent Trajectory Inference Through Cellular Signaling DataIEEE Transactions on Cognitive Communications and Networking10.1109/TCCN.2019.29616606:2(586-596)Online publication date: Jun-2020
      • (2019)A Feasible Method for the Trajectory Measurement of Radial Jet Drilling LateralsSPE Drilling & Completion10.2118/192140-PAOnline publication date: 14-Oct-2019
      • (2019)Mobile Phone Anti-theft Method Based on Mobile Track and User Characteristic2019 5th International Conference on Big Data Computing and Communications (BIGCOM)10.1109/BIGCOM.2019.00012(28-32)Online publication date: Aug-2019
      • (2019)Surviving sensor node failures by MMU-less incremental checkpointingJournal of Systems and Software10.1016/j.jss.2013.09.00187(74-86)Online publication date: 2-Jan-2019
      • (2018)Location Privacy Violation via GPS-agnostic Smart Phone Car TrackingIEEE Transactions on Vehicular Technology10.1109/TVT.2018.2800123(1-1)Online publication date: 2018
      • (2018)The future of data privacy and security concerns in Internet of Things2018 IEEE International Conference on Innovative Research and Development (ICIRD)10.1109/ICIRD.2018.8376320(1-4)Online publication date: May-2018
      • (2018)Traffic flow monitoring systems in smart cities: Coverage and distinguishability among vehiclesJournal of Parallel and Distributed Computing10.1016/j.jpdc.2018.07.008Online publication date: Aug-2018
      • (2017)Accurate Real-time Map Matching for Challenging EnvironmentsIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2016.259195818:4(847-857)Online publication date: 1-Apr-2017
      • (2017)SmartMTra: Robust Indoor Trajectory Tracing Using SmartphonesIEEE Sensors Journal10.1109/JSEN.2017.269226317:12(3613-3624)Online publication date: 15-Jun-2017
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