Inspiration

Living in Delhi, I saw daily traffic and parking chaos. Inspired by smart city initiatives like Singapore’s, I created ParkRight Delhi to reduce congestion and improve parking compliance using AI, real-time maps, and citizen engagement.

What I Learned

Mastered React, Node.js, and MongoDB for full-stack development. Learned Leaflet.js for OpenStreetMap integration and geospatial data handling. Gained insights into TensorFlow.js for AI-based violation detection. Understood real-time systems and user-centric design for dual interfaces.

How I Built It

Frontend: React with Tailwind CSS and Leaflet.js for maps. Backend: Node.js with Express, MongoDB for data storage. AI: Placeholder TensorFlow.js model to simulate violation detection. Features: Real-time parking, congestion heatmaps, citizen reporting with rewards, rule awareness, live alerts, and an authority dashboard. Process: Built APIs, integrated maps, mocked data, and tested locally.

Challenges Faced

Handling geospatial data with Leaflet.js and MongoDB. Simulating AI without real traffic camera data. Balancing simple citizen UI with detailed authority dashboard. Implementing real-time updates without WebSockets. Planning for scalability and security in production.

Built With

and-citizen-reports).-apis:-openstreetmap-via-leaflet.js-(for-interactive-maps-and-heatmaps).-browser-geolocation-api-(for-user-location-tracking).-custom-rest-apis-(built-with-express-for-parking
api
but-aws-or-heroku-recommended-for-production-deployment.-databases:-mongodb-(for-storing-parking-spots
congestion
congestion-data
css.-frameworks:-react-(frontend-for-dynamic-ui).-node.js-with-express-(backend-for-restful-apis).-tailwind-css-(styling-for-responsive-design).-platforms:-web-based-application
designed-to-be-extensible-to-mobile-with-react-native.-cloud-services:-none-in-the-prototype
for-parkright-delhi
html
i-used-the-following-technologies:-languages:-javascript-(for-frontend-and-backend)
jsx
transpilation