Sahaay - Healthcare Companion App

Sahaay is a comprehensive healthcare companion and Smart Health Surveillance & Early Warning platform. It simplifies medical management, supports community health reporting, and helps detect and prevent water-borne disease outbreaks in vulnerable communities.

Problem Statement (Smart Health Surveillance & Early Warning)

This project addresses the development of a Smart Health Surveillance and Early Warning System that can:

• Collect health data from local clinics, ASHA workers, and community volunteers via mobile apps or SMS.
• Use AI/ML models to detect patterns and predict potential outbreaks based on symptoms, water quality reports, and seasonal trends.
• Integrate with water testing kits or IoT sensors to monitor water source contamination (turbidity, pH, bacterial presence).
• Provide real-time alerts to district health officials and local governance bodies.
• Include a multilingual mobile interface for community reporting and awareness (including tribal languages).
• Offer dashboards for health departments to visualize hotspots, track interventions, and allocate resources.

How Sahaay Addresses This

Requirement	Sahaay Feature
Collect health data from community	Community posts, health records, family health, water quality reporting
AI/ML outbreak prediction	Outbreak risk engine (symptoms + water quality + area aggregation); AI report analysis
Water quality integration	Water Quality page: manual test kit reporting (turbidity, pH, bacterial presence)
Alerts for officials	Outbreak Risk dashboard with risk levels by area; Alert schema for future push/email
Multilingual / tribal languages	Language selection: English, Hindi, Assamese (NER)
Dashboards for health depts	Outbreak Risk page: hotspots, risk by area, symptom and water-fail counts

Key Features

• AI Medical Report Analysis: Upload medical PDFs to get detailed summaries, extracted vitals, and dietary recommendations using Google Gemini AI.
• Outbreak Risk & Surveillance: AI-driven early warning by area using symptom and water quality data (last 14 days).
• Water Quality Reporting: Submit and view water source test results (manual kits/sensors): turbidity, pH, bacterial presence.
• Nearby Care Finder: Locate hospitals, clinics, and pharmacies near you with an interactive map interface.
• Health & Vitals Monitoring: Track essential health metrics like Blood Pressure, Glucose, Heart Rate, and more.
• Family Health Management: Manage health records and appointments for family members in one place.
• Community Support: Join specific groups (e.g., Diabetes Support, Cardiac Care) to share experiences and get advice.
• Multilingual: English, Hindi, Assamese for community and tribal language support.
• Secure Authentication: Robust user authentication system using JWT.

Tech Stack

• Framework: Next.js 16 (App Router)
• Language: TypeScript
• Styling: Tailwind CSS
• Database: MongoDB (Mongoose)
• AI Integration: Google Gemini (via google-generative-ai SDK)
• Maps: Google Maps JavaScript API
• PDF Processing: pdf-parse, jspdf

Prerequisites

Before you begin, ensure you have the following installed:

• Node.js (v18 or higher recommended)
• MongoDB (local or Atlas)

Local development (recommended)

Run the app against a local MongoDB to avoid Atlas DNS/network issues (ENOTFOUND _mongodb._tcp.cluster0.mongodb.net).

1. Install and start MongoDB locally

   • macOS (Homebrew): brew tap mongodb/brew && brew install mongodb-community, then brew services start mongodb-community
   • Docker: docker run -d -p 27017:27017 --name mongodb mongo:latest
   • Or use MongoDB Community Server for your OS.

2. Use env from the app directory Next.js loads .env from the my-app directory (where next dev runs). So you need a .env inside my-app:

   • Copy the example: cp my-app/.env.example my-app/.env
   • If your .env is at the repo root, copy it to my-app/.env or create my-app/.env with at least DB_URL and JWT_SECRET.

3. Set the database URL for local MongoDB In my-app/.env set:

   DB_URL=mongodb://localhost:27017/sahaay
   JWT_SECRET=your_secure_jwt_secret_key

   Add GOOGLE_API_KEY and SMTP vars only if you need AI reports or email OTP.

4. Run the dev server from my-app

   cd my-app
   npm run dev

   Open http://localhost:3000 (or the port shown if 3000 is in use).

Installation & Setup (generic)

1. Clone the repository

   git clone <repository_url>
   cd Sahaay

2. Install Dependencies

   cd my-app
   npm install

3. Environment Configuration Create a .env file in the my-app directory (see my-app/.env.example). For local MongoDB use:

   DB_URL=mongodb://localhost:27017/sahaay
   JWT_SECRET=your_secure_jwt_secret_key

   For Atlas use DB_URL=mongodb+srv://<user>:<password>@cluster0.xxxxx.mongodb.net/sahaay. Optionally set GOOGLE_API_KEY, NEXT_PUBLIC_GOOGLE_API_KEY, and SMTP variables for AI and email.

4. Run the Development Server

   cd my-app
   npm run dev

   The application will be available at http://localhost:3000 (or another port if 3000 is busy).

Testing (BDD)

Sahaay uses Behavior-Driven Development (BDD) with Cucumber for the surveillance and water quality API tests. Feature files are written in Gherkin (Given/When/Then).

What’s tested	Location
Outbreak Risk API (all areas, by PIN, risk levels)	features/outbreak-risk.feature
Water Quality API (list, filter, submit, validation)	features/water-quality.feature
Step definitions	features/step_definitions/api.steps.js

Run BDD tests (dev server must be running):

1. Terminal 1 – start the app:

   cd my-app
   npm run dev

2. Terminal 2 – run the tests (default: http://localhost:3000):

   cd my-app
   npm run test:bdd

   If the app runs on another port (e.g. 3002), set the base URL:

   BASE_URL=http://localhost:3002 npm run test:bdd

Expected result: 7 scenarios (7 passed), 33 steps (33 passed).

This is a hackathon project by dineshkorukonda @pavankarthikgaraga @nithinkumark