A conceptual framework for user-centric smart homes: integrating the KANO model with IoT and machine learning
DOI:
https://doi.org/10.56294/dm2026825Keywords:
Smart Home systems, KANO model, IoT architecture, user-centered design, feature engineering, machine learningAbstract
Introduction: The evolution of the smart home technologies has been rapid, and the integration of innovative IoT devices, advanced automation, and responsive control systems are introduced to enhance comfort, security, and energy efficiency.
Objective: Despite the developments, the majority of smart home platforms are still not able to meet the expectation of the users due to the absence of the computational analysis of user priorities and feature-perception patterns. The article recommends a design and analysis framework using KANO Model that would contribute to the development of a user-friendly smart home system architecture.
Method: KANO Model is a computational requirement-classification model to categorize system characteristics into Must-Be features, One-Dimensional features, Attractive features, Indifferent features, and Reverse features to permit a methodical evaluation of their effect on user satisfaction. The study does not employ the traditional data collection method through survey, but employs the feature-engineering and requirement-Mapping methodology, which relies on user interaction behaviour, usage of existing systems, market analytics and performance-feature correlations based on smart home IoT environments.
Results: The findings reveal that One-Dimensional features, such as temperature control and energy optimization, directly correlate with user satisfaction levels, achieving scores of 0.85 and 0.88, respectively, while successfully reducing energy consumption by 25%. Furthermore, Must-Be features like motion detection showed a high satisfaction score of 0.95, reinforcing the necessity of fulfilling basic user expectations to prevent dissatisfaction.
Conclusions: Using the KANO Model in the development pipeline will enable more informed design decisions, improve the prioritization of features, and develop smart and user-centered solutions to the home.
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Copyright (c) 2026 Beibei Kao (Author)
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