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Urban growth and population surges strain traditional waste management, causing bin overflows, spills, odors, pollution, and health risks from manual checks and fixed schedules. This study presents a camera-free AI-IoT system for real-time garbage and spill detection using edge sensors: ultrasonic/IR/weight/gas in smart bins and moisture/conductivity units in high-risk areas like hallways, restrooms, and wards—all geo-tagged via GPS. Data streams via Wi-Fi/LoRaWAN/GSM to a cloud platform, where ML identifies anomalies, predicts overflows, optimizes routes, and alerts nearby staff. An admin dashboard enables live monitoring, task management, analytics, and predictive maintenance, delivering a scalable solution for cities, campuses, hospitals, and transit hubs that cuts costs, boosts hygiene, reduces labor, preserves privacy, and supports sustainable urban environments.
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