Systematic Literature Review on Realtime Emotion Detection Using AI Approach

The integration of Artificial Intelligence (AI) in enhancing human business operations is an undeniable and transformative trend. This paper examines the research domain of real-time emotion detection (RED), which has seen a substantial boost in identification accuracy through advanced AI algorithms. The study involved a comprehensive survey of 202 papers, ultimately leading to the analysis of 13 key references that represent significant contributions to this field. The findings showcase the potential of RED to improve monitoring and engagement in various sectors such as security, education, healthcare, and human-machine interactions. Furthermore, the research underscores the critical role of face detection algorithms, which are essential for achieving high classification accuracy in emotion recognition tasks. Notably, Convolutional Neural Networks (CNNs) emerged as the most widely used and effective algorithm for classifying emotions, demonstrating their value in advancing the capabilities and applications of emotion detection technologies across multiple industries.