Machine learning for real-time stress analysis in IT team

In the swiftly moving tech industry, combating stress is important for IT pros under long hours, tight deadlines, and demanding expectations. Heart Rate, Skin Conductivity, Hours Worked, Number of Emails Sent, Meetings Attended etc. in this case this study is based on features used for predicting stress levels using machine learning. These markers provide insight into stress factors of physiological and occupational origin. Our proposed model aims to provide insight into their behavior for self-monitoring and intervention by players. By finding patterns in these phenotypic features, other data-driven methods can like these researchers take us a step closer to unlocking the time series of stress within the workplace.