Undip Student Designs AI System to Detect Worker Fatigue
JAKARTA – Tiaman Gea, a student of the D4 Mechanical Design Engineering programme at the Vocational School of Diponegoro University (Undip) in Semarang, Central Java, has created an innovation in the form of an artificial intelligence (AI)-based system for monitoring the physical and psychological condition of high-risk workers.
The innovation, named WellGuard, is designed to help detect physical fatigue and psychological risks among workers, particularly in the energy sector such as the oil and gas industry and mining.
According to Tiaman in Semarang on Tuesday, the scientific work, which won third place in the HSSE Innovation Challenge 2026, was developed to address the limitations of conventional occupational safety monitoring systems, which have tended to be reactive and carried out periodically.
The work is titled “WellGuard: Design of an Integrated System for Monitoring Physical Fatigue and Psychological Risks of Energy Industry Workers Based on Multimodal Artificial Intelligence, Biometric Wearables, and Natural Language Processing as an Effort to Improve Occupational Safety and Health”.
Tiaman said workers in the energy sector face working environments with high levels of risk. Beyond the dangers posed by machinery, equipment and environmental conditions, workers’ physical and psychological states can also affect safety levels.
“Work fatigue and psychological pressure can reduce workers’ situational awareness, which ultimately increases the risk of accidents,” he said.
WellGuard offers an integrated monitoring system by combining biometric wearable technology and artificial intelligence. The system is directed at monitoring workers’ physiological conditions whilst also reading indications of psychological risk more comprehensively.
Data from wearable devices can serve as one source for tracking changes in workers’ bodily conditions in real time. Meanwhile, the multimodal AI approach allows information from more than one type of data to be analysed simultaneously, producing a more thorough picture of a worker’s condition.
Tiaman also incorporated a natural language processing (NLP) approach into the WellGuard concept. The technology can be used to analyse language or text related to psychological conditions, so that mental aspects are not separated from physical monitoring.
“The transformation of occupational safety and health systems in the energy industry must move towards a predictive paradigm. Through WellGuard, we combine real-time physiological data and psychological sentiment analysis to break the cycle of physical-mental degradation that is prone to triggering workplace accidents in high-risk areas,” said Tiaman.
Fatigue is indeed a concern in energy industry worker safety. A study published in the journal Occupational Medicine in 2024, involving 67 offshore oil and gas rig workers in Indonesia, found that levels of acute and chronic fatigue increased significantly over a four-week work period. Workers’ capacity to recover between shifts also continued to decline.
The study noted that offshore rig workers can work 12-hour shifts every day for roughly four consecutive weeks. The researchers recommended more comprehensive fatigue management, as fatigue can contribute to human error and increase the risk of workplace accidents.