AI & Chaos Theory-Powered EEG-Based Systems Predicting and Managing Worker Fatigue and Stress in the Mining Industry

This project focuses on developing a smart, wearable system powered by artificial intelligence (AI) and advanced brain signal analysis to help monitor worker fatigue and stress in the mining industry. Mining is a demanding job, and workers often face long hours and stressful conditions, increasing the risk of accidents. The system uses a small, non-invasive device to measure brain activity in real-time and detect early signs of fatigue or stress. The system can help prevent accidents, improve worker safety, and maintain productivity by alerting workers and supervisors to potential risks. This research not only addresses critical safety challenges in the mining sector but also provides the partner organization with innovative technology that can be applied to other high-risk industries. The results will have a lasting impact on workplace safety and health monitoring.

Faculty Supervisor:

Farid Golnaraghi

Student:

Partner:

DyMoTech

Discipline:

Engineering

Sector:

Mining; Professional, scientific and technical services

University:

Simon Fraser University

Program: