Hritik Chaudhary

https://doi.org/10.64823/ijter.2604031

The rapid growth of academic and workplace stress has significantly increased mental health concerns among students and professionals. Traditional therapeutic models lack real-time monitoring, personalization, and scalable accessibility. Existing digital platforms often provide static recommendations without integrating structured mood analytics, secure data management, and intelligent conversational assistance. This paper presents RELieF, a MERN stack-based AI powered mental health monitoring and emotional support system. The proposed framework integrates daily mood tracking, graphical analytics, conversational AI assistance, and gamification mechanisms within a secure and scalable web architecture. The frontend is developed using React.js, while the backend employs Node.js and Express.js with MongoDB Atlas for cloud-based data storage. JWT-based authentication ensures secure access and data privacy. Experimental evaluation conducted on structured test cases demonstrates consistent performance with an overall accuracy of 93.33%, high engagement consistency, and effective visualization of emotional patterns. The proposed system provides a modular, scalable, and user-centric approach toward digital mental wellness.