Individuals who work in the IT sector might be exposed to crisis-oriented jobs that are prolonged by long shifts, limited timeframes, and persistent problem-solving. Stress increases in these environments. Due to the nature of their work, IT practitioners have to spend a lot of time focused on a computer, which has previously been said to increase their stress and mental fatigue. If not managed properly, the stress mentioned above can escalate into serious adverse health consequences such as burnout, anxiety, depression, and other illnesses that can negatively impact performance and wellbeing. This study uses image processing and deep learning to assess IT professionals' stress. Monitoring an individual's mental state during prolonged computer use can reveal and reduce tension, improving IT workers' working conditions. This strategy aims to maximize employee performance during approved work periods by reducing tension and creating a supportive, dynamic environment. The study aims to create a reliable, easy, and accurate detection method. Through monitoring symptoms, the study seeks to understand employee stress levels, provide appropriate data, and properly predict stress levels.
