This paper explores the development and implementation of smart street lighting systems through the integration of Internet of Things (IoT) technology and fuzzy logic control. As urbanization accelerates, the demand for efficient and adaptive street lighting solutions becomes increasingly crucial for enhancing energy efficiency, reducing operational costs, and improving public safety. Traditional street lighting systems often operate without real-time adaptability, leading to energy wastage and suboptimal performance. By leveraging IoT sensors and networks, this research enables real-time data acquisition and communication between street lights and a central control system. Fuzzy logic algorithms are employed to process the data, allowing for dynamic adjustment of lighting intensity based on environmental conditions, traffic flow, and pedestrian activity. The integration of fuzzy logic provides a robust mechanism to handle the uncertainties and variabilities inherent in urban environments. Our prototype system demonstrates significant improvements in energy efficiency, with adaptive lighting adjustments reducing power consumption by up to 40% compared to conventional systems. Moreover, the enhanced responsiveness of the lighting system contributes to increased safety and comfort for urban residents. The findings underscore the potential of IoT and fuzzy logic integration in creating intelligent, sustainable, and user-centric urban infrastructure.

Smart Street Lighting, Internet of Things (IoT), Fuzzy Logic

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