ITcon Vol. 29, pg. 894-913, http://www.itcon.org/2024/39

BIM-based framework for optimization of CCTV surveillance in buildings

DOI:10.36680/j.itcon.2024.039
submitted:April 2024
revised:August 2024
published:December 2024
editor(s):Obonyo E, Amor R
authors:Taha Aziz,
National University of Sciences and Technology
ORCID: https://orcid.org/0009-0004-3706-2640
taziz.bece19nice@student.nust.edu.pk

Muhammad Umer Zubair*, Assistant Professor, (corresponding author)
King Faisal University
mzubair@kfu.edu.sa

Muhammad Usman Hassan, Assistant Professor
National University of Sciences and Technology
usman.hassan@nice.nust.edu.pk

Mehmood Ahmed,
National University of Sciences and Technology
mahmed.bece19nice@student.nust.edu.pk

Muhammad Arsalan Khan, Assistant Professor
International Islamic University
arsalan.khan@iiu.edu.pk

Waqas Arshad Tanoli, Assistant Professor
King Faisal University
wtanoli@kfu.edu.sa
summary:Surveillance cameras are becoming an integral part of the buildings due to their ability to ensure security, as well as to promote safety and overall well-being. Finding the optimal camera configuration remains a challenge, as current practices depend heavily on professional experience and subjective judgment. These practices have several limitations which can adversely impact camera coverage. Building information modelling (BIM) usage is growing in the industry due to its ability to generate accurate spatial data. Therefore, this study proposes a BIM-based framework to optimize camera placement process using optimization algorithms (OAs). Firstly, the framework extracts spatial data of the target area from the BIM based on user defined requirements. Secondly, it adopts an optimization algorithm to find the optimal camera positions for the target area based on the user requirement. The selection of optimization algorithm was made following a comparative evaluation between Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Lastly, it helps visualize the optimized results within the building using BIM. The framework was validated on a hospital building, revealing 27% increase in coverage, a significant reduction in overlap, and a lower camera requirement compared to experience-based camera configuration.
keywords:Building information modeling (BIM), CCTV Network, Automation, Optimization of camera placement, Genetic Algorithm (GA), Particle Swarm Optimization (PSO)
full text: (PDF file, 1.228 MB)
citation:Aziz T, Zubair M U, Hassan M U, Ahmed M, Khan M A, Tanoli W A (2024). BIM-based framework for optimization of CCTV surveillance in buildings, ITcon Vol. 29, pg. 894-913, https://doi.org/10.36680/j.itcon.2024.039
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