Solving 3D coverage problem using genetic algorithms in wireless camera-based sensor network modelling
Wireless camera sensor networks are used mostly in research today. However, the camera location in a space of study is a problem in maximizing the coverage of the camera. Instead of being a 2D computation, this computation is modeled in 3D projected to 2D walls. This research makes use of Genetic Al...
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oai:animorepository.dlsu.edu.ph:faculty_research-16462022-02-02T00:40:59Z Solving 3D coverage problem using genetic algorithms in wireless camera-based sensor network modelling Velasco, Neil Oliver M. Del Rosario, Jay Robert B. Bandala, Argel A. Wireless camera sensor networks are used mostly in research today. However, the camera location in a space of study is a problem in maximizing the coverage of the camera. Instead of being a 2D computation, this computation is modeled in 3D projected to 2D walls. This research makes use of Genetic Algorithms - a search optimization algorithm to find the best placement of camera which will yield to a maximum coverage ratio. The results of the experiment show the length of time the algorithm computed, and the obtained the least number of cameras needed for the most coverage.© 2019 IEEE. 2019-11-01T07:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/647 Faculty Research Work Animo Repository Genetic algorithms Wireless sensor networks Digital cameras Electrical and Electronics |
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Genetic algorithms Wireless sensor networks Digital cameras Electrical and Electronics Velasco, Neil Oliver M. Del Rosario, Jay Robert B. Bandala, Argel A. Solving 3D coverage problem using genetic algorithms in wireless camera-based sensor network modelling |
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Wireless camera sensor networks are used mostly in research today. However, the camera location in a space of study is a problem in maximizing the coverage of the camera. Instead of being a 2D computation, this computation is modeled in 3D projected to 2D walls. This research makes use of Genetic Algorithms - a search optimization algorithm to find the best placement of camera which will yield to a maximum coverage ratio. The results of the experiment show the length of time the algorithm computed, and the obtained the least number of cameras needed for the most coverage.© 2019 IEEE. |
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Velasco, Neil Oliver M. Del Rosario, Jay Robert B. Bandala, Argel A. |
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Velasco, Neil Oliver M. Del Rosario, Jay Robert B. Bandala, Argel A. |
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Velasco, Neil Oliver M. |
title |
Solving 3D coverage problem using genetic algorithms in wireless camera-based sensor network modelling |
title_short |
Solving 3D coverage problem using genetic algorithms in wireless camera-based sensor network modelling |
title_full |
Solving 3D coverage problem using genetic algorithms in wireless camera-based sensor network modelling |
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Solving 3D coverage problem using genetic algorithms in wireless camera-based sensor network modelling |
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Solving 3D coverage problem using genetic algorithms in wireless camera-based sensor network modelling |
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solving 3d coverage problem using genetic algorithms in wireless camera-based sensor network modelling |
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2019 |
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https://animorepository.dlsu.edu.ph/faculty_research/647 |
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