Real time stress monitoring system for workers using IOT and Machine Learning

Real time stress monitoring system for workers using IOT and Machine Learning

Balaji.M, Beski.J, Chezhiyan.P, Gowdham.S

Balaji.m biomedical engineering and dhanalashmi Srinivasan engineering college

Beski.J biomedical engineering and dhanalashmi Srinivasan engineering college

Chezhiyan.P biomedical engineering and dhanalashmi Srinivasan engineering college

Gowdham.S biomedical engineering and dhanalashmi Srinivasan engineering college

Dr.D.KARTHIKEYAN, M.E.,Ph.D.

Hod of Biomedical Engineering Department , Dhanalakshmi Srinivasan Engineering college Perambalur

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Abstract

The work presents the design of a real-time stress estimation system using wearable sensors and machine learning techniques. Through ongoing sensing of physiological responses such as heart rate, skin conductance, and motion data, the system is able to estimate levels of stress in close to real time. A slim machine learning approach offers fast and effective processing in order for the system to be used in real time. Customers receive immediate alerts and stress-reducing advice specifically for them through a smartphone application. The technology also solves main pain points like noise in signals, delay, and data privacy. Its flexibility and accuracy allow it to be applied to many areas including health care, office wellness, and personal mental well-being assistance

Key Words:  Real-time stress prediction, worker stress monitoring, physiological sensors, machine learning, vibration therapy, workplace wellness, stress relief system.