Key points are not available for this paper at this time.
The burgeoning demand for sustainable urban development necessitates innovative solutions in urban infrastructure, particularly in the realm of street lighting. This paper introduces a novel sensor-reduced smart street lighting system designed to optimize energy consumption while maintaining safety and comfort in urban environments. Unlike traditional systems that rely heavily on continuous sensor input, our proposed model utilizes a minimal sensor setup coupled with an intelligent algorithm that predicts lighting needs based on historical data and predictive analytics. This approach significantly reduces the system's complexity and cost, making sustainable technology more accessible to municipalities. Through a series of simulations and real-world trials, we demonstrate that our system can achieve up to a 40% reduction in energy usage compared to conventional sensor-based systems without compromising the illumination quality. This research not only highlights the potential of sensor-reduced technologies in urban lighting but also sets a precedent for future sustainable urban infrastructure projects.
Kumar et al. (Sun,) studied this question.