Research ArticleNo Access

Design and simulation of AI remote terminal user identity recognition system based on reinforcement learning

Yan Chen

Information Engineering Institute, Yongzhou Vocational Technical College, Yongzhou 425100, P. R. China

https://doi.org/10.1142/S1793962323410052Cited by:3 (Source: Crossref)

Abstract

Presently, the design process of the AI remote server can enable the user to evaluate whether an authorized user can gain emotional responses when they establish an emotional product interface in the approach of the interaction with the device. Therefore, it is necessary for user experience and the ability to address the user’s emotional expectations. This paper proposes an artificial intelligence-based user face recognition response system (AI-UFRRS) to monitor users’ emotions in real life continually and provide new insights into their emotional responses and transitions. The user face recognition response system design is analyzed based on device intelligence. Eventually, the response system is improved and strategy based on an intelligent device. The proposed AI-UFRRS utilizes reinforcement learning technologies to maintain emotional processing in substantial information relating to the user’s identity. This paper offers AI remote strategies to reduce identification information and maximize information on emotions formed by reinforcement learning. The results suggest that the system provided can perform a convolute transformation to maintain user recognition accuracy and reduce face identity recognition. Thus, the experimental results of AI-UFRRS show the improved accuracy ratio of 95.6%, the recognition rate of 93.4%, emotion ratio of 95.5%, high response system ratio of 96.3%, and to increase user identification ratio of 91.8% and reduced false acceptance rate of 19.2%, the false rejection rate of 19.5% compared to other methods.

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