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AutoWitness: Locating and Tracking Stolen Property While Tolerating GPS and Radio Outages

机译:AutoWitness:在容忍GPS和无线电中断的同时定位和跟踪被盗的财产

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摘要

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.
机译:我们介绍了AutoWitness,该系统可以阻止,检测和跟踪个人财产盗窃,提高历史上令人沮丧的失窃财产追回率并破坏被盗财产分配网络。财产所有人在待保护的资产内嵌入一个小标签,该标签处于休眠状态,直到检测到车辆移动为止。一旦移动,标签使用基于惯性传感器的航位推算来估计位置变化,但是为了减少积分误差,只要传感器指示车辆已停止,相对位置就会重置。运动,停止和转弯的顺序以紧凑的形式记录下来,并在经过足够的时间(避免检测到)并且可以检测到RF功率(提示可以进行蜂窝访问)之后,最终使用蜂窝调制解调器将其传输到服务器。最终,将轨迹数据发送到服务器,该服务器尝试将路径与观测值匹配。该算法使用城市街道的隐马尔可夫模型和维特比解码来估计最可能的路径。拟议的设计利用了低功率无线电和惯性传感器,可以防止过时的伪装,并支持事后路径重建。我们的原型展示了设计的技术可行性;推动机器对机器通信的大量市场力量将很快使该设计在经济上可行。

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