Optimizing Smart City Street Lighting: A Hybrid IoT-SAC Approach

Abstract

The confluence of artificial intelligence (AI) and the internet of things (IoT) is fast changing the concept of smart cities. Smart street lighting is only one example of the great opportunities this potent combination presents for enhancing urban infrastructure. While previous studies have looked into the possibility of combining IoT and Soft Actor-Critic (SAC) for this goal, this work takes a different tack. A simulated Internet of Things system that replicates real-world sensor data is used in our work. The SAC algorithm receives data from this system on variables like ambient light levels, weather, and vehicle and pedestrian traffic. The SAC algorithm modifies street light operation patterns and brightness dynamically within this controlled environment. This enables us to fine-tune the hybrid strategy so that it strikes a balance between user comfort and energy efficiency