Research on Detection and Regulation of Adaptive Lighting Equipment Based on Computer Vision
ZHANG Qiang
ZHAO Shengtian
Abstract：In response to the issues of redundant energy consumption and experience imbalance caused by the single environmental perception dimension and static control strategies of traditional lighting equipment in complex scenarios,this paper proposes a computer vision-driven adaptive detection and dynamic control method for lighting devices.By constructing a multi-spectral fusion perception network and a spatiotemporal-semantics dual-stream analysis framework,key technologies such as high-reflection interference suppression and dense occlusion detection of devices are overcome;a constrained perception deep reinforcement learning algorithm is designed to achieve balanced optimization of energy efficiency and comfort.Experiments show that this method achieves an average detection accuracy of 92.7%,reduces system energy consumption by 31.5%in dynamic scenes while maintaining a visual comfort score of≥8.6.
Keywords：computer visionadaptive lightingequipment detection
Publication Date：2025-10-25
Online Publishing Date：2025-11-10(First online date of this platform, not the publication date of the document)
Pages：4( 42-44,66 )