This project uses deep learning and image processing techniques to automate waste sorting and disposal. The system comprises four dustbins that can classify waste into six different categories, including paper, plastic, glass, metal, organic, and others.
Technology Stack:
- Python
- Keras and TensorFlow for deep learning
- OpenCV for image processing
- Arduino for hardware control
- Servo motors, a camera, jumper wires, and breadboard for hardware components
Future Work:
- Improving the accuracy of the deep learning model by increasing the size and diversity of the training dataset.
- Enhancing the image processing module to handle different types of waste and environmental conditions.
- Optimizing the hardware control module to improve the speed and efficiency of waste sorting.