Sahara is an AI-powered mobile application designed to provide accessible and personalized mental health support, particularly addressing barriers in under-resourced and stigmatized communities like Nepal. The app integrates AI-driven tools with human-centered care, enabling users to track their emotional well-being through daily journaling, mood and sleep tracking, and connections to certified counselors.
Developed as a major project for the Bachelor of Engineering in IT Engineering at Nepal College of Information Technology (affiliated with Pokhara University), Sahara uses a fine-tuned DistilBERT model for emotion classification. The frontend is built with React Native, while the backend leverages Express.js and Flask. Key integrations include a chatbot powered by Gemini, a secure payment gateway via eSewa, and video call sessions for counseling.
By combining scalable AI technologies with professional oversight, Sahara aims to revolutionize mental healthcare in Nepal, fostering inclusivity, affordability, and stigma-free access.
- Daily Journaling with Emotion Classification: Users can log daily entries, with AI (fine-tuned DistilBERT) analyzing text to classify emotions and provide mood insights.
- Mood and Sleep Tracking: Tools to monitor emotional well-being and sleep patterns over time.
- Counselor Booking System: Search, book, and schedule sessions with certified counselors, including real-time video calls.
- Feedback and Rating System: Users can rate counselors and provide feedback to ensure quality.
- Secure Payment Gateway: Integrated with eSewa for affordable, secure transactions.
- AI Chatbot: Powered by Gemini for instant, conversational mental health support.
- Users: Journaling, Sleep tracking, booking sessions, chatbot interaction.
- Counselors: Manage availability, accept bookings, conduct sessions.
- Admins: Onboard certified counselors, monitor platform activities.
| Category | Technologies/Tools |
|---|---|
| Frontend | React Native |
| Backend | Node.js, Express.js, Python, Flask |
| Database | MongoDB with Mongoose |
| AI/ML | DistilBERT (fine-tuned for emotion classification), Gemini (for chatbot) |
| Testing/Dev | Postman, VSCode, Figma (for UI design), Git & GitHub |
| Others | LaTeX (for documentation), eSewa (payment gateway) |
The project follows an Incremental Software Development Life Cycle (SDLC), with iterations focusing first on core features like journaling and emotion detection, followed by advanced integrations like video sessions and secure payments.
- Sign up/login
- Add daily journals for emotion analysis
- Track sleep and mood
- Browse and book counselors
- Join video sessions
- Interact with the chatbot
- Register (via admin )
- Set availability
- Manage bookings
- Conduct sessions
- Onboard certified counselors
- Oversee user/counselor management through the dashboard