The 'Auto-Trash' concept is a way to make waste disposal more efficient, which should be a priority for anyone interested in slowing the effects of climate change. Designed as a proof of concept for the TechCrunch Disrupt Hackathon, Auto-Trash is able to identify whether an object is recyclable or compostable and then place that item in the correct bin.
To make its assessment, the Auto-Trash machine uses a Raspeberry Pi computer that takes an image of the object placed on the can's rotating lid. An algorithm powered by Google's TensorFlow AI engine then judges what type of item the image is based on its machine learning tenets. If the item is recyclable, the lid tilts left and drops it in the recycling, and vice versa for the compost.
Trash-Sorting Concepts
The 'Auto-Trash' Sorts Between Compostables and Recyclables
Trend Themes
1. Efficient Waste Disposal - The 'Auto-Trash' concept improves waste disposal efficiency through automation and AI technology.
2. Climate Change Mitigation - Efficient waste sorting, like the 'Auto-Trash' concept, can contribute to slowing the effects of climate change.
3. AI-powered Recycling - Using AI and machine learning, the 'Auto-Trash' concept identifies recyclable items and places them in the correct bin.
Industry Implications
1. Waste Management - The 'Auto-Trash' concept has applications in the waste management industry, enabling more efficient sorting and disposal processes.
2. AI and Automation - The 'Auto-Trash' concept highlights the potential for AI and automation in improving recycling and waste management practices.
3. Environmental Technology - The 'Auto-Trash' concept represents innovation in environmental technology, offering a solution for more effective waste sorting and disposal.