AquaGuard

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Inspiration

Seeing accounts of communities in developing countries drinking contaminated water since they lack access to testing laboratories or water treatment knowledge.

What it does

Artificial intelligence-powered platform that analyzes photos of water samples using Google Vision API to detect contamination, gives safety ratings, and gives do-it-yourself water treatment procedures using locally available materials.

How we built it

React + TypeScript frontend with Google Vision API for image analysis, Google Gemini AI for safety scores, interactive Mapbox maps for community water sources, and offline-capable PWA design.

Challenges we overcame

Finding a balance between the precision of AI analysis and cautious safety-first advice, crafting treatment guides that can function within resource-poor environments, and ensuring that the platform works offline in remote communities.

Accomplishments that we're proud of

Created image-based water quality analysis that detects contamination through color and clarity, detailed DIY filtering guides using locally available materials, and offline mode support for areas where the internet is not always available.

What we learned

Visual water analysis can be incredibly informative without lab equipment, communities need working low-cost solutions more than high-tech solutions, and accessibility necessitates offline-first design.

What's next for AquaGuard

Multi-lingual customer support for global communities, integrating into local NGOs and water safety departments, enhancing contaminant detection with machine learning, and co-operation to validate AI testing against lab analysis.

Built With

• canvas-api
• clean-water-access
• community-mapping
• framer-motion
• google-gemini-api
• google-vision-api
• image-recognition
• lucide-react
• mapbox-gl-js
• offline-pwa
• react
• react-map-gl
• react-router
• tailwind-css
• typescript
• un-sdg-6
• vite
• water-quality-analysis