| Issue |
EPJ Web Conf.
Volume 372, 2026
Advanced Power Systems (APS 2026)
|
|
|---|---|---|
| Article Number | 05007 | |
| Number of page(s) | 7 | |
| Section | Energy Policy, Markets and Education | |
| DOI | https://doi.org/10.1051/epjconf/202637205007 | |
| Published online | 11 June 2026 | |
https://doi.org/10.1051/epjconf/202637205007
IOT-based intelligent street system: Design and implementation of an educational prototype for smart urban infrastructure
Technical University of Cluj-Napoca, Faculty of Electrical Engineering, 400114 Cluj-Napoca, Romania
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 11 June 2026
Abstract
Rapid urbanisation and the proliferation of Internet of Things (IoT) devices are creating unprecedented demand for intelligent, energy-efficient urban infrastructure. Traditional street systems fixed- schedule lighting, static traffic signals, and periodic waste collection consume unnecessary energy and operational resources without adapting to real-time conditions. This paper presents the design and hardware implementation of an integrated smart street prototype consisting of three coordinated subsystems: an adaptive LED street lighting system driven by ambient-light and motion sensors, a sensor-based intelligent traffic management system with adaptive signal timing and an IoT-enabled waste container with fill-level monitoring and automated actuation. All subsystems are controlled by Arduino microcontrollers, and a centralised LabVIEW dashboard provides real-time monitoring of the entire system. Three-dimensional container components were designed in SolidWorks. The prototype was developed as a bachelor’s degree capstone project at the Technical University of Cluj-Napoca, demonstrating the educational value of integrating embedded programming, sensor fusion, energy analysis, and 3D design within a single engineering project. Results indicate measurable energy savings in lighting operation and logistics benefits from demand-driven waste collection scheduling.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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