Emotion-Aware Smart Home Automation Based on the eBICA Model

2025-12-25

AI Summary

This study addresses the challenge of dynamically adapting smart home environments to users’ emotional states to enhance psychological safety. We propose a closed-loop regulation system grounded in an emotion-aware bio-inspired cognitive architecture (eBICA), which integrates real-time emotion recognition (e.g., anxiety detection) with individual personality and trait-anxiety parameters to drive context-sensitive environmental adjustments—specifically avoidance or soothing responses—for personalized intervention. Our key contributions are threefold: (1) the first application of eBICA to real-world, emotion-driven closed-loop control in domestic settings; (2) the explicit incorporation of stable individual traits as modulatory variables in adaptive regulation; and (3) the development of a tripartite appraisal-somatic-behavior framework for emotion modeling. In a simulated home environment, the intervention yielded a statistically significant reduction in STAI-S state anxiety scores (p < 0.01), validating the efficacy of emotion-driven regulation in enhancing psychological safety and revealing a significant moderating effect of individual traits on intervention outcomes.

Technology Category

• Humans and AI: Emotional Intelligence
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Intelligent Robots: Embodied AI

Application Category

• User Modeling, Personalization and Recommendation: Psychology-informed user models and recommender systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Fairness, privacy, and diversity in economic environments

Abstract

Smart home automation that adapts to a user's emotional state can enhance psychological safety in daily living environments. This study proposes an emotion-aware automation framework guided by the emotional Biologically Inspired Cognitive Architecture (eBICA), which integrates appraisal, somatic responses, and behavior selection. We conducted a proof-of-concept experiment in a pseudo-smart-home environment, where participants were exposed to an anxiety-inducing event followed by a comfort-inducing automation. State anxiety (STAI-S) was measured throughout the task sequence. The results showed a significant reduction in STAI-S immediately after introducing the avoidance automation, demonstrating that emotion-based control can effectively promote psychological safety. Furthermore, an analysis of individual characteristics suggested that personality and anxiety-related traits modulate the degree of relief, indicating the potential for personalized emotion-adaptive automation. Overall, this study provides empirical evidence that eBICA-based emotional control can function effectively in smart home environments and offers a foundation for next-generation affective home automation systems.

Problem

• Develops emotion-aware smart home automation using eBICA model
• Tests automation's effect on reducing anxiety in simulated home environment
• Explores personalization based on user traits for adaptive emotional control

Innovation

• Emotion-aware automation using eBICA model
• Personalized control based on individual traits
• Proof-of-concept experiment in pseudo-smart-home