Title: A dynamic interactive system for intelligent lighting art installations based on multimodal sensing

Authors: Tingshuo Yan; Yan Chen; Shenjian Hu; Wei Deng

Addresses: School of Architecture and Fine Art, Dalian University of Technology, Dalian, 116001, China ' School of Architecture and Fine Art, Dalian University of Technology, Dalian, 116001, China ' School of Architecture and Fine Art, Dalian University of Technology, Dalian, 116001, China ' School of Architecture and Fine Art, Dalian University of Technology, Dalian, 116001, China

Abstract: To address the problem of incomplete effective feature information extraction in the interaction methods of intelligent lighting art installations, this paper first collects data such as light intensity and user behaviour through multimodal sensors. Then, multimodal sensor signals are mapped to a two-dimensional image space, and a lighting perception network is used to evaluate lighting conditions and obtain lighting probabilities. By comprehensively representing shallow and deep features for information measurement and assigning adaptive weights, the beneficial information of the fusion method is maximally preserved. Finally, positive and negative feedback are set based on user behaviour to train the reinforcement learning model, enabling it to adapt to the user's dynamic interaction habits gradually. Simulation results show that the control accuracy of the proposed method is 95.39%, the system interaction response time is 13.6 ms, and it can effectively improve the control accuracy and real-time performance of the interaction system.

Keywords: intelligent lighting art installation; dynamic interaction; multimodal sensing fusion; lighting perception; reinforcement learning.

DOI: 10.1504/IJSNET.2025.149898

International Journal of Sensor Networks, 2025 Vol.49 No.3, pp.195 - 208

Received: 27 Aug 2025
Accepted: 29 Aug 2025
Published online: 17 Nov 2025 *

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