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Video Surveillance Applications based on ultra-low power sensors

Abstract : Power consumption is an important goal for many applica- tions, expecially when the power can be wasted doing nothing. Video surveillance is one of this application where the camera can be on for long period without "see" nothing. For this reason several power man- agement techniques were carried out in order to reduce the activities of the camera when it is not needed. In this work we focus on surveillance applications performed through Video Surveillance Camera (VSC) that are not permanently active, but need to be properly "woken-up", by speci c ultra Low Power wireless Sensor Nodes (LPSN) able to monitor continuously the area. named. The LPSN are equipped by Piezoelectric "Passive" Infrared (PIR) sensors to detect the movement, thus they have a speci c transmission range (to wirelessly send the "wake-up" messages to the camera sensor device) and a sensing range to detect events of in- terest (i.e. a man that crosses a speci c area). Di erent deployments may highly impact not only in terms of events detectable, but also in terms of the number of VDS that can be woken-up. In this work, we propose a neural/genetic algorithm, that tries to compute the best deployment of the LPSN, based on two weight factors that "prioritize" the rst ob- jective, that is the number of VSC that can be woken-up or the second objective, namely the events detectable. The two objectives can be op- posite and based on the di erent values assigned to the weight factors, di erent deployments can be obtained. The performance evaluation is realized through a simulation tool and we will show the e ectiveness of our approach to reach very e ective deployments in di erent scenarios.
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Contributor : Valeria Loscri <>
Submitted on : Wednesday, November 18, 2015 - 4:45:58 PM
Last modification on : Friday, October 30, 2020 - 12:04:03 PM
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Valeria Loscri, Michele Magno, Rosario Surace. Video Surveillance Applications based on ultra-low power sensors. 1st International Workshop on Autonomous Monitoring and Networking (WAMN'14) in conjunction with ADHOCNETS 2014, Aug 2014, Rhodes Island, Greece. pp.235-244, ⟨10.1007/978-3-319-13329-4_21⟩. ⟨hal-01053390⟩



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