Dynamic time window based full-view coverage maximization in CSNs
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...
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Veröffentlicht in: | Journal of combinatorial optimization 2024-12, Vol.48 (5), Article 42 |
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Sprache: | eng |
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Zusammenfassung: | 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
π
], 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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ISSN: | 1382-6905 1573-2886 |
DOI: | 10.1007/s10878-024-01227-6 |