AI赋能下的空间展示设计创新与用户体验优化研究OACHSSCD

To address the problems of excessive technical stacking,fragmented narratives,and mis-alignment with user needs in traditional spatial exhibition design,this paper constructs an AI-enabled theo-retical model for innovation in spatial exhibition design and optimization of user experience.With"techno-logy empowerment,user needs,and cultural translation"as its core elements,the model reconstructs the"human-object-space"relationship in exhibition environments through a closed technical loop of"algo-rithm-scenario-feedback".Integrating generative AI,multimodal interaction,affective computing,and other technologies,this study demonstrates three core mechanisms:First,leveraging AI's real-time data analysis and generative capabilities to achieve a shift from static viewing to personalized and dynamic narra-tive paths.Second,enhancing users' immersive experience from sensory attraction to behavioral partici-pation via multimodal interactions including voice,eye-tracking,and somatosensory input.Third,ensuring the accuracy and depth of digital translation of regional cultural symbols through human-AI collaboration supported by artificial intelligence and knowledge graphs.The findings show that the model effectively alle-viates pain points in traditional exhibitions such as low user engagement and distorted cultural expression.It promotes the development of exhibition design toward intelligence,personalization,and sustainability.