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The paper introduces V-SHiNE, a browser-based virtual smart home environment designed to facilitate the evaluation of explainable AI (XAI) methods in the context of smart home automation. V-SHiNE enables researchers to configure realistic smart home environments, simulate user behaviors, integrate custom explanation engines, and log user interactions. A user study with 159 participants demonstrates the framework's utility for assessing the impact and quality of different explanation strategies.
Stop struggling with explainability evaluation in smart homes: V-SHiNE offers a browser-based simulation framework for scalable, realistic, and reproducible assessments.
Explanations are essential for helping users interpret and trust autonomous smart-home decisions, yet evaluating their quality and impact remains methodologically difficult in this domain. V-SHiNE addresses this gap: a browser-based smarthome simulation framework for scalable and realistic assessment of explanations. It allows researchers to configure environments, simulate behaviors, and plug in custom explanation engines, with flexible delivery modes and rich interaction logging. A study with 159 participants demonstrates its feasibility. V-SHiNE provides a lightweight, reproducible platform for advancing user-centered evaluation of explainable intelligent systems