Published March 14, 2026 | Version v1
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AI-Powered Smart Waste Management System

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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  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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Submitted
2026-03-14
Rapid urbanization and population growth have significantly increased the volume of municipal solid waste generated in cities around the world. Recent global estimates indicate that more than billion tonnes of solid waste 2 are produced annually, and this figure is expected to rise to approximately 3.4 billion tonnes by 2050 as urban populations continue to expand. Managing such a large amount of waste has become a major challenge for city administrations, particularly in densely populated regions where infrastructure and resources are often limited. Inefficient waste management practices can lead to serious environmental and public health issues, including air and water pollution, unpleasant living conditions, and the spread of diseases caused by decomposing waste and the presence of pests.

References

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