Smart automated noise policy monitoring and feedback control system for mining application

Abstract

Abstract This work develops an integrated smart noise monitoring model that can be used to monitor mine workers on site. The system provides mine administrators with the current state of hearing of the individual employee. The information obtained from the model can be used by the administration, for various purposes including monitoring and provision of early intervention. The main purpose of the model is to protect mining employees from experiencing significant hearing threshold shifts which can result in permanent hearing loss. The novelty of this model is the formulation of noise policy management model using feedback control with policies acting as actuators. Mining noise policies, Code of Practice and milestones are used in the selection of the appropriate controllers to be used in the system. Feedback is used in the system to compare the threshold output to the baseline. The output of the system is further processed using Internet of Things to ensure effective communication between the mine employees and the administrators. The model was validated using open source data from a real deep gold mine in South Africa. The results were generated using Matlab as a platform and were found to be comparable to the existing static model and more accurate. Future improvements to this work is to include artificial intelligence and machine learning concepts to the system to make it more robust.