Research on the Interactive Model of Sensor Network in Environmental Responsive Art Design

This study explores the application of sensor network in environmental responsive art design and proposes an art interactive model based on particle swarm algorithm. The model captures environmental change information such as temperature, humidity, light intensity, etc. in real time through sensor network, and converts this information into input parameters for artistic expression to generate interactive artworks. In this study, an optimization scheme with particle swarm algorithm as the core is designed to dynamically adjust the expression form of artworks so that they can be adaptively adjusted as the environment changes. The system architecture includes functional modules such as data acquisition, environmental response analysis, environmental expression generation and feedback control. This paper compares the performance of multiple algorithms by systematically simulating the interactive effects under different environmental conditions. The simulation results show that the model based on particle swarm algorithm performs well in response speed, interactivity, and artistic expression, and can effectively improve the real-time and expressiveness of environmental responsive art design.