Optimizing cctv placement for indoor building using genetic algorithm

Nor Azman, Muhammad Nabil Akif (2023) Optimizing cctv placement for indoor building using genetic algorithm. Project Report. Melaka, Malaysia, Universiti Teknikal Malaysia Melaka. (Submitted)

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Abstract

The placement of CCTV cameras in indoor buildings played a crucial role in ensuring effective security and surveillance. However, the previous system often suffered from inefficiencies, resulting in areas with blind spots and excessive camera usage, leading to increased costs and maintenance requirements. Hence, the project aimed to address these challenges by developing a genetic algorithm-based solution for optimizing the placement of CCTV cameras in indoor buildings. The proposed solution aimed to optimize camera placement using a genetic algorithm, taking into account factors such as coverage area, field of view, and the minimum number of cameras required. The system also provided evaluation and comparison functionalities to assess the improvements achieved compared to the previous methods. The expected outcome of the project was a genetic algorithm-based solution that optimized CCTV camera placement in indoor buildings, resulting in improved security and surveillance. The solution was validated using real-world examples, and recommendations for optimal camera placement were provided. The project’s significance lay in its contribution to efficient resource utilization, improved security, and the application of artificial intelligence techniques in solving real-world problems. Thus, a user-friendly interface was also provided to allow technicians and engineers to input data and view the optimized camera placement results.

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