Assistive Mobile Application for Software Engineers in Sri Lanka to Support Depression 'Emoods'

This paper presents an Assistive mobile application in Sri Lanka to support depression. The framework uses face recognition technologies and algorithms to identify depressionprediction via machine learning for the users. The most effective means of improving the quality of Depression and mental illnesses at work is becoming increasingly widespread in the tech industry. Software developers, according to the International Journal of Social Sciences, have a far higher risk of depression, burnout, anxiety, and stress than their colleagueswho execute mechanical activities. Employees' mental health, as well as the company's total productivity, is threatened by declining mental health. Researchers from Stuttgart's Institute of Software Technologies discovered that developers who are emotionally exhausted or depressed generate lower-quality code and are more concerned about missing deadlines. The objective of this research is to determine the prevalence of depression among Sri Lankan software engineers. It is critical not to deal with depression on one's own. They require a system of loving individuals, such as family members, friends, coworkers, and neighbors, who enable them to be themselves. Building and maintaining a strong support system of people who can provide encouragement, help to keep moving and involved in meaningful activity, and help them challenge their negative thinking is a critical part of an assistive mobile app. This app provides features such as patient attention, patient awareness, treatment for patient depression levels, monitoring patient progress through time series analysis, collecting patientinformation via chatbot, and monitoring the improvement of doctor-patient relationships