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The growing number of fatalities among miners caused by toxic gases puts pressure on the mining industry; innovative approaches are required to improve underground miners' health. Toxic gases are very often released in underground mines and cannot easily be detected by human senses. This paper investigates the presence of the inherent types of toxic fumes in critical regions and their suspension and trends in the air and intends to generate knowledge that will assist in preventing miners from contracting diseases. The development of intelligent decision support systems is still in its infancy. Knowledge of how to make them profitable in improving miners' safety is largely lacking. An autonomous remote monitoring framework of wireless sensor networks, which integrates mobile sensing and Ohm's law, coupled with ambient intelligence governing decision-making for miners, is developed. The framework has been investigated in indoor scenarios and successfully deployed for real-life application in an aeronautic engine test cell environment, such as those typically found in underground mines. Useful demonstrations of the system were carried out to provide similar knowledge to safeguard engineers from the inhalation of toxic gases. This provides early warning for safety agents. The system has proven to be suitable for deployment in underground mines.
Isaac O. Osunmakinde (Fri,) studied this question.