JeevanRaksha was inspired by the lack of accessible, understandable, and organized healthcare services in rural and underserved communities, where people often struggle with medical awareness, language barriers, and delayed consultations. The platform combines multiple intelligent healthcare services into a single ecosystem, including ArogyaMitra, an AI-based symptom assistant that helps users identify whether their condition is mild or severe; Medilingo, an NLP-powered tool that simplifies complex medical reports into easy-to-understand summaries in multiple regional languages; a smart appointment booking system that allows patients to select doctors, departments, modes of consultation, dates, and time slots; and an admin-controlled dashboard where appointment requests can be approved or rejected to ensure organized service delivery. The system was built using HTML, CSS, and JavaScript for the frontend, Flask for the backend, MySQL for database management, and Hugging Face NLP models for AI functionality. Throughout development, we faced challenges in integrating AI models with the backend, managing real-time form behavior, handling multilingual support, and ensuring smooth communication between the frontend and database. Despite these challenges, we successfully developed a complete end-to-end healthcare solution that integrates AI with real-world medical workflows. This project helped us gain hands-on experience in full-stack development, AI integration, and building scalable systems, and in the future we plan to add real-time notifications, telemedicine features and doctor availability tracking to further strengthen JeevanRaksha as a digital healthcare backbone for rural India.

Share this project:

Updates