Abstract
A Wireless Visual Sensor Network (WVSN) enables wide-area imaging and collection of images by networking multiple sensor nodes equipped with visual sensors and performing multi-hop communication between sensor nodes. Thus, it can be used for monitoring infrastructure facilities and rivers. However, the placement of sensor nodes has a significant impact on the connectivity and transmission loss of wireless communication. Also, the visual sensors have a limited imaging range. Therefore, the optimal sensor node placement and the imaging direction of the visual sensor should be decided in order to cover all events within the imaging range of the visual sensor. In this paper, we propose an intelligent system for optimization of sensor node placement in WVSNs. The proposed system integrates two methods by considering the number of events within the imaging range of the visual sensor for placement of sensor nodes and the imaging direction of visual sensors. From simulation results, we confirmed the SGC for both methods is maximized, so all sensor nodes are connected. While, considering NCE for CCM not all events are covered at the end of iterations, while for CCM-based SA all events are covered. From vizualization results, for CCM there is a dense placement of sensor nodes and not all events are covered. While, for CCM-Based SA the nodes are spread over a wider area and all events are covered in the imaging range of visual sensors.
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This work was supported by JSPS KAKENHI Grant Number JP20K19793.
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Nagai, Y. et al. (2023). An Intelligent System for Optimization of Sensor Node Placement in Wireless Visual Sensor Networks: Performance Evaluation of CCM and CCM-Based SA Methods. In: Barolli, L. (eds) Advances in Networked-based Information Systems. NBiS 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 183. Springer, Cham. https://doi.org/10.1007/978-3-031-40978-3_12
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