TrashIntel AI is a machine learning-based waste classification and reward system that encourages users to collect garbage and keep their surroundings clean. The project uses computer vision to classify dry and wet waste, and provides rewards to users for their efforts in collecting and disposing of garbage. Additionally, users can send their location to the admin/garbage collector to request garbage collection.
- Waste classification: The machine learning model can distinguish between dry and wet waste, which helps users know how to dispose of garbage properly.
- Reward system: Users receive rewards in the form of points as they collect garbage. Points can be redeemed for various incentives, such as discounts or coupons.
- Location-based garbage collection: Users can send their location to the admin/garbage collector to request garbage collection. This helps ensure that garbage is collected promptly and efficiently.
- User-friendly interface: The application has a simple and intuitive interface, making it easy for users to use and navigate.
- Machine learning: The waste classification model is built using TensorFlow and trained on a dataset of images of dry and wet waste.
- Android development: The application is built for Android devices using Java programming language and Android Studio.
- Firebase: The project uses Firebase Authentication for user authentication, Firebase Firestore for database management, and Firebase Cloud Messaging for push notifications.
To run the application locally, follow these steps:
- Clone the repository using
git clone https://github.com/MhaskeAditya42/TrashIntelAI.git. - Open the project in Android Studio.
- Set up a Firebase project and add the Firebase configuration files to the app (see Firebase documentation for details).
- Build and run the application on an Android device or emulator.
Contributions to the project are welcome! If you want to contribute, please create a pull request or contact us.
TrashIntel AI was developed by Aditya Mhaske , Mokshit Oswal , Aditya Nawale and Sumit Mulhar as a part of our academics. Special thanks to Prof. Ranjhana Jadhav and Vishwakarma Institute of Technology Pune for their support and contributions.
We hope this README helps potential users and contributors understand your project's features, technologies, and benefits. If you have any questions or need further assistance, feel free to contact us. Good luck with your project!