A Comprehensive Intelligent Monitoring System for Mines

矿山综合智能监控系统

• 批准号: 536337-2018
• 负责人: Fernando, Xavier
• 金额: $ 5.83万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=698335
• 关键词: Comprehensive; Intelligent; Monitoring; System; Mines

Every worker's health is influenced by biological, physical, psychological, and other individual traits. This percentage is much higher in the stressful mining sector where work is arduous and often dangerous. No surprise, this workplace fatigue is the primary reason for increased number of various accidents in the mining industry. Every year, the mining industry sees significant losses in terms of human lives and valuable infrastructure due to these incidents. Despite employing only 1% of the global workforce, the mining industry is responsible for approximately 8% of work-related fatalities worldwide (8.2% in Canada). Unfortunately, many of these are preventable. Although technological advancements and tighter regulations have helped in alleviating mining incidents, still the number is too high, especially when over 400,000 worker mostly from remote communities are employed by the mining industry. A human centric approach is necessary to understand the issues and to improve the well-being of miners. This in turn will reduce the number and the impact of occupational hazards in the mining industry. In this project, a comprehensive remote monitoring system will be developed to collect biomedical data from miners in addition to their location and environment data in real time. This multi-sensor data will be fused and Machine learning algorithms will be developed to analyze and interpret the collected data. This will create better understanding of the correlations among miners' ability to function efficiently, environmental factors, their age, work duration and other physiological conditions. The outcome will not only be used to ensure long- and short-term wellbeing of miners, it will also help to alleviate accidents and improve productivity and optimize resource usage in mines. This will be done in collaboration with PBE Canada, a global leader for communication and monitoring systems for mines and tunnels.

每个工人的健康都受到生物、身体、心理和其他个人特征的影响。在压力很大的采矿业，这个比例要高得多，因为那里的工作既辛苦又常常危险。毫不奇怪，这种工作场所疲劳是采矿业各种事故数量增加的主要原因。每年，采矿业都会因这些事件而遭受重大人员伤亡和宝贵的基础设施损失。 尽管采矿业仅雇佣了全球劳动力的 1%，但其造成的死亡人数却占全球约 8%（加拿大为 8.2%）。不幸的是，其中许多是可以预防的。尽管技术进步和更严格的监管有助于缓解采矿事故，但这一数字仍然过高，特别是超过 40 万名采矿业工人（大部分来自偏远社区）受雇于采矿业。 为了理解问题并改善矿工的福祉，必须采取以人为本的方法。 这反过来将减少采矿业职业危害的数量和影响。在该项目中，将开发一个全面的远程监控系统，除了实时收集矿工的位置和环境数据外，还可以收集矿工的生物医学数据。这些多传感器数据将被融合，并且将开发机器学习算法来分析和解释收集到的数据。这将有助于更好地了解矿工高效工作的能力、环境因素、年龄、工作时间和其他生理条件之间的相关性。其成果不仅将用于确保矿工的长期和短期福祉，还将有助于减少事故、提高生产力并优化矿山资源利用。这将与 PBE Canada 合作完成，PBE Canada 是矿山和隧道通信和监控系统的全球领导者。