A MERN-Based Empathetic AI Framework for Holistic Health Management in Student-Centric Environments
Ashutosh Kumar1, Ishwari Jawale2, Sunil Kashyap3, Krishna Dwivedi4
1 B.tech CSE Student in MIT Art Design and Technology University, Pune, Maharashtra, India
kumar.ashutosh.er@gmail.com
2B.tech CSE Student in MIT Art Design and Technology University, Pune, Maharashtra, India
ishwarijawale01@gmail.com
3B.tech CSE Student in MIT Art Design and Technology University, Pune, Maharashtra, India
sunillkashhyap@gmail.com
4B.tech CSE Student in MIT Art Design and Technology University, Pune, Maharashtra, India
krishnadwivedi9579@gmail.com
Abstract: A comprehensive solution is required to create a student-friendly atmosphere to tackle physical, mental, as well as lifestyle-related issues. In this regard, the proposed study attempts to develop a comprehensive MERN Stack-based artificial intelligence framework that is based on empathy and is entirely dedicated to taking care of overall health. It incorporates diverse intelligent components, such as a medication interaction checker which provides suitable food along with medications, as well as a mental wellness platform which tracks emotional status on the basis of quizzes as well as everyday activity. A virtual herbal garden raises awareness among users about Ayurvedic recipes, which act as healthy substitutes to medication. In addition, it incorporates a personalized dietary assistant which changes food plans on the basis of users’ physical as well as mental wellness parameters, facilitating easy transition to healthy eating. Moreover, domain-specific artificial intelligence personalities like fitness experts as well as meditation mentors are implemented to generate domain-specific as well as context-specific knowledge. Additionally, it incorporates a digital journal writing assistant which is useful not just to reflect on one’s experiences but also to identify emotional patterns.
Keywords: Emotional ai healthcare, Empathetic artificial intelligence, Holistic wellness system, Natural language processing, Student health management
