Abstract
In order to maximize full-view coverage of moving targets in Camera Sensor Networks (CSNs), a novel method known as “group set cover” is presented in this research. Choosing the best camera angles and placements to accomplish full-view coverage of the moving targets is one of the main focuses of the research in CSNs. Discretize the target into multiple views of [0, 2\(\pi \)], use a set of views of targets to represent the sensing direction of the camera sensor, and use a group set of views of targets to represent the position of the camera sensor. The total number of targets in a dynamic time window that is visible in full view is calculated. A mixed integer linear programming formulation is employed, which is then approximated using a random rounding method. This approximation approach offers a global estimation of local optimality, particularly for non-submodular optimization problems. Two methods for maximizing overall full-view coverage within a dynamic time window are proposed TSC-FTC-DTW and FTC-TW-DTW. Finally, the proposed methods are verified through experiments.
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Acknowledgements
We are deeply grateful to the editor and the anonymous reviewers for their insightful and constructive feedback. Their suggestions have been instrumental in enhancing the clarity and rigor of our manuscript.
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This work is supported by the National Natural Science Foundation of China (No. 62172124), the Shenzhen Basic Research Program (Project No. JCYJ20190806 143011274), and the Shenzhen Science and Technology Program (Grant No. RCBS2021060910 3900003).
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Su, J., Li, Z., Du, H. et al. Dynamic time window based full-view coverage maximization in CSNs. J Comb Optim 48, 42 (2024). https://doi.org/10.1007/s10878-024-01227-6
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DOI: https://doi.org/10.1007/s10878-024-01227-6