The Museum That Feels: AI-Driven Affective Computing for Emotion-Adaptive AR Experiences

Abstract

This paper presents a conceptual and architectural framework that integrates Artificial Intelligence (AI), affective computing, and augmented reality (AR) to enable emotionadaptive cultural heritage experiences. Building upon advances in deep learning and human-AI interaction, the proposed system introduces a non-intrusive and ethically aligned approach capable of recognizing visitors’ affective states in real time and dynamically adapting digital narratives and immersive visualizations. The framework extends traditional personalization by embedding emotion recognition, context awareness, and adaptive reasoning directly into the cultural heritage experience, transforming static interpretation into an interactive, empathic dialogue between users and content.A comprehensive review of the state of the art situates this proposal within current research on smart museums, affective analytics, and AR-driven storytelling. The envisioned system architecture includes multimodal sensing, CNN-based emotion analysis, reinforcement-learning-based content adaptation, and AR rendering through mobile or head-mounted devices. Although conceptual, the framework outlines a roadmap for developing emotionally responsive and human-centered AI systems in cultural heritage environments. It contributes a structured model for future empirical validation and highlights the potential of AI to augment empathy, engagement, and inclusivity while adhering to principles of ethics, privacy, and open science.

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