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Conference Papers Year : 2020

Hybrid Internet of Things Network for Energy Efficient Video Surveillance

Abstract

Wi-Fi-based wireless multimedia sensor networks (WMSNs) are effective and flexible solutions for video surveillance systems in detecting intrusions in selected monitored areas. The Wi-Fi-based WMSNs offer high bit rate video transmissions but suffer from energy inefficiency problems. To resolve the energy inefficiency problem, this paper proposes a hybrid system through the integration of Wi-Fi-based WMSN along with the LoRa network to form an autonomous and high bit rate, energy-efficient video surveillance system. The proposed solution used for intruder detection and tracking is investigated. By taking the advantages of LoRa network characteristics (i.e., low cost, long range and low- power consumption), this paper proposes to use the LoRa network as an always-active network for preliminary motion detection and transmitting sensed information to the central controller so that the central controller can decide which visual sensor nodes to wake up or shut down. Based on the target detection and tracking information, the central controller can forward a control command through the LoRa network for completely shutting down the visual sensor nodes that are idle. Further, the central controller can wake up the visual sensor nodes that are needed and participating in the video vigilance activity. Thus, it reduces the energy consumption in the network. The hybrid proposed system is numerically simulated, and the results show that the proposed approach can help in reducing a significant amount of energy consumption. Hence, the proposed approach is a new knowledge contribution towards the energy-efficient systems in the Internet of Things (IoT) domain.
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Dates and versions

hal-03002244 , version 1 (12-11-2020)

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Eyassu Dilla Diratie, Khaldoun Al Agha. Hybrid Internet of Things Network for Energy Efficient Video Surveillance. 2020 IEEE 6th World Forum on Internet of Things (WF-IoT), Jun 2020, New Orleans, United States. pp.1-6, ⟨10.1109/WF-IoT48130.2020.9221241⟩. ⟨hal-03002244⟩
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