Struck Prevention on Construction Sites with Wireless Technology and Machine Learning

Construction sites are prone to significant "struck-by" incidents involving interactions between workers and moving equipment. This paper presents StruckSafe, a look into novel systems that utilize Bluetooth Low Energy (BLE) and Radio Frequency Identification (RFID) technologies to enhance construction site safety. StruckSafe is designed to provide real-time tracking and proximity alerts to prevent accidents through BLE and RFID for dynamic proximity detection and efficient tracking and provide a comprehensive comparison between these 2 systems. Additionally, the system integrates Machine Learning (ML) algorithms for data analysis, which contribute to error reduction and improved accuracy. The final evaluation of the system demonstrated a Mean Absolute Error (MAE) of 3.2% for BLE proximity detection and 4.33% for RFID tracking. These results validate that StruckSafe effectively minimizes error and enhances safety on construction sites. By offering real-time collision warnings and leveraging advanced data analysis techniques, StruckSafe presents a promising approach to reduce injury rates, prevent accidents, and potentially save lives in the construction industry.