Waste Product Identification to assist EPR using Object Detection

With the increase in population, there has been a large increase in waste production. This has affected the environment and in turn have led to land pollution. To increase the recycling of products and increase the lifespan of raw materials, several countries of the world have implemented EPR policy. EPR requires collection of data related to the amount of non biodegradable waste generated by each company. With the recent technological advancements in machine vision, it has become possible to develop an infrastructure to easily collect such data in realtime using various object detection models like Yolo, SSD, RCNN and so on. This paper provides the details of a complete prototype that can help assist in the identification of non biodegradable waste products into their respective producers which can in turn help to implement the EPR policy and also elaborates on the model selection process for this application. The models that were used and compared in this paper includes CNN, Faster RCNN and Yolo v5