The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Real-Time AIoT-Based Fatigue Detection System for Enhancing Worker Well-Being and Learning Efficiency
|
|
Author(s): Mengjia Long (Hong Kong Polytechnic University, Hong Kong), Ka Ni Lo (Hong Kong Polytechnic University, Hong Kong), Lin Peng (Hong Kong Polytechnic University, Hong Kong), Aquil Mirza Mohammed (Hong Kong Polytechnic University, Hong Kong)and Cong Wu (Liaoning Technical University, China)
Copyright: 2026
Pages: 30
Source title:
Intelligent Construction Monitoring Systems: Real-Time Safety, Environmental Prediction, and Risk Management
Source Author(s)/Editor(s): Aquil Mirza Mohammed (The Hong Kong Polytechnic University, Hong Kong)and Hewa Majeed Zangana (Duhok Polytechnic University, Iraq)
DOI: 10.4018/979-8-3373-9245-5.ch005
Purchase
|
Abstract
In today's fast-paced work environments, fatigue among workers can decrease productivity and health. To address this, we developed a real-time fatigue detection system using Artificial Intelligence of Things (AIoT). It integrates sensors—including cameras, simulated physiological sensors, environmental monitors, and logs—to assess workers' cognitive and physical states. Key indicators such as eye aspect ratio (EAR), head pose, and behaviors are extracted. A weighted fusion algorithm combines these to generate a fatigue score, triggering alerts when thresholds are exceeded. This non-intrusive system enables timely interventions, promoting well-being and productivity. Achieving 86% accuracy, it effectively monitors fatigue via vision, physiological, and behavioral data, offering personalized feedback. Ultimately, this AIoT solution shows great promise for improving worker health and efficiency.
Related Content
|
M. Vinayaka, B. Lokeshappa, Shanmukha N. T..
© 2026.
16 pages.
|
|
Kholis Kholis Ernawati.
© 2026.
32 pages.
|
|
Cristina Elena Turcu, Corneliu Octavian Turcu.
© 2026.
40 pages.
|
|
Muhammad Usman Tariq.
© 2026.
28 pages.
|
|
Gaganpreet Kaur, Amandeep Kaur, Ramandeep Sandhu.
© 2026.
22 pages.
|
|
C. V. Suresh Babu, V. Karunya Lydia, M. Jeevananthan, S. Sidharth.
© 2026.
26 pages.
|
|
Renu Mishra, Adarsh Tiwari, Sneha Sinha, Anmol Kr. Sah, Mamta Narwaria.
© 2026.
24 pages.
|
|
|