Solar-powered lamps, including lanterns and streetlights, are gaining popularity in India as a sustainable and cost-effective lighting solution, particularly in remote and rural areas. Many countries around the world are moving towards smart streetlights using IOT and replacing traditional streetlights with LED lamps to reduce energy consumption and carbon footprint. Integrating solar powered smart streetlights with features like dimming control to adjust light intensity based on time of day or traffic levels, saves energy and extends lamp life. Machine learning can optimize solar street light systems by predicting solar energy generation, improving energy efficiency, and enhancing lighting performance. This can be achieved through various techniques, including adaptive lighting control, energy consumption prediction. These characteristics enhance street lighting systems’ operation and efficiency while also promoting general urban sustainability and safety. The capability of controlling these lights from a distance, Intelligent solar streetlights are a terrific solution for smart city development and a useful asset for contemporary cities when paired with cutting-edge features and data collection. This paper aims to bring a novel approach to controlling the light intensity in smart streetlamps using technologies like IOT and ma- chine learning while supporting the broader global movement towards renewable energy and sustainability…