“Smart City Advanced Adaptive Street Lighting Systems” that aimed to build all hardware/software components of an adaptive urban smart lighting architecture that allows municipalities to manage and control public street lighting lamps. To save energy, the system can automatically modify the brightness of street lamps based on the presence of vehicles (buses/trucks, cars, motorbikes, and bikes) and/or pedestrians in specified locations or segments of the streets/roads of interest. The fundamental contribution of this research is to build a low-cost smart lighting system while also defining an IoT infrastructure in which each lighting pole is a component of a network that can improve the amplitude of the system. In a broader sense, the suggested smart infrastructure can be seen as the foundation for a larger technology architecture aiming at providing value-added services for sustainable cities. The smart architecture consists of a number of subsystems (local controllers, motion sensors, video cameras, and weather sensors) and electronic devices, each of which is responsible for performing certain tasks: Video processing for vehicle motion detection and classification, remote street segment lamp management, single street lamp brightness control, wireless and wired data exchanges, power consumptions analysis and traffic evaluation.