Practice of human-computer interaction behavior recognition and experience optimization in intelligent tour guide equipment

With the widespread application of smart devices, smart guide equipment has become a core component of major museums, tourist attractions, exhibitions and other places. How to improve user experience through effective human-computer interaction behavior recognition and experience optimization has become an important topic in the development of smart guide equipment. Based on behavior recognition technology, this study explores how to capture and analyze user behavior to achieve personalized content recommendation and dynamic interactive feedback, and further optimize the user experience of smart guide equipment. The study proposes optimization strategies for multiple terminals and multiple scenarios, focusing on analyzing the differences in user behavior in different devices and environments and their impact on experience. Through case analysis, this study demonstrates the innovative application and optimization practice of smart guide equipment in actual applications, and proposes potential directions for future development. The innovation of the study is to combine behavior recognition and experience optimization methods to provide a comprehensive design framework, providing theoretical support for the continuous innovation and development of smart guide equipment.