Intelligent User Experience Design in Digital Media Art under Internet of Things Environment

Abstract

This paper discusses the cutting-edge methods of intelligent user experience design in digital media art, especially focusing on the fusion innovation of emotion perception, personalized recommendation and user interface design. Through biometric recognition techniques, especially heart rate variability (HRV) and skin conductance response (EDA) analysis, combined with deep learning models such as ResNet, Bi-LSTM and 1D-CNN, fine recognition of user emotions is achieved. Furthermore, an emotional response algorithm based on deep reinforcement learning is introduced, which dynamically adjusts the artwork to improve audience emotional satisfaction. In the aspect of recommendation system, through advanced feature fusion strategy and attention mechanism, the model enhances the understanding of user behavior sequence and static features, and optimizes the recommendation accuracy. The user interface design emphasizes simplicity, direct-viewing, personalized customization and efficient feedback mechanism to ensure the benign interaction between users and the system. The experimental evaluation part verified the effectiveness of the above methods through a series of carefully designed experiments, and the data showed that voice control, personalized recommendations, fast response, beautiful interface and efficient information delivery significantly improved the user experience.