IoT Enabled Intelligent Street Lighting System for Smart Cities

Citation

Karimeh, Ali Salim and Chan, Kah Yoong and Lee, Chu Liang and Chung, Gwo Chin and Pang, Wai Leong and Mitani, Sufian Mousa (2024) IoT Enabled Intelligent Street Lighting System for Smart Cities. In: 2024 Multimedia University Engineering Conference (MECON), 23-25 July 2024, Cyberjaya, Malaysia.

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Abstract

The Internet of Things (IoT) has opened new possibilities for enhancing urban infrastructure, with a promising application being the IoT-enabled Smart Street Lighting System (SSLS). This system employs sensors, communication technologies, and data analytics to automate streetlight management, optimize energy use, and improve lighting quality. Optimal conditions are dynamically established in real-time by leveraging traffic, weather, and ambient light data to reduce energy consumption and bolster safety measures effectively. The paper delves into creating IoT Enabled Smart Street Lighting Systems (SSLS) components, examining both the advantages and hurdles associated with their implementation. In addition, an innovative IoT alert platform for road defect detection using computer vision is introduced, employing ESP32-CAM for pothole detection via Machine Learning and reporting to ThingsBoard, thus enhancing urban traffic safety and infrastructure management.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Internet of Things (IoT)
Subjects: Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 10 Feb 2025 03:12
Last Modified: 10 Feb 2025 03:12
URII: http://shdl.mmu.edu.my/id/eprint/13409

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