Construction Equipment Monitoring Research: A Bibliometric and Scientometric Analysis of Trends and Emerging Directions

Construction equipment monitoring has shifted from manual logbooks and early telematics toward intelligent digital systems, driven by the need to reduce delays in obtaining equipment data and improve decision-making on construction sites. This study examines research on construction equipment monitoring and tracking published between 2000 and 2026 to identify the evolution, major themes, and emerging directions in the field. A scientometric and bibliometric analysis was conducted on 1093 bibliographic records retrieved from Scopus and Web of Science on 20 May 2026. The annual publication trend was evaluated through 2025, the last complete publication year, while records indexed in 2026 were retained for the remaining corpus-level analyses. The datasets were preprocessed and analyzed using Bibliometrix, VOSviewer, and CiteSpace to examine publication trends, keyword networks, collaboration patterns, citation structures, and research clusters. The keyword network was interpreted through six major thematic clusters, which were synthesized into four broader knowledge streams covering operations and sensing, AI-based perception, safety monitoring, and BIM/digital-twin integration. The results show a substantial increase in the representation of AI- and perception-related research across the later publication periods, reflecting a transition from basic sensor-based approaches toward more intelligent and connected site systems. The study identifies leading contributors and comparatively underdeveloped research priorities, particularly real-time idle-state detection, multimodal data fusion, multi-site validation, and the integration of monitoring outputs with BIM and digital-twin decision-support environments.

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Publication Details

Journal
Buildings
Published
2026-08-21
DOI
https://doi.org/10.3390/buildings16163336
Primary Topic
Occupational Health and Safety Research
Type
article
Field-Weighted Citation Impact
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article

Construction Equipment Monitoring Research: A Bibliometric and Scientometric Analysis of Trends and Emerging Directions

Ruqaya Al Sabah, Mohamed Tantawy, Salah Omar Said, Ahmed Mahmoud Elganzory
Buildings
Occupational Health and Safety Research
article

Construction Equipment Monitoring Research: A Bibliometric and Scientometric Analysis of Trends and Emerging Directions

Ruqaya Al Sabah, Mohamed Tantawy, Salah Omar Said, Ahmed Mahmoud Elganzory
article en

Abstract

Construction equipment monitoring has shifted from manual logbooks and early telematics toward intelligent digital systems, driven by the need to reduce delays in obtaining equipment data and improve decision-making on construction sites. This study examines research on construction equipment monitoring and tracking published between 2000 and 2026 to identify the evolution, major themes, and emerging directions in the field. A scientometric and bibliometric analysis was conducted on 1093 bibliographic records retrieved from Scopus and Web of Science on 20 May 2026. The annual publication trend was evaluated through 2025, the last complete publication year, while records indexed in 2026 were retained for the remaining corpus-level analyses. The datasets were preprocessed and analyzed using Bibliometrix, VOSviewer, and CiteSpace to examine publication trends, keyword networks, collaboration patterns, citation structures, and research clusters. The keyword network was interpreted through six major thematic clusters, which were synthesized into four broader knowledge streams covering operations and sensing, AI-based perception, safety monitoring, and BIM/digital-twin integration. The results show a substantial increase in the representation of AI- and perception-related research across the later publication periods, reflecting a transition from basic sensor-based approaches toward more intelligent and connected site systems. The study identifies leading contributors and comparatively underdeveloped research priorities, particularly real-time idle-state detection, multimodal data fusion, multi-site validation, and the integration of monitoring outputs with BIM and digital-twin decision-support environments.

BuildingsVol. 16(16)
Cairo University (EG), Kuwait Petroleum Corporation (Kuwait) (KW), Egypt Nanotechnology Center (EG), Kuwait University (KW)
Openalex Percentile: Top 9%
Occupational Health and Safety Research
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