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|Title:||Human comfort in indoor environment : a review on assessment criteria, data collection and data analysis methods||Authors:||Song, Ying
|Keywords:||Engineering::Electrical and electronic engineering||Issue Date:||2019||Source:||Song, Y., Mao, F., & Liu, Q. (2019). Human comfort in indoor environment : a review on assessment criteria, data collection and data analysis methods. IEEE Access, 7, 119774-119786. doi:10.1109/ACCESS.2019.2937320||Journal:||IEEE Access||Abstract:||Occupants' comfort perception about the indoor environment is closely linked to their health, wellbeing and productivity. Improvement of comfort level in office buildings has significant positive impacts on both employers and employees. Human comfort in indoor environment usually can be assessed in four aspects: thermal comfort, visual comfort, acoustic comfort and respiratory comfort. In this paper, we present a literature review on the previous research contributions towards studying various aspects of human comfort with a special focus on the respective assessment criteria, data collection methods and data analysis approaches employed by former studies. Previous review work has covered the fundamental concepts associated with human comfort. However, their studies mainly focus on thermal comfort and there is limited work that covers other aspects of comfort. Moreover, few of them discuss how the data is obtained, how to extract useful information from the data and how the data is analyzed. To fill up this gap, this paper conducts the survey from the data-driven point of view. Through the survey, we find that sensor technology has been widely used in the data collection for various types of comfort, while so far the machine learning approaches are mainly applied in the area of thermal comfort study. Finally, some potential future research areas are proposed based on the current status of the research work. The established knowledge in this paper would provide useful insights for engineers or researchers who embark on their research in this area.||URI:||https://hdl.handle.net/10356/137876||ISSN:||2169-3536||DOI:||10.1109/ACCESS.2019.2937320||Rights:||This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given.||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Journal Articles|
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