Mohamed Imam, Karim Baïna, Youness Tabii, I. Benzakour, Youssef Adlaoui, El Mostafa Ressami, E. Abdelwahed
{"title":"基于计算机视觉的地下矿山事故预防碰撞系统","authors":"Mohamed Imam, Karim Baïna, Youness Tabii, I. Benzakour, Youssef Adlaoui, El Mostafa Ressami, E. Abdelwahed","doi":"10.1145/3571560.3571574","DOIUrl":null,"url":null,"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.","PeriodicalId":143909,"journal":{"name":"Proceedings of the 6th International Conference on Advances in Artificial Intelligence","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Anti-Collision System for Accident Prevention in Underground Mines using Computer Vision\",\"authors\":\"Mohamed Imam, Karim Baïna, Youness Tabii, I. Benzakour, Youssef Adlaoui, El Mostafa Ressami, E. Abdelwahed\",\"doi\":\"10.1145/3571560.3571574\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":143909,\"journal\":{\"name\":\"Proceedings of the 6th International Conference on Advances in Artificial Intelligence\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 6th International Conference on Advances in Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3571560.3571574\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Advances in Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3571560.3571574","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Anti-Collision System for Accident Prevention in Underground Mines using Computer Vision
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.