Systematic Literature Review on Knowledge-Driven Approaches for Construction Safety Analysis and Accident Prevention
Due to its inherent complexities in the process and the dynamic interactions with external environmental factors, the construction industry is widely considered one of the most hazardous industries worldwide. With advancements in artificial intelligence (AI), construction safety management practices...
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| Language: | English |
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MDPI AG
2024-10-01
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| Online Access: | https://www.mdpi.com/2075-5309/14/11/3403 |
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| author | Sonali Pandithawatta Seungjun Ahn Raufdeen Rameezdeen Christopher W. K. Chow Nima Gorjian |
| author_facet | Sonali Pandithawatta Seungjun Ahn Raufdeen Rameezdeen Christopher W. K. Chow Nima Gorjian |
| author_sort | Sonali Pandithawatta |
| collection | DOAJ |
| description | Due to its inherent complexities in the process and the dynamic interactions with external environmental factors, the construction industry is widely considered one of the most hazardous industries worldwide. With advancements in artificial intelligence (AI), construction safety management practices have increasingly used knowledge-driven approaches. Such incorporation of knowledge-based methods has led to significant improvements in various elements of construction safety management systems, including hazard identification and risk assessment, selection of risk mitigation strategies, analysis of accident information, sharing of health and safety knowledge, access to regulations, and identification of applicable safety requirements. Against this background, this paper presents a systematic literature review to provide an overview of the current state of the art in the use of knowledge-driven approaches in construction safety management. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) procedure, this study reviews how the knowledge-driven approach is utilized in the construction safety management field to automate different activities that come under it. Journal papers published from 2000 were considered for this review, and the analysis focused on the contributions of research, the evolution of knowledge-driven approaches, sources of incorporated knowledge, methods of system development, yearly publications, and publication by journals. The results provide a comparison of related studies over two decades and offer insights into trends and gaps in this research field. Notably, the trend analysis shows a dramatic increase in the number, as well as the depth, of research efforts utilizing AI techniques for analyzing unstructured data, such as construction images and texts from construction documents, and drawing data-based decisions for accident prevention. |
| format | Article |
| id | doaj-art-d40c244f8dd940afbe27faa4553a01d2 |
| institution | OA Journals |
| issn | 2075-5309 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
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| series | Buildings |
| spelling | doaj-art-d40c244f8dd940afbe27faa4553a01d22025-08-20T01:53:41ZengMDPI AGBuildings2075-53092024-10-011411340310.3390/buildings14113403Systematic Literature Review on Knowledge-Driven Approaches for Construction Safety Analysis and Accident PreventionSonali Pandithawatta0Seungjun Ahn1Raufdeen Rameezdeen2Christopher W. K. Chow3Nima Gorjian4Sustainable Infrastructure and Resource Management, UniSA STEM, University of South Australia, Adelaide, SA 5000, AustraliaDepartment of Civil and Environmental Engineering, Hongik University, P506, 94 Wausanro, Mapo-gu, Seoul 04066, Republic of KoreaSustainable Infrastructure and Resource Management, UniSA STEM, University of South Australia, Adelaide, SA 5000, AustraliaSustainable Infrastructure and Resource Management, UniSA STEM, University of South Australia, Adelaide, SA 5000, AustraliaSustainable Infrastructure and Resource Management, UniSA STEM, University of South Australia, Adelaide, SA 5000, AustraliaDue to its inherent complexities in the process and the dynamic interactions with external environmental factors, the construction industry is widely considered one of the most hazardous industries worldwide. With advancements in artificial intelligence (AI), construction safety management practices have increasingly used knowledge-driven approaches. Such incorporation of knowledge-based methods has led to significant improvements in various elements of construction safety management systems, including hazard identification and risk assessment, selection of risk mitigation strategies, analysis of accident information, sharing of health and safety knowledge, access to regulations, and identification of applicable safety requirements. Against this background, this paper presents a systematic literature review to provide an overview of the current state of the art in the use of knowledge-driven approaches in construction safety management. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) procedure, this study reviews how the knowledge-driven approach is utilized in the construction safety management field to automate different activities that come under it. Journal papers published from 2000 were considered for this review, and the analysis focused on the contributions of research, the evolution of knowledge-driven approaches, sources of incorporated knowledge, methods of system development, yearly publications, and publication by journals. The results provide a comparison of related studies over two decades and offer insights into trends and gaps in this research field. Notably, the trend analysis shows a dramatic increase in the number, as well as the depth, of research efforts utilizing AI techniques for analyzing unstructured data, such as construction images and texts from construction documents, and drawing data-based decisions for accident prevention.https://www.mdpi.com/2075-5309/14/11/3403construction safety managementontologiesknowledge graphknowledge baseexpert systemPRISMA |
| spellingShingle | Sonali Pandithawatta Seungjun Ahn Raufdeen Rameezdeen Christopher W. K. Chow Nima Gorjian Systematic Literature Review on Knowledge-Driven Approaches for Construction Safety Analysis and Accident Prevention Buildings construction safety management ontologies knowledge graph knowledge base expert system PRISMA |
| title | Systematic Literature Review on Knowledge-Driven Approaches for Construction Safety Analysis and Accident Prevention |
| title_full | Systematic Literature Review on Knowledge-Driven Approaches for Construction Safety Analysis and Accident Prevention |
| title_fullStr | Systematic Literature Review on Knowledge-Driven Approaches for Construction Safety Analysis and Accident Prevention |
| title_full_unstemmed | Systematic Literature Review on Knowledge-Driven Approaches for Construction Safety Analysis and Accident Prevention |
| title_short | Systematic Literature Review on Knowledge-Driven Approaches for Construction Safety Analysis and Accident Prevention |
| title_sort | systematic literature review on knowledge driven approaches for construction safety analysis and accident prevention |
| topic | construction safety management ontologies knowledge graph knowledge base expert system PRISMA |
| url | https://www.mdpi.com/2075-5309/14/11/3403 |
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