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Artificial intelligence and the internet of things in environmentally building water consumption model: bibliometric analysis

  • Maranatha Wijayaningtyas*
  • , Abraham Lomi
  • , Ellysa Nursanti
  • , Nusa Sebayang
  • , Maria Istiqhoma
  • *Corresponding author for this work
  • National Institute of Technology, Malang

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

Environmentally friendly houses are a solution to reduce the negative impact of buildings on the environment. One of the criteria is water conservation in housing, the implementation of which is heavily influenced by the behaviour of residents. The inhabitants' behaviour varies and affects how much water conservation and conservation are applied in the building. This study performs a thorough bibliometric analysis of the scientific output concerning using artificial intelligence and the Internet of Things in water consumption and conservation in environmentally friendly or sustainable buildings. The research is based on data from Scopus, covering the period from 1996 to 2024. The study found research collaborations among diverse institutions and nations, highlighting prominent research achievements in this sector. The network visualisation analysis was conducted using a VOS viewer. The results of this study can provide valuable insights for scholars, experts, politicians, and funding organisations seeking a comprehensive overview of the current trends and objectives in this field. The results from this study provide a valuable framework for future research directions and underscore the importance of continued investment in implementing Artificial Intelligence and the Internet of Things to achieve water conservation in the future.

Original languageEnglish
Article number08004
JournalBIO Web of Conferences
Volume155
DOIs
Publication statusPublished - 29 Jan 2025
Externally publishedYes
Event10th International Conference on Climate Change, ICCC 2024 - Hybrid, Gifu, Japan
Duration: 6 Nov 20248 Nov 2024

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