MARATTO

article · Frontiers in Neuroscience

Development of an artificial intelligence based occupational noise induced hearing loss early warning system for mine workers

202413 citationsOpen accessUniversity of the Witwatersrand

Abstract

Preliminary results of the system show decision tree had the highest accuracy compared to the other algorithms used. It has an average testing accuracy of 91.25% and average training accuracy of 99.79%. The system also showed a good response level in terms of detection of noise input levels of exposure, transmission of the information to the data base and communication of recommendations to the miner. The developed system is still undergoing further refinements and testing prior to being tested in an actual mine.

Research topics

  • Noise Effects and Management
  • Hearing Loss and Rehabilitation
  • Gait Recognition and Analysis

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.3389/fnins.2024.1321357

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.