Object Detection-Based Security Monitoring System in The Framework of Architectural and Structural Design Optimization

Rats are one of the main pests that cause significant damage to grain during storage in warehouses. Rat activities such as gnawing on sacks, contaminating grain, and damaging storage structures can drastically reduce the quality and quantity of grain. Conventional security systems, such as passive CCTV, are unable to provide automatic notifications or real-time threat identification. This study aims to design and develop a warehouse security system based on Object Detection using the YOLO algorithm to automatically detect the presence of rats. This system is integrated with environmental sensors to monitor the temperature, grain humidity, room humidity, and light intensity in real-time to support optimal storage conditions. The implementation of YOLO in the system is expected to provide a high level of accuracy in detecting rats, so that warnings can be given quickly to warehouse operators. Thus, this system has the potential to minimize the risk of grain damage, increase the effectiveness of warehouse surveillance, and support more modern and efficient security management.