Optimising urban lighting efficiency with IoT and LoRaWAN integration in smart street lighting systems

Jabbar, Waheb A. and Keat, Tan Keng and Dael, Fares A. and Hong, Lee Chee and Yussof, Yusra Farhana M. and Nasir, Abdul (2025) Optimising urban lighting efficiency with IoT and LoRaWAN integration in smart street lighting systems. Discover Internet of Things, 5. ISSN 2730-7239

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Abstract

The integration of the Internet of Things (IoT) into smart city frameworks ushers in new opportunities for merging and enhancing diverse services, enabling seamless connectivity across multiple application domains. This paper presents the LoRaWAN-IoT-SSLS, an advanced automated streetlight control system that leverages IoT technology to achieve substantial energy savings and minimise the need for manual intervention. By employing LoRaWAN as the sensor network backbone, the system effectively addresses challenges related to long-range data transmission in IoT applications. The setup integrates a programmed Arduino board with PIR and LDR sensors, a GPS module, a LoRa shield, and a LoRaWAN gateway. The system is powered by a monocrystalline solar panel with a solar charger shield and battery and utilises LED lights for illumination. These components collectively enable automated switching and adaptive brightness control based on real-time environmental conditions, optimising energy use and enhancing safety. The system's performance was validated across distances up to 1000 m, maintaining stable operation with SNR values ranging from 9.8 to 1.5 dB and reliable RSSI levels, demonstrating robust communication and monitoring capabilities. Real-time status updates are visualised through the TagoIO platform, allowing for continuous remote management. The deployment of LoRaWAN-IoT-SSLS has the potential to significantly reduce electricity consumption and CO2 emissions by harnessing renewable energy resources. By activating lighting only when pedestrians or vehicles are detected and dimming or turning off when no presence is sensed, the system demonstrates superior performance over conventional models. This scalable and secure solution lays the groundwork for future innovations in smart urban infrastructure, setting new benchmarks for energy-efficient city lighting.

Item Type:	Article
Identification Number:	10.1007/s43926-025-00163-z
Dates:	Date Event 16 May 2025 Accepted 29 May 2025 Published Online
Uncontrolled Keywords:	LoRa/LoRaWAN, Lighting management, Smart street, Smart city, TTN/TagoIO
Subjects:	CAH10 - engineering and technology > CAH10-01 - engineering > CAH10-01-01 - engineering (non-specific)
Divisions:	Architecture, Built Environment, Computing and Engineering > Engineering
Depositing User:	Gemma Tonks
Date Deposited:	24 Feb 2026 09:49
Last Modified:	24 Feb 2026 09:49
URI:	https://www.open-access.bcu.ac.uk/id/eprint/16883

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