Automated Object Detection and Tracking for Construction Site Safety

The construction industry is increasingly adopting digital solutions to enhance safety, efficiency, and productivity. This project leverages the YOLOv8 object detection model and ByteTrack algorithm to track and count objects on construction sites. The system enables automated monitoring of personnel, machinery, and safety equipment through video analysis, addressing critical challenges like occlusions and dynamic object interactions. A custom dataset tailored for construction environments ensures high accuracy in detecting safety-critical items, such as personal protective equipment (PPE). This approach demonstrates significant potential for real-time safety assessments and operational optimization, serving as a technological leap in construction practices.