EcoGo was inspired by the urgent need to make our communities aware of the environmental issues we face, in a tangible and impactful way. By converting air quality data into the equivalent number of cigarettes smoked, we provide a stark visualization of pollution levels, encouraging people to take action against air pollution.
EcoGo incentivizes users to reduce their carbon footprints by offering a heatmap of pollution, organizing events for climate action, suggesting eco-friendly routes, and promoting sustainable choices through a leaderboard. The app also helps users find eco-friendly restaurants, shopping locations, and informs them about community initiatives tackling climate change.
Built during a 24-hour hackathon with sustainability as the cornerstone, EcoGo was developed using Google Cloud Platform (GCP) services, Firebase for authentication, Google Maps for mapping and geocoding, Firestore for real-time data, and React Native for a cross-platform mobile experience.
We encountered hurdles with real-time pollution data updates, precise geocoding for events, seamless integration of multiple Google APIs, and the steep learning curve of React Native within the tight hackathon deadline.
Our proudest achievement is the MVP which combines a pollution heatmap, an event system, and a user engagement leaderboard. The integration of multiple Google APIs showcases our app's robustness and our commitment to using technology for environmental advocacy.
This project was a deep dive into how various Google services can be combined to create a powerful tool to promote sustainable living. It also highlighted the importance of user engagement in environmental apps.
We aim to refine EcoGo, adding more interactive elements like location-based pollution alerts, akin to Pokemon Go. We're also planning to integrate more backend features, enhance the user interface, and implement a dynamic description of locations using Google's API.
- React Native
- Expo
- TypeScript
- Firebase
- GCP
- Google Maps (including Directions, Geocoding, Places, and Prediction APIs)