Abstract
Nowadays, to improve animal well being in livestock farming or beekeeping application, a wireless video sensor network (WVSN) can be deployed to early detect injury or Asiatic hornets attacks. WVSN represents a low-cost monitoring solution compared to other technologies such as the closed circuit television technology (CCTV). WVSNs are composed of low-power resource-constrained video sensor nodes (motes). These nodes capture frames from videos at a given frequency (frame rate) and wirelessly send them to the sink. The big amount of data transferred from the nodes to the sink consumes a lot of energy on the sensor node, which represents a major challenge for energy-limited nodes. In this paper, we introduce two complementary mechanisms to reduce the overall number of frames sent to the sink. First, the Transmission Data Reduction algorithm (TDR) run on the sensor node leverages the similarity degree of consecutive images. Second, the Inter-Nodes Similarity algorithm (INS) exploits the spatio-temporal correlation between neighbouring nodes in order reduce the number of captured frames. The results show a \(95\%\) data reduction, surpassing other techniques in the literature by \(30\%\) at least.
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Acknowledgements
This work was partially supported by a grant from CPER DATA, by LIRIMA Agrinet project and the Inria/CEFIPRA Associate team DC4SCM.
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Salim, C., Mitton, N. (2021). Image Similarity Based Data Reduction Technique in Wireless Video Sensor Networks for Smart Agriculture. In: Barolli, L., Woungang, I., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2021. Lecture Notes in Networks and Systems, vol 225. Springer, Cham. https://doi.org/10.1007/978-3-030-75100-5_39
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DOI: https://doi.org/10.1007/978-3-030-75100-5_39
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