A Waste Management Technique to detect and separate Non-Biodegradable Waste using Machine Learning and YOLO algorithm

This research Paper proposes an application of Image Processing that works on the principle of machine learning and YOLO (You Only Look Once) algorithm was used to detect the custom object. The proposed application is a method to detect non-biodegradable waste from the bins so that the non-biodegradable waste can easily be separated from the bins. Data was divided into three major categories of non- biodegradable waste that were glass, metal and plastic. 450 -500 images of each category were collected in order to train the model. Each image was labelled using a labelling tool in the format of yolo. A machine learning model was created that was trained on the data set of all three categories of the images of non- biodegradable waste. After completion of training a number of files were obtained that were further used in testing model of the application. After completion of testing and checking the accuracy of the model on the webcam all the files were finally imported on the raspberry pi camera. Final testing was done on raspberry pi camera and results were verified accordingly and accuracy was calculated on the basis of the output received.