TelosCAM: Identifying Burglar through Networked Sensor-Camera Mates with Privacy Protection

Shaojie Tang, Xiang-Yang Li, Haitao Zhang, Jiankang Han, Guojun Dai, Cheng Wang, Xingfa Shen
<span title="">2011</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/v45oxowmzff5lbub4ixtl2tazu" style="color: black;">2011 IEEE 32nd Real-Time Systems Symposium</a> </i> &nbsp;
We present TelosCam, a networking system that integrates wireless module nodes (such as TelosB nodes) with existing legacy surveillance cameras to provide storage-efficient and privacy-aware services of accurate, realtime tracking and identifying of the burglar who stole the property. In our system, a property owner will have a wireless module node (called secondary module) for each of the properties that s/he wants to protect. The secondary wireless module node (which may be equipped with a
more &raquo; ... ion detector) will not store any personal information about the owner, nor any specific information about the property to be protected. Each user of the system will also have a unique wireless module node (called primary module) that contains some security information about the owner, thus should be privately held by the user and be kept to the user always. The primary wireless module node will periodically send the heart-beat information to the secondary wireless module node. Once a secondary wireless module cannot detect the existence of a primary wireless module within its vicinity and it detects its own movement, it will start sending out the alarm signal periodically. The alarm signal will be captured by some reading wireless module nodes, integrated with existing surveillance cameras. Using the trajectory information provided by the secondary wireless module node, and the images captured by the surveillance cameras, our system will then automatically pinpoint the target burglar (e.g., a person or a car) that carries the stolen property. Our extensive evaluation of the system shows that we can find the burglars with almost 100% accuracy, while significantly reduce the storagerequirement of the legacy video surveillance system. It also can help the police to catch the burglars more efficiently by providing critical images containing the burglars.
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