Continuous Monitoring For Safety, Health And Optimisation In South African Deep Level Mining.

This paper describes the development of a monitoring architecture that allows for continuous monitoring of the process of mining, the underground environment, the state of the rockmass and its response to mining. The system is based on an open standard and is non-propriety. It allows for dense sensor arrays in the workplace, wire less communication to the closest power line, and TCP/IP communication to a central server. Continuous monitoring and quantification of the appropriate parameters allows a mine to optimise its mine process; to dynamically access the safety and health risk to people and equipment; and to quantify exposure to potential heath hazards such as dust, gas or noise. Current application examples of continuous monitoring include an application to optimise drilling and blasting thought fragmentation monitoring; an application of wireless sensor network-based monitoring in to provide early detection of potential rockfalls; and a trail to continuously assess the gold grade at the shaft through correlation with radioactivity. It is unlikely that a single monitored parameter will provide adequate knowledge of the assessed risk or even an optimisation approach. Multiple parameters are being combined using cognitive science tools such as Bayesian theory and other statistical methods to improve the accuracy and relevance of, for example, risk quantification. The decision maker is not confronted with massive amounts of raw data but rather with a single knowledge statement such a probability of failure, a human physiological strain index or an optimisation index.