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Title	Iot Enabled Intelligent Street Lighting System For Smart Cities
ID_Doc	33799
Authors	Karimeh A.S.; Chan K.-Y.; Lee C.-L.; Chung G.-C.; Pang W.-L.; Mitani S.M.
Year	2024
Published	2024 Multimedia University Engineering Conference, MECON 2024
DOI	http://dx.doi.org/10.1109/MECON62796.2024.10776428
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. © 2024 IEEE.
Author Keywords	Infrared sensor (IR); Light Dependent Resistor; Machine Learning; Object detection; Potholes; Smart Street Lighting System; The Internet of Things (IoT); YOLOv5

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