2022 IEEE International Students Conference on Electrical, Electronics and Computer Science
Title: Real-time mobile application for classifying solid waste material into recyclable and non-recyclable using Image Recognition and Convolutional Neural Networks.
Authors: Thumiki, Mayukha and Khandelwal, Aditi
Abstract:
Several applications of deep neural network have come into the limelight these days, one of them is the classification of solid waste material. Enormous amount of waste in generated in a highly populated country like India. A large portion of this can be recycled for further uses. Recyclable waste is separated in the treatment plants and sent to the recycling units or simply dumped into the water bodies or waste lands. This article provides a workable solution for categorizing waste into various categories at the gross root level. The methodology adopted for this project is Convolutional Neural Network clubbed with Image Recognition concepts. It was found that the accuracy improved notably after augmenting the input data. The proposed system when integrated with front end apps, can be used at community level to segregate domestic waste, which will contribute to the reduction of generation of unused waste material.