With the construction of smart cities, the intelligent streetlight system has become an important part of modern urban management. However, the traditional scheduling method is difficult to dynamically adapt to complex traffic flow and environmental changes, leading to energy waste and low efficiency. This paper proposes a smart streetlight scheduling method based on fuzzy logic, which uses traffic flow and vehicle speed as input variables and achieves dynamic control of streetlight brightness and time through a fuzzy inference system and custom rules. Specifically, this paper designs fuzzy domains and membership functions for vehicle numbers and vehicle speeds, dividing them into five fuzzy subsets: VS (very few/very short), S (few/short), M (medium), L (many/long), and VL (many/very long). Based on the logic that "the longer the time and the more vehicles, the longer the time; the shorter the time and the fewer vehicles, the shorter the time," 25 fuzzy rules are formulated. The experimental results show that the method can dynamically adjust the brightness and time of streetlights based on real-time traffic conditions, achieving an energy-saving efficiency rate of 59% and ensuring traffic safety. This method has good extensibility and can provide reference for intelligent streetlight scheduling in complex traffic environments.

Songyang Li, Yaoyang Zhang, Bohan Li, Jianping Shuai. An Intelligent Street Lighting Scheduling Optimization Algorithm Based on Fuzzy Logic. Academic Journal of Computing & Information Science (2024), Vol. 7, Issue 12: 66-72. https://doi.org/10.25236/AJCIS.2024.071209.

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