Automatic street light brightness optimization using iot

Rapid urbanization and the increasing demand for energy-efficient infrastructure necessitate innovative solutions for public lighting systems. This project presents an IoT-based smart street lighting system designed to optimize brightness based on environmental and contextual conditions across diverse locations such as railway stations, rural areas, and urban smart cities. The system integrates multiple sensors, including flood detection and air pollution monitoring modules, to dynamically adjust light intensity, enhance safety, and conserve energy. The use of the Blynk IoT platform enables real-time data visualization and remote control, facilitating responsive maintenance and decision-making. The prototypedemonstrates significant potential for reducing power consumption and environmental impact while improving public infrastructure reliability and adaptability. This approach contributes toward sustainable urban development and disaster preparedness through smart technology integration.