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: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=692092
• 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，心理和其他个体特征的影响。在压力大的采矿部门中，这一百分比要高得多，那里的工作很艰巨，而且通常很危险。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，矿业行业都会看到由于这些事件而导致的人类生命和宝贵的基础设施的巨大损失。 尽管仅雇用了全球劳动力的1％，但矿业行业仍造成全球与工作有关的死亡人数的8％（加拿大8.2％）。不幸的是，其中许多是可以预防的。尽管技术的进步和更严格的法规有助于减轻采矿事件，但数量仍然太高，尤其是当超过40万名工人大多来自偏远社区的工人受到采矿业的使用。以人为中心的方法来理解问题并改善问题矿工的福祉。 反过来，这将减少职业危害在采矿业的数量和影响。在该项目中，将开发一个全面的远程监控系统，以从矿工实时收集矿工的生物医学数据。该多传感器数据将融合，并将开发机器学习算法来分析和解释收集的数据。这将更好地理解矿工有效运作，环境因素，年龄，工作持续时间和其他生理状况的能力之间的相关性。结果将不仅用于确保矿工的长期和短期福祉，还将有助于减轻事故和提高生产率并优化矿山中的资源使用情况。这将与PBE Canada合作，这是矿山和隧道的通信和监测系统的全球领导者。