Stress Detection in IT Employees Using CNN

Stress Detection in IT Employees Using CNN

Dr. Aravinda T V1, Poral Nagaraj2, Dr. Krishnareddy K R3, Ramesh B E4, Neelakantappa T T5, Suresh6

1Professor, Department of Computer Science and Engineering S.J.M.I.T. Chitradurga, Karnataka

2Associate Professor, Department of Computer Science and Engineering S.J.M.I.T. Chitradurga, Karnataka

3Professor, Department of Computer Science and Engineering S.J.M.I.T. Chitradurga, Karnataka

4Associate Professor, Department of Computer Science and Engineering S.J.M.I.T. Chitradurga, Karnataka

5Assistant Professor, Department of Computer Science and Engineering S.J.M.I.T. Chitradurga, Karnataka

6Student, IVth Sem Mtech, Department of Computer Science and Engineering S.J.M.I.T. Chitradurga, Karnataka

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Abstract - In contemporary society, Stress has emerged as a pervasive issue affecting a majority of individuals. Despite their material prosperity, people often find themselves dissatisfied due to pressures of stress. Stress is a difficult phenomenon that can manifest in emotional, physical, and mental forms. The objective of this project is to be identifying indicators of stress in IT professionals over the application of sophisticated image processing and machine learning methods. This technology represents an improvement over previous approaches for stress detection that didn't account for the subjective experiences of employees or real-time detection. The current model incorporates both periodic and live detection of employee emotions. Automated stress detection serves to mitigate health risks and enhance the well-being of both the IT Company and its employees. By understanding the emotional states of IT professionals, businesses can provide appropriate guidance and achieve better outcomes.

Key Words:  Stress, Machine learning and IT professionals.