Smart Street - An Artificial Intelligence (Ai) Powered Street Garbage Detection & Alert System

With the advancement of Artificial Intelligence (AI), traditional waste management systems can be transformed to provide real-time monitoring, enabling more efficient and cost-effective waste management. This research aims to develop a smart waste management system utilizing a TensorFlow based deep learning model for real-time object detection and waste classification. The proposed system incorporates a waste segregation bin with compartments for materials such as metal, plastic, and paper. Object detection and classification is implemented using TensorFlow’s pre-trained models, trained with a dataset of waste images to generate a frozen inference graph. The detection is performed through a camera for accurate waste classification. Additionally, a Machine Learning-based program is developed to classify images from CCTV cameras to identify clean and unclean streets. Trained on hundreds of labelled images, the model can Analyse new inputs and classify them accordingly. When unclean streets are detected, an automatic email alert is sent to the respective authorities, ensuring timely action. This innovative approach addresses the inefficiencies of traditional waste management systems, which operate on fixed schedules, and provides a scalable solution for real-time street cleanliness monitoring. Keywords: Smart Wast Management, AI Garbage Detection, Real-time Monitoring, Garbage Alert, Waste Detection, Real-time Alerts