Towards energy-efficient indoor environment quality using artificial intelligence: A bibliometric analysis

Lim, S.C.J. and Tee, Boon Tuan and Siew, P.W. and Lee, M.F. (2024) Towards energy-efficient indoor environment quality using artificial intelligence: A bibliometric analysis. In: 2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 15 December through 18 December 2024, Bangkok, Thailand.

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Abstract

With the increasing awareness of sustainability in the built environment, there is a pressing need to achieve a comfortable and healthy indoor environment with optimized energy consumption. In this context, artificial intelligence (AI) has shown its potential as a tool for energy optimization while upholding high IEQ standards. This research paper explores the current and future research trends in utilizing AI to achieve an energy-efficient indoor environment quality (IEQ). Bibliometric analysis is used as a methodology to identify key research themes and the thematic evolution of a research field. Based on a carefully formulated search term, a case study is performed using bibliometric data downloaded from the SCOPUS database. Upon data pre-processing steps, the research evolution of the field is presented visually using strategic mapping and thematic evolution networks over the years 2018-2023, with discovered insights discussed. Finally, some discussion on future works is given based on key insights.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Energy efficiency, Indoor environment quality, Artificial intelligence, Bibliometric analysis, Building environment
Divisions:	Faculty Of Mechanical Technology And Engineering
Depositing User:	Wizana Abd Jalil
Date Deposited:	30 Oct 2025 07:22
Last Modified:	30 Oct 2025 07:22
URI:	http://eprints.utem.edu.my/id/eprint/29135
Statistic Details:	View Download Statistic

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