An Intelligent IoT Framework for Real-Time Waste Bin Level Monitoring and Collection Optimization

Authors

  • Emmy Danny Ajik Federal University Dutsinma
  • Joseph Nda Ndabula
  • Fagbemi Stephen Oluwatobi
  • Ali Bala Abdullahi

DOI:

https://doi.org/10.33003/fjs-2026-1014-5779

Keywords:

Internet of Things (IoT), Smart waste management, Ultrasonic sensor, Bin level monitoring, Real-time dashboard, ESP32 microcontroller

Abstract

The rapid increase in urban population and solid waste generation has intensified the need for efficient and intelligent waste management systems. Conventional waste collection methods rely on fixed schedules, often resulting in overflowing bins, environmental pollution, and inefficient resource utilization. This study presents the design and implementation of a Smart Bin Level Monitoring System based on Internet of Things (IoT) technology. The system utilizes an ultrasonic sensor mounted at the top of the waste bin to measure the distance between the sensor and the waste surface, thereby determining the bin’s fill level in real time. A microcontroller processes the sensor data and transmits it wirelessly to a remote server for online monitoring. The collected data is displayed on a dedicated web-based dashboard accessible at https://iot.net.ng/bin/dashboard.php, enabling authorized users to monitor bin status remotely. The system generates alerts when the bin reaches a predefined threshold, facilitating timely waste collection and optimized route planning. Experimental results indicate accurate level detection, reliable wireless transmission, and effective real-time visualization. The proposed solution enhances operational efficiency, reduces environmental hazards, and supports smart city waste management initiatives

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Smart Bin Monitoring records for Waste levels using Distance between the Ultrasonic Sensor and the waste

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Published

24-08-2026

How to Cite

Ajik, E. D., Ndabula, J. N., Oluwatobi, F. S., & Abdullahi, A. B. (2026). An Intelligent IoT Framework for Real-Time Waste Bin Level Monitoring and Collection Optimization. FUDMA Journal of Sciences, 10(14), 291-298. https://doi.org/10.33003/fjs-2026-1014-5779