Year: 2025
Type: article
Abstract: Waste management is a major issue worldwide as inappropriate disposal puts the environment and public health at risk. Innovative solutions are required since traditional garbage sorting processes are labour-intensive and inefficient. This study introduces an AI-powered garbage Classification System with Iot, combining real-time Iot-enabled sorting processes with deep learning-based picture classification. To accomplish high-accuracy classification, the system uses a convolutional neural network (CNN) that has been trained on several trash types. An Iot-enabled actuator system is then used to autonomously sort the categorised garbage, decreasing the need for human involvement and increasing operational effectiveness. To guarantee real-time processing and smooth interaction with smart city infrastructure, the suggested approach is implemented on edge devices. High classification accuracy and effective waste segregation are demonstrated by experimental findings, indicating that this strategy is feasible for widespread use. This study demonstrates how AI and IoT have the potential to transform waste management systems and support a circular and sustainable economy.
Authors: Avi Dedania, Mr. Dhruv Panchal, Asst. Prof. Janki Patel, Ms Jayati Jani
Language: English
Subfield: Waste Management and Disposal
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409573129