Development of intelligent real-time monitoring systems for the mining sector**

对矿难和重大事故的回顾表明，在规划、控制和风险管理方面存在一系列失误。该行业正面临多个新的环境、安全、健康、社会和治理挑战，这些挑战将决定其建立合法性、发展可信度、赢得信任和创造价值的能力。需要的是通过实施先进的数据驱动技术获得运营洞察力。存在的问题是，采矿业没有表现出执行、监测和维持有效的关键控制措施以减少死亡和重大事故的能力或能力。因此，存在着解决这个问题的重大机会。这项由圭尔夫大学和安大略省多伦多的可持续风险战略(SRS)合作的研究项目旨在开发一个支持人工智能(AI)的数字风险管理平台。SRS将在连接和大数据领域进行创新，利用人工智能和机器学习从一线运营(人员和设备)中收集见解。圭尔夫大学团队将开发新的关键控制和机器学习技术，并将就相关工业项目对高素质人员(HQP)进行培训。

A review of mining fatalities and major incidents reveals a series of failures of planning, control and risk management. The industry is facing multiple new environmental, safety, health, social and governance challenges that will determine its capacity to establish legitimacy, develop credibility, earn trust, and create value. What is needed is operational insight through the implementation of advanced data-driven technology. The problem that exists is that the mining industry has not demonstrated its capability or capacity to implement, monitor, and maintain effective critical controls that mitigate fatalities and major incidents. Therefore, a significant opportunity exists to solve this problem. This collaborative research project between the University of Guelph and Sustainable Risk Strategies (SRS) in Toronto, Ontario aims to develop an artificial intelligence (AI)-enabled digital risk management platform. SRS will innovate in the space of connectivity and big data to gather insights from frontline operations (personnel and equipment) using AI and machine learning. New critical controls and machine learning techniques will be developed by the University of Guelph team, and highly qualified personnel (HQP) will be trained on a relevant industrial project.