Stress Identification in it Employees Utilising Machine learning Methods

Abstract

The objective of this article is to utilize machine-learning and visual processing techniques to identify IT employees who are overworked. Our technology represents an enhanced iteration of previous stress prediction systems, which were deficientterm of human counselling and live detection. This research focuses on enhancing stress detection technologies that lack realtime monitoring and personalized therapy. Employee mental stress levels are evaluated through a survey, enabling the provision of effective stress management strategies. To optimize your workforce, peruse this article to discover methods of stress reduction and the creation of an enjoyable and relaxed work atmosphere.