Department of Energy Resources Engineering, Pukyong National University, Busan 48513, Republic of Korea.
Int J Environ Res Public Health. 2022 Dec 6;19(23):16312. doi: 10.3390/ijerph192316312.
Recently, collisions between equipment and workers occur frequently on the road in construction and surface mining sites. To prevent such accidents, we developed a smart helmet-based proximity warning system (PWS) that facilitates visual and tactile proximity warnings. In this system, a smart helmet comprising an Arduino Uno board and a camera module with built-in Wi-Fi was used to transmit images captured by the camera to a smartphone via Wi-Fi. When the image was analyzed through object detection and a heavy-duty truck or other vehicle was detected in an image, the smartphone transmitted a signal to the Arduino via Bluetooth and, when a signal was received, an LED strip with a three-color LED visually alerted the worker and the equipment operator. The performance of the system tested the recognition distance of the helmet according to the pixel size of the detected image in an outdoor environment. The proposed personal PWS can directly produce visual proximity warnings to both workers and operators enabling them to quickly identify and evacuate from dangerous situations.
最近,在建筑和露天采矿场的道路上,设备和工人之间经常发生碰撞。为了防止此类事故,我们开发了一种基于智能头盔的接近警告系统 (PWS),该系统可提供视觉和触觉接近警告。在该系统中,使用了一个由 Arduino Uno 板和带有内置 Wi-Fi 的摄像头模块组成的智能头盔,通过 Wi-Fi 将摄像头拍摄的图像传输到智能手机。当通过目标检测分析图像并在图像中检测到重型卡车或其他车辆时,智能手机通过蓝牙将信号传输到 Arduino,当接收到信号时,带有三色 LED 的 LED 灯带会向工人和设备操作员发出视觉警报。在户外环境中,根据检测到的图像的像素大小测试了头盔的识别距离,以检验系统性能。所提出的个人 PWS 可以直接向工人和操作员提供视觉接近警告,使他们能够快速识别并从危险情况中撤离。