Abstract
Determining the optimal placement of CCTV cameras in industrial environments is a critical challenge, often complicated by complex layouts, varying operational requirements, and limited resources. This study applied the Simple Additive Weighting (SAW) method to evaluate and prioritize camera placement in four main zones: Production Process Zone, Product Storage Zone, Product Loading Zone, and Access Door/Perimeter. Three multi-criteria decision-making factors were considered: area coverage, installation cost, and operational efficiency of surveillance. The SAW method allows for structured and data-driven analysis, normalizing and weighting each criterion to calculate a final score for each zone. The results revealed that the Product Storage Zone achieved the highest priority score (0.99), followed by the Product Loading Zone (0.84), Access Door/Perimeter (0.77), and Production Process Zone (0.71). These priorities are not in line with the results of the security officer preference survey, but are in line with the opinions of CCTV experts and company managers according to the operational needs of the zones. These findings underscore the effectiveness of the SAW method in providing objective and transparent decision-making for CCTV placement. By integrating quantitative analysis into the design of surveillance systems, this approach optimizes resource allocation and enhances industrial safety. Future research is encouraged to explore the integration of SAW with advanced technologies, such as artificial intelligence and the Internet of Things (IoT), for dynamic and real-time surveillance solutions.
Keywords
Simple Additive Weighting