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Smart Cities’ Automatic Image-Based Waste Segregation through an Intelligent Agent Using CNN
Joan Conag Vargas,Sheikh Babar Hameed,Taliah Tajammal,Gulzar Ahmad,Rahat H. Bokhari 한국차세대컴퓨팅학회 2022 한국차세대컴퓨팅학회 학술대회 Vol.2022 No.10
Rapidly growing innovative technologies enabled human beings to enjoy smart city services despite the development of such cities are still facing several challenges needed to be addressed. The waste management in smart cities particularly its segregation by smart methods is one of the primary concerns as the amount of waste generated every day by citizens is increasing. A comprehensive intelligent waste management system is direly needed to address the situation. This article aims to segregate recyclable and non-recyclable types of garbage collected from smart cities using the Intelligent Agent proposed and developed so far. The expected smart solution should provide the best level of accuracy at the lowest possible cost. Our study proposed a model to differentiate and segregate waste into recyclable and organic objects based on Intelligent Agent developed using a Convolutional Neural Network (CNN). The model proposed comprises of Intelligent Agent developed and the existing CNN model which is commonly used for transfer learning. The classification accuracy achieved is up to 93.27% which is better than the already published results of different models discussed in the recent past research studies. Furthermore, how can recyclable and organic waste be utilized in the future is part of our ongoing study. The findings may be of interest to practitioners and the researchers’ community working in the relevant field.