N.Manjula, B. THARUN KUMAR, A. SUNNY BHARGAV, G. GANESH KARTHIKEYA, K.VAMSHI 03 3(1) Waste management has become a significant global concern as improper disposal methods pose serious risks to both the environment and public health Conventional waste sorting techniques are often laborintensive and inefficient highlighting the need for smarter and more effective solutions This study presents an AIbased garbage classification system integrated with IoT combining realtime IoTenabled sorting with deep learningdriven image classification The system utilizes a convolutional neural network CNN trained on diverse categories of waste to achieve high classification accuracy Once the waste is identified an IoTenabled actuator mechanism automatically segregates it reducing human effort and improving operational efficiency To ensure realtime performance and seamless integration with smart city systems the proposed solution is deployed on edge computing devices Experimental results demonstrate high accuracy in classification along with efficient waste segregation indicating the practicality of the system for largescale implementation This study highlights the transformative potential of combining AI and IoT in modern waste management contributing to a more sustainable and circular economy Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026