Application of Anti-Collision Visual Detection Algorithm in Warehouse Management System Using Raspberry Pi - Hidayati, Qory; Sari, Danar Retno; Prastya, Muhammad Ramadhan (Faculty of Engineering, Universitas Tanjungpura, 2025)
Ensuring safety and efficiency at warehouse intersections has become increasingly vital in the era of automation and intelligent logistics. This study proposes a vision-based anti-collision traffic management system tailored to the dynamic warehouse environment. By combining YOLOv5 object detection with a real-time microcontroller-based actuation system, the system detects and prioritizes movement between forklifts and pedestrians. Four webcams positioned at warehouse intersections transmit visual data to a Raspberry Pi 4, which performs object detection and decision-making based on predefined priority rules. Actuation is executed via Arduino Uno and Nano for signaling