A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Productivity monitoring in building construction projects: a systematic review
The unique nature of the construction sector makes it fall behind other sectors in terms of productivity. Monitoring construction productivity is crucial for the construction project's success. Current practices for construction productivity monitoring are time-consuming, manned and error prone. Although previous studies have been implemented toward reducing these limitations, a gap still exists in the automated monitoring of construction productivity.
This study aims to investigate and assess the different techniques used for monitoring productivity in building construction projects. Therefore, a mixed review methodology (bibliometric analysis and systematic review) was adopted. All the related publications were collected from different databases, which were further screened to get the most relevant based on the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) criteria.
A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. Also, it was observed that current studies did not cover all the complex construction job sites and they were applied based on a small sample of construction workers and machines separately.
This review paper contributes to the literature on construction management by providing insight into different productivity monitoring techniques.
Productivity monitoring in building construction projects: a systematic review
The unique nature of the construction sector makes it fall behind other sectors in terms of productivity. Monitoring construction productivity is crucial for the construction project's success. Current practices for construction productivity monitoring are time-consuming, manned and error prone. Although previous studies have been implemented toward reducing these limitations, a gap still exists in the automated monitoring of construction productivity.
This study aims to investigate and assess the different techniques used for monitoring productivity in building construction projects. Therefore, a mixed review methodology (bibliometric analysis and systematic review) was adopted. All the related publications were collected from different databases, which were further screened to get the most relevant based on the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) criteria.
A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. Also, it was observed that current studies did not cover all the complex construction job sites and they were applied based on a small sample of construction workers and machines separately.
This review paper contributes to the literature on construction management by providing insight into different productivity monitoring techniques.
Productivity monitoring in building construction projects: a systematic review
Productivity monitoring
Alaloul, Wesam Salah (author) / Alzubi, Khalid M. (author) / Malkawi, Ahmad B. (author) / Al Salaheen, Marsail (author) / Musarat, Muhammad Ali (author)
Engineering, Construction and Architectural Management ; 29 ; 2760-2785
2021-06-23
26 pages
Article (Journal)
Electronic Resource
English
Extending and operationalizing construction productivity measurement on building projects
| Taylor & Francis Verlag | 2018
Extending and operationalizing construction productivity measurement on building projects
| British Library Online Contents | 2018
Productivity in Construction Projects
| Wiley | 2015