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Smart city article details
| Title | Iot-Enabled Smart Waste Management System With Real-Time Gps Monitoring And User Notification |
|---|---|
| ID_Doc | 34088 |
| Authors | Vidyalakshmi R.; Surya M.K.; Kumar R.; Sabari S.; Harshan Prabhu A. |
| Year | 2025 |
| Published | Proceedings of 8th International Conference on Trends in Electronics and Informatics, ICOEI 2025 |
| DOI | http://dx.doi.org/10.1109/ICOEI65986.2025.11013255 |
| Abstract | In any urban setting, waste management needs to be efficient so as not to compromise its ecological sustainability. This is only possible with sophisticated automated systems that optimize collection while minimizing environmental impact. Incorporating real-time monitoring of trash levels, GPS tracking of vehicles, and automated alerts, this paper presents a Smart Trash Management System based on Internet of Things technologies which improves efficiency in waste collection. The system includes an ESP32 microcontroller, NEO-6M GPS, MQ-3 gas sensor, ultrasonic sensor, LCD, and buzzer to identify noxious environmental threats, measure ultrasonic distances, and track vehicles to determine gas concentration levels. AI cloud computing coupled with autonomous data capturing ensures the monitoring process is performed in the cloud, which enhances route planning, fuel efficiency, and operational effectiveness. Users, via a Flutter mobile application, can take geo-tagged photos to report overflowing and unsightly trash which mobilizes the authorities to act instantly. Fleet control with a web dashboard enhances decision making with automatic scheduling, real-time data monitoring, and fleet overview visualization. The proposed system integrates cheap computation and higher scalability with light IoT devices while ensuring precision in data tracking and transfer. The proposed systems optimize accuracy while making the data computing and tracking processes, particularly applying to cost-efficient light IoT devices, more scalable. The research conducted, through both real-life simulations and tests, proved effective in lowering the overall collection costs and improving garbage collection rates alongside response time. There are also plans to implement AI for trash sorting and blockchain technology for efficient monitoring within smart city frameworks. Maintaining a specific network may require constant attention, however, in terms of cost and scalability this analytical system facilitates city waste management, making urban areas not only more organized, but smarter as well. © 2025 IEEE. |
| Author Keywords | Cloud-Based Monitoring; Environmental Sustainability; Fleet Management; Geo-Tagged Alerts; IoT-Based Waste Management; Real-Time GPS Tracking; Smart City Solutions; Waste Collection Optimization |
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