Artificial Intelligence for Climate-Resilient Architecture and Sustainable Built Environments: Scopus Literature Dataset

Description

This dataset comprises Scopus-indexed literature examining the application of artificial intelligence and emerging computational approaches to architecture, buildings, and the built environment. It focuses on how these technologies support climate resilience, sustainability, energy efficiency, adaptation, and environmentally responsive design, providing a structured evidence base for systematic review and thematic analysis.

Steps to reproduce

The dataset can be reproduced in Scopus by entering the complete Boolean search string into the Advanced Search interface using the TITLE-ABS-KEY field. The search should combine four conceptual blocks: artificial intelligence and computational approaches; architecture and the built environment; climate resilience and adaptation; and sustainability-related concepts. Apply subject-area limits to Engineering (ENGI), Environmental Science (ENVI), Social Sciences (SOCI), Computer Science (COMP), Energy (ENER), and Multidisciplinary (MULT). Restrict the language to English and the document type to Article (ar). Set the publication-year range from 2020 through 2026 by applying PUBYEAR > 2019 AND PUBYEAR < 2027. Run the search and record the number of resulting documents. Export the complete results, preferably including citation information, bibliographical information, abstracts, keywords, and other available metadata. Save the exported records as a CSV file and retain the original search string, search date, database version/interface, and applied filters to ensure transparency and reproducibility.

Institutions

• Baze University

  FCT, Abuja

Categories

Licence