Towards Energy-Efficient Indoor Environment Quality using Artificial Intelligence: A Bibliometric Analysis

• Published in: IEEE International Conference on Industrial Engineering and Engineering Management
• Main Author: Lim S.C.J.; Tee B.T.; Siew P.W.; Lee M.F.
• Format: Conference paper
• Language: English
• Published: IEEE Computer Society 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85218020875&doi=10.1109%2fIEEM62345.2024.10857153&partnerID=40&md5=54fd0b728adfad347e8c16a6602d6d12

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. © 2024 IEEE.