Deep CNN Approach for a Circular Economy with Waste Recycling and Management in smart Cities

Abstract

Waste management encompasses all activities that are necessary from the generation of rubbish until it is ultimately disposed of. Academic studies investigating the potential of smart cities to solve environmental problems, especially waste management, are urgently needed. The findings of this study give light on potential ways in which linked communities and smart cities could bolster waste management efforts. An integrative literature review served as its foundation. There are primarily three steps to a model training operation: data preparation, feature selection, and model training. Data preparation can lead to erroneous data collection, which could cause systems in smart cities to malfunction.  The two primary parts of feature extraction are finding locations of interest and descriptions. On a regular basis, the proposed approach beats PSO and SVM, two top algorithms in the business. The data accuracy percentage of 98.04% is a significant improvement.