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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM25211
Volume:
7 |
8 |
Aug 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
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.
KEYWORDS
Publication Date
8/16/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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