Sorting waste into the right categories, like plastic, glass, metal, or paper, is not as simple as it sounds. To make this tiresome job easier, researchers have developed a smart waste classification system that uses artificial intelligence to recognize different types of trash, making waste management easier and more efficient.
A team of researchers from the Ronin Institute (USA), Asia University (Taiwan), Symbiosis International University (India), and Chandigarh University (India) collaborated on this project, bringing together experts from computer engineering, medical research, and data science to tackle the waste management challenge.
These researchers trained a computer model to recognize different types of waste, like cardboard, glass, metal, paper, plastic, and general garbage, just by looking at a photo. With the help of thousands of images, they taught the system to recognize images and classify them. This is done by deep learning and machine learning techniques.
A tool called VGG16 helps the model break down images into features like textures and patterns, while the Random Forest algorithm sorts the trash into the right category, like cardboard or metal, for example. To fine-tune accuracy, they even used an optimization method called Cat Swarm Optimization (CSO) inspired by the way cats track and search for things.
The system can sort waste correctly about 85% of the time, which is a big step toward smarter and more efficient waste management. AI-powered waste sorting is still evolving, but it won’t be long before it becomes a part of our daily lives. With more upgrades, it could take over the messy job of sorting trash by hand, making waste management easy and hassle-free.
