Sensor-assisted Evaluation Framework for Mobile Cooling Devices Integrating Environmental Sensing and Multicriteria Decision-making

technique for order preference by similarity to ideal solution (TOPSIS), sensory evaluationIn this study, we propose an integrated evaluation framework for mobile cooling products by combining environmental sensing, the analytic hierarchy process (AHP), and a fuzzy technique for order preference by similarity to ideal solution (Fuzzy-TOPSIS) to assess product performance and user experience under realistic usage conditions.Four representative product design types-turbo type, ice crystal type, folding type, and ice-crystal/folding hybrid typewere selected for empirical investigation.Environmental sensing was first employed to acquire microclimate parameters, including ambient temperature, relative humidity, and air velocity, enabling context-aware performance assessment.AHP was subsequently applied to determine the relative weights of two primary evaluation dimensions, namely, sensory attributes and sustainable design factors.Subjective sensory ratings and fuzzy linguistic evaluations collected from 60 participants were then integrated using Fuzzy-TOPSIS to obtain overall performance rankings across different usage scenarios.The results indicate comparable importance between sensory and sustainability dimensions (0.515 vs 0.485), reflecting users' simultaneous emphasis on thermal comfort and energy efficiency.The overall ranking was ice-crystal/folding hybrid type > ice-crystal type > turbo type > folding type.Regression analysis further reveals that tactile comfort and perceived airflow cooling significantly enhance emotional satisfaction, while noise negatively affects user experience in quiet environments.The proposed framework effectively integrates environmental sensing with multicriteria decision-making and sensory evaluation, offering a scalable approach for the design and assessment of portable and wearable climate-adaptive products.Sensors and Materials, Vol.38, No. 2 (2026) conditions characterized by high ambient temperature, low wind speed, and elevated radiative load frequently lead to thermal discomfort among commuters, outdoor workers, and people in recreational situations.Mobile cooling products have therefore emerged as an on-demand and infrastructure-independent solution for localized thermal relief.Despite their growing market presence, the evaluation of such products remains largely limited to isolated performance indicators, such as airflow velocity, battery endurance, and noise level, which cannot adequately represent the coupled effect of environmental conditions, device behavior, and user perception encountered in real-world usage scenarios.From an engineering and measurement perspective, two critical gaps persist in current research.First, device performance is rarely assessed in conjunction with environmental sensing data, meaning that cooling effectiveness is often evaluated without reference to actual microclimatic conditions.As thermal sensation and airflow perception are strongly modulated by ambient temperature, humidity, wind, and radiation, performance metrics obtained under controlled laboratory conditions may lack contextual validity.Second, the user perception of mobile cooling products, including thermal sensation, tactile comfort, acoustic quality, and visual semantics, is inherently multidimensional and uncertain.Conventional linear rating scales struggle to capture such fuzzy subjective judgments, particularly when these perceptions must be integrated with sustainability-related design indicators such as energy efficiency, modularity, repairability, and lifecycle considerations.These limitations highlight the need for evaluation frameworks that explicitly link sensor-derived environmental data with human-centered experience assessment.To address these challenges, we propose an integrated evaluation framework combining environmental sensing, the analytic hierarchy process (AHP), and a fuzzy technique for order preference by similarity to ideal solution (Fuzzy-TOPSIS).Environmental sensing is employed to acquire key microclimatic parameters, enabling context-aware measurement rather than abstract performance comparison.AHP is applied to establish the relative importance of sensory attributes and sustainability indicators through expert-driven hierarchical weighting, ensuring transparency and consistency in the decision structure.Fuzzy-TOPSIS is then used to manage uncertainty in subjective user evaluations by representing linguistic judgments with fuzzy numbers, allowing the robust comparison and ranking of alternative product designs.Four representative product design categories-turbo type, ice crystal type, folding type, and hybrid type-are selected as empirical case studies to enable cross-scenario and cross-dimensional analyses.The conceptual foundation of this work is grounded in sensory design and product experience research, which emphasizes that user responses emerge from the combined effects of multiple sensory stimuli, including thermally perceived airflow, acoustic characteristics, tactile interaction, and visual semantics, rather than from isolated functional performance indicators.This viewpoint motivates the adoption of an integrated evaluation framework that links sensor-measured physical parameters with usercentered experience assessment.Norman proposed that product experience is shaped through visceral, behavioral, and reflective levels. (1)Desmet and Hekkert (2) and Hekkert and Schifferstein (3) further conceptualized product experience as an integration of sensory perception, meaning attribution, and emotional response.In the context of mobile cooling products, this implies that perceived cooling effectiveness depends not only on measured airflow