Smart Waste Classifier

Context: Recycling can be tricky – what if a machine could help by sorting trash for us? Create a Smart Waste Classifier that can tell recyclable and non-recyclable items apart using AI vision.

Task: Collect images (or use a pre-trained model) for two categories: e.g., paper vs plastic, or recyclable vs general waste. Use an image recognition tool to train a simple model. Set up your Junkbot Core with two output indicators or sections of a bin. When an item is shown to the camera, have the AI classify it. Program the Junkbot Core to respond: for example, if “recyclable” is detected, a green LED lights and a servo could direct the item towards a recycle bin section; if “non-recyclable,” a red LED lights and directs to a different section. Expected Output: A prototype sorting station. In a demo, showing a paper item to the camera might cause the device to say “Recycle” (green light) and move a small flap (servo) toward a recycle bin label. Showing a piece of general trash results in a “Trash” indication (red light) and the flap moving the other way. Though small in scale, this models how AI-powered recycling centers might sort materials automatically to help the environment