Machine Learning Based Prototype Working Model to Determine Category of Garbage Waste Using Raspberry Pi

Abstract Existing waste management ecosystem includes various steps like collecting the waste material from different places and transporting it to a waste treatment plant for treatment and disposal of waste. In urban and rural areas, the most important and basic step of segregation of waste is not followed properly by majority of the people. There are multiple factors attached to this root cause. Lack of awareness is one of the main reasons behind it, i.e., sometimes people themselves are not sure which dustbin to put the waste in as they are not sure on the category of the waste. As a result, people just throw the waste in the dustbin without recognizing the purpose of the deployed dustbin which defeats the overall objective of the waste management system. To address this problem, we have prepared a prototype working model using Raspberry Pi that runs a machine learning model to determine the category of the waste material and displays it on a display so that the person can decide whether to throw the waste material into a wet waste dustbin or dry waste dustbin. This prototype is one of the novel initiatives which will help the society in many ways and can be deployed in residential areas, malls, industrial areas, schools, hospitals, etc. The developed model will help the society and make them aware about disposing the waste material in a correct dustbin.