AI-DRIVEN HUMAN DETECTION AND GARBAGE SEGREGATION USING YOLOV11 FOR SMART CITIES

Abstract

This paper describes an AI-driven solution for human detection and garbage segregation in smart cities that makes use of YOLOv11. The model efficiently detects persons and categorizes waste as dry or moist, allowing for automatic sorting. The system improves garbage management procedures by utilizing deep learning and real-time object detection, decreasing manual effort and increasing urban cleanliness. High precision and recall scores reflect its ability to reliably distinguish waste types and human presence. This system promotes sustainable city development by optimizing waste disposal, encouraging recycling, and providing a cleaner environment through intelligent automation