Abstract
The objective of this work is to present a comprehensive occupational health monitoring system which provides the current state of the occupational health for mine workers. The hearing threshold shift and dust exposure of each individual mine worker is monitored using this system. The data obtained from the system is transmitted via Internet of Things to storage which may be cloud or a server. The novelty of this model lies in its dual ability to monitor both Noise Induced Hearing Loss and Pneumoconiousis which is caused by inhalation of dust particles. The output of this dual system is further processed using Machine learning and artificial intelligence techniques. Recommendations are then provided to the mine worker with regards to their state of health. This system forms part of an early intervention system in the mines. The model was validated using real data from a Platinum mine in South Africa. Future improvement to this work would entail refinement of the current preliminary implementation plan and carrying out the first phase of the implementation.
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