Anti-Collision System for Accident Prevention in Underground Mines using Computer Vision

Mohamed Imam, Karim Baïna, Youness Tabii, I. Benzakour, Youssef Adlaoui, El Mostafa Ressami, E. Abdelwahed
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引用次数: 2

Abstract

Underground prospecting operations are often characterized by critical safety issues mainly due to poor visibility and blind spots around large vehicles and equipment. This can result in vehicle-to-vehicle collisions, as well as vehicle-to-pedestrian or structural-element collisions, resulting in accidents. In this article, we discuss an anti-collision system for pedestrian identification in deep mines under the premise that we are looking to prevent collisions with moving machinery. This study presents the findings from testing an image processing module and sensory system based on deep learnig in the context of "smart connected mine" project.
基于计算机视觉的地下矿山事故预防碰撞系统
地下勘探作业往往存在严重的安全问题,主要原因是大型车辆和设备周围的能见度差和盲点。这可能导致车辆与车辆的碰撞,以及车辆与行人或结构元件的碰撞,从而导致事故。在本文中,我们在寻找防止与移动机械碰撞的前提下,讨论了一种用于深井行人识别的防碰撞系统。本研究介绍了在“智能互联矿山”项目背景下,基于深度学习的图像处理模块和传感系统的测试结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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