AI-Driven Spatial Adaptations Through Emotions: The case of emo-land as a human-centric approach

Abstract

The research on controlling and interacting with the environment has been accelerated by developments of artificial intelligence (AI) and the internet of things (IoT). While the quest for intelligence has been widely studied, spatial adaptation and human emotion relation remain ambiguous. This initial research attempts to investigate human-centric spatial adaptations through emotions in architecture. A case study called Emo-Land is designed to unfold the real-time relationship between space and emotion recognition. Emo-Land is an interactive spatial augmented reality installation that responds to the real-time emotions of the viewer via face expressions. A deep learning model developed to detect continuous emotions through cameras. By paying attention to the live interactive level of the detail and quality of the interaction between users and the projection mapping, the research demonstrates how advances in technology and computing can contribute to deeper connection and new layers of interactivity.Emo-Land projection mapping has been examined as a case study. According to the results, a relationship is developed between emotion recognition, form, computation, and human-computer interaction. The project contributes to the well-being of occupants, affective computing theory, and AI's role, such as the interaction between technology using affordable technologies.