Abstract: Ensuring the safety of workers in dangerous areas is an important issue at construction sites. In particular, fatal accidents at construction sites often involve falls or traffic accidents, and tend to occur around hazardous areas. In this paper, to prevent such accidents, a proximity detection and warning system based on image recognition and Bluetooth Low Energy (BLE) technology is proposed. This system mainly uses image recognition to detect workers approaching dangerous areas, and uses BLE beacons as an auxiliary to achieve continuous detection even under occlusion conditions. A master-slave operation model is adopted, with image recognition serving as the main detection method and BLE beacons as an auxiliary. When a worker approaches a dangerous area, a real-time warning is issued via a wireless earphone connected to a smartphone, allowing immediate recognition and response. This has made it possible to reach the stage of detecting intrusion into dangerous areas. However, there are still some challenges remaining for this system. The first challenge is individual re-identification. In order to issue a warning to the relevant worker when an intrusion into a dangerous area is detected, the worker needs to be recognized individually. The second challenge is adapting to changes in the structure of the construction site. Since the environment of a construction site changes over time, it is necessary to consider the appropriate placement of cameras. Experiments show that the proposed method works well to locate workers approaching and entering dangerous areas. The proposed system also detects intrusion into dangerous areas through bone conduction wireless earphones from a distance of 115 meters and issues a warning to the corresponding workers.

Yuya Ifuku, Kohei Arai and Mariko Oda, “Approach Detection and Warning Using BLE and Image Recognition at Construction Sites” International Journal of Advanced Computer Science and Applications(IJACSA), 16(4), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160409

@article{Ifuku2025,
title = {Approach Detection and Warning Using BLE and Image Recognition at Construction Sites},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160409},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160409},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {4},
author = {Yuya Ifuku and Kohei Arai and Mariko Oda}
}