Insights into the Emotion Classification of Artificial Intelligence: Evolution, Application, and Obstacles of Emotion Classification †

Abstract

In this systematic literature review, we examined the integration of emotional intelligence into artificial intelligence (AI) systems, focusing on advancements, challenges, and opportunities in emotion classification technologies. Accurate emotion recognition in AI holds immense potential in healthcare, the IoT, and education. However, challenges such as computational demands, limited dataset diversity, and real-time deployment complexity remain significant. In this review, we included research on emerging solutions like multimodal data processing, attention mechanisms, and real-time emotion tracking to address these issues. By overcoming these issues, AI systems enhance human–AI interactions and expand real-world applications. Recommendations for improving accuracy and scalability in emotion-aware AI are provided based on the review results.