Virtual reality application for indoor daylight visual comfort assessment: a systematic review of current research

日光 电流(流体) 虚拟现实 建筑工程 计算机科学 环境科学 人机交互 工程类 电气工程 物理 光学
作者
Athira Azmi,Sarah Abdulkareem Salih,Annisa Ummihusna,Maszura Abdul Ghafar,Rahinah Ibrahim
出处
期刊:Smart and sustainable built environment [Emerald (MCB UP)]
标识
DOI:10.1108/sasbe-08-2024-0303
摘要

Purpose This study explores the role of digital visualization technology, specifically virtual reality (VR), in assessing daylight visual comfort, a critical aspect of indoor environmental quality (IEQ) in built environment. Design/methodology/approach A systematic literature review was conducted following PRISMA guidelines on articles published between 2019 and 2023, sourced from Scopus, ScienceDirect, Emerald Insight and Sage. A total of 17 articles were selected for final analysis. The study classifies factors affecting users’ emotions and behavioral responses in immersive virtual environments using the stimulus-organism-response (S-O-R) framework from environmental psychology. Findings The review reveals that most VR studies on visual comfort and lighting focus predominantly on office environments, highlighting a significant research gap in residential contexts where daylighting strategies differ considerably. The analysis identifies four major clusters of factors—window properties, light properties, natural properties and spatial properties—that influence emotional, physiological, cognitive and perceptual responses, leading to behavioral outcomes such as energy consumption, productivity and lighting preferences. Practical implications The experimental designs, protocols and measurement tools from the selected studies are analyzed to recommend best practices for future research. This research offers strategic insights for conducting empirical studies using VR to assess daylight visual comfort in buildings. Originality/value This study extends the S-O-R framework by proposing a conceptual model linking key elements of visual comfort in residential settings to users’ emotions and behavioral responses. This model serves as a foundation for future VR-based experiments on indoor daylight visual comfort evaluation.

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