Prediction-based Object Tracking and Coverage in Visual Sensor Networks Tzung-Shi Chen Jiun-Jie Peng,De-Wei Lee Hua-Wen Tsai Dept. of Com. Sci. and Info. Dept. of Info. and Learning Dept. of Computer Info. and Engineering Technology Network Eng. National University of Tainan National University of Tainan Lunghwa University of Science Tainan 700, Taiwan Tainan 700, Taiwan and Technology, Taiwan IEEE Proceedings of The 7th International Wireless Communications and Mobile Computing Conference (IWCMC 2011)

Outline  Introduction  Goals  Network Model and Assumptions  Prediction-based algorithm for the tracking and coverage of objects(POTC)  Experimental results  Conclusion

Introduction  Visual sensor networks(VSNs) are a type of wireless sensor network.  All sensor are equipped with cameras  Difference between visual and scalar sensor Visual sensor can capture the image of object Scalar sensorVisual sensor 0/1

Introduction  When tracking a mobile object, visual sensors cannot remain in an active mode until the object is out of the sensing range  To track objects, a set of visual sensors must be active before the mobile object approaches them

Goals  We have developed an algorithm to monitor the mobile object Minimum number of visual sensors Maximum coverage of mobile object

Network Model and Assumptions Sensor Node  Each sensor Deploying randomly Communication range = Sensing range Location-aware Location of object Equipped the camera Camera can rotate 360° Active and sleep  The object is mobile and moving with a random waypoint  Build up a planar graph by Gabriel Graph for the visual sensor network Mobile object

Prediction-based algorithm for the tracking and coverage of objects(POTC)  Awakening the Monitoring Area using Face Routing  Covered Range

Prediction-based algorithm for the tracking and coverage of objects(POTC)  Awakening the Monitoring Area using Face Routing  Covered Range

Prediction-based algorithm for the tracking and coverage of objects(POTC) Sensor node Mobile object Nearest node Cross node Cross edge Moving edge

Prediction-based algorithm for the tracking and coverage of objects(POTC) Sensor node Mobile object Nearest node Cross node Cross edge Moving edge Routing edge Wake node F1F1 F2F2 F3F3 F4F4 F5F5 F6F6

Prediction-based algorithm for the tracking and coverage of objects(POTC) Sensor node Mobile object Cross edge Moving edge Routing edge Boundary node Wake node F1F1 F2F2 F3F3 F4F4 F5F5 F6F6 F7F7 F8F8 F9F9 F 10 F 11 F 13 F 12 F 14 F 15 F 16 F1 7

Prediction-based algorithm for the tracking and coverage of objects(POTC)  Awakening the Monitoring Area using Face Routing  Covered Range

Single Characteristic Point Multiple Characteristic Point Covered Segment Both Covered Segment Prediction-based algorithm for the tracking and coverage of objects(POTC)

 Covered Range Single Characteristic Point Multiple Characteristic Point Prediction-based algorithm for the tracking and coverage of objects(POTC)

Experimental results

Conclusion  we developed the algorithm, prediction-based object tracking and coverage algorithm (POTC) to monitor the mobile object Minimum number of visual sensors Maximum coverage of mobile object

Thank you

Experimental results