The Automated Waste Sorter addresses waste mismanagement in high-traffic school environments by combining embedded systems and machine learning. A Raspberry Pi, paired with a camera module, powers a custom image classification model trained on 10,000+ images to sort waste into trash, recycling, and compost bins with 96% accuracy. A rack-and-pinion carriage system ensures precise sorting, while a touchscreen interface provides real-time feedback. The Instasort mobile app, available on iOS and Android, extends functionality with 98% accurate waste classification via photo uploads, offering disposal guidance and environmental impact tracking. Deployed in six schools, including American High and Ardenwood Elementary, the system fosters sustainability through gamified features like intraschool competitions. Recognized by the Mayor of Fremont and reaching 34 million viewers, this user-centric solution optimizes accessibility and performance, inspiring sustainable change across communities.