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The project leverages the Arduino Uno microcontroller as the core processing unit, interfacing with the ESP8266 Wi-Fi module to enable remote communication and control. The LDR sensors detect ambient light levels, allowing the system to automatically dim or brighten the streetlights based on environmental conditions. Additionally, motion sensors can be incorporated to detect pedestrian or vehicle presence, ensuring that lights are only at full brightness when activity is detected nearby, further reducing energy usage when streets are empty. Data from the sensors is transmitted to a cloud-based platform via the ESP8266 module, where it can be accessed and analysed in real-time by city management systems or operators. This real-time data analysis enables predictive maintenance, alerting the system to potential faults or failures before they occur, thus minimizing downtime and repair costs. Moreover, by implementing a modular design, this system can be scaled to cover extensive urban areas, or adapted to different environments such as rural or residential settings. The IoT-based architecture also allows for easy integration with other smart city applications, potentially feeding data to broader municipal platforms for comprehensive urban analytics. Overall, this project supports green initiatives by minimizing energy consumption, reducing carbon emissions, and contributing to the creation of sustainable, intelligent urban infrastructure.