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https://www.um.edu.mt/library/oar/handle/123456789/128830| Title: | Automated monitoring technologies and construction productivity enhancement : building projects case |
| Authors: | Alzubi, Khalid Mhmoud Alaloul, Wesam Salah Malkawi, Ahmad B. Salaheen, Marsail Al Qureshi, Abdul Hannan Musarat, Muhammad Ali |
| Keywords: | Construction projects Construction industry -- Risk management Construction industry -- Automation Construction industry -- Production control Artificial intelligence |
| Issue Date: | 2023 |
| Publisher: | Elsevier BV |
| Citation: | Alzubi, K. M., Alaloul, W. S., Malkawi, A. B., Al Salaheen, M., Qureshi, A. H., & Musarat, M. A. (2023). Automated monitoring technologies and construction productivity enhancement: Building projects case. Ain Shams Engineering Journal, 14(8), 102042. |
| Abstract: | Monitoring the construction productivity (CP) is significant for the success of construction projects as it helps to assess the project performance. This study aims to investigate the relation between automated monitoring (AM) technologies and CP enhancement. To achieve this, the different AM technologies that are used for monitoring in building projects, factors affecting CP, and factors of CP that can be monitored using AM were investigated and prioritized. A mixed methodology including a systematic review and analytic hierarchy process was adopted. Results provide that; CP factors can be detected and enhanced effectively by monitoring CP. Among the adopted AM technologies, vision-based (37%) is the most effective one in monitoring CP. While workforce factors are the most important factors affecting CP. Also, in terms of factors monitored using AM technologies, factors within the workforce category come in the first place. Consonantly, it is rational to focus on monitoring these factors to enhance CP. |
| URI: | https://www.um.edu.mt/library/oar/handle/123456789/128830 |
| Appears in Collections: | Scholarly Works - FacBenCPM |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Automated_monitoring_technologies_and_construction_productivity_enhancement_building_projects_case_2023.pdf | 1.76 MB | Adobe PDF | View/Open |
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