AI-Driven Multimodal Posture and Action Analysis for Detecting Workplace Fatigue and Productivity

L. Anand, Ansh Nilesh Doshi, Sanskriti Kumari, Sunny Chaudhary

2025

Abstract

We all know how easy it is to lose focus when we’re tired, in many workplaces that can lead to mistakes or even accidents. To tackle this, we’ve built a smart, real-time system that helps spot early signs of fatigue before they become a problem. Using AI and computer vision, the system watches for subtle cues like frequent blinking, frequent head downs and shifted focus, common signals that someone might be getting drowsy Additionally, a screen activity detection feature ensures that users remain engaged in their work by monitoring active applications, mouse interactions, and screen content.It runs discreetly in the background with only a cheap webcam and open-source software, providing live feedback and cheery nudges when it’s time to take a break or get back on track. Our system is lightweight, easy to use, and is privacy respectful because it is always about movement patterns, not personal data. By fusing together physical and behavioural insights, this project is looking to be able to provide a safer, more productive environment that allows people to be at their best and healthy at the same time.

Paper Citation

in Harvard Style

Anand L., Doshi A., Kumari S. and Chaudhary S. (2025). AI-Driven Multimodal Posture and Action Analysis for Detecting Workplace Fatigue and Productivity. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 370-379. DOI: 10.5220/0013898300004919

in Bibtex Style

@conference{icrdicct`2525,
author={L. Anand and Ansh Doshi and Sanskriti Kumari and Sunny Chaudhary},
title={AI-Driven Multimodal Posture and Action Analysis for Detecting Workplace Fatigue and Productivity},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={370-379},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013898300004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - AI-Driven Multimodal Posture and Action Analysis for Detecting Workplace Fatigue and Productivity
SN - 978-989-758-777-1
AU - Anand L.
AU - Doshi A.
AU - Kumari S.
AU - Chaudhary S.
PY - 2025
SP - 370
EP - 379
DO - 10.5220/0013898300004919
PB - SciTePress