Adaptive matching optimization and VR system for indoor music performance based on wireless sensors

Abstract

With the continuous development of technology, music performances are gradually moving from the traditional stage format to the virtual reality (VR) environment to provide a more immersive experience for the audience. But traditional music performance lacks interaction and adaptability with the audience. This research aims to propose an adaptive matching optimization and VR system for indoor music performance based on wireless sensors to realize the interaction and self-adaptation between music performance and audience. The research uses wireless sensor networks to obtain audience behavior and feedback information, and matches it with music performance. By collecting physiological indicators such as the audience's movements, emotions and heartbeat, we can analyze and identify the audience's emotion and experience state in real time, so as to realize the adaptive music performance. The experimental results show that the adaptive music performance system based on wireless sensor successfully improves the audience's participation and emotional experience. The audience can interact with the musical performance through their movements and emotions, and feel a personalized musical experience that enables the audience to be more immersed and engaged.