Mental Health and Wellness Surveillance, Tracking and Assessment Solution among Children

This research focuses on developing a mental health surveillance and assessment solution tailored for children, addressing the rising concerns of mental disorders such as anxiety and depression. The project aims to provide a comprehensive tool for early detection and intervention by incorporating features like mood tracking, symptom logging, meditation exercises, sleep pattern monitoring, and mental health tests. Using an agile methodology, the solution leverages data analytics and machine learning to analyze trends, identify risk factors, and recommend personalized interventions. The platform also includes a secure parental oversight system, ensuring a safe environment for children while allowing guardians to monitor well-being through a dashboard displaying weekly and monthly reports. By integrating these features, the solution strives to enhance mental health support for children, offering tools that facilitate both self-care and parental involvement. The system’s real-time monitoring, coupled with machine learning-driven insights, aims to improve early diagnosis, thus contributing to better mental health outcomes for children.