Automated Data Acquisition in Construction with Remote Sensing Technologies
Near real-time tracking of construction operations and timely progress reporting are essential for effective management of construction projects. This does not only mitigate potential negative impact of schedule delays and cost overruns but also helps to improve safety on site. Such timely tracking...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-04-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/10/8/2846 |
| _version_ | 1797570131276070912 |
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| author | Osama Moselhi Hassan Bardareh Zhenhua Zhu |
| author_facet | Osama Moselhi Hassan Bardareh Zhenhua Zhu |
| author_sort | Osama Moselhi |
| collection | DOAJ |
| description | Near real-time tracking of construction operations and timely progress reporting are essential for effective management of construction projects. This does not only mitigate potential negative impact of schedule delays and cost overruns but also helps to improve safety on site. Such timely tracking circumvents the drawbacks of conventional methods for data acquisition, which are manual, labor-intensive, and not reliable enough for various construction purposes. To address these issues, a wide range of automated site data acquisition, including remote sensing (RS) technologies, has been introduced. This review article describes the capabilities and limitations of various scenarios employing RS enabling technologies for localization, with a focus on multi-sensor data fusion models. In particular, we have considered integration of real-time location systems (RTLSs) including GPS and UWB with other sensing technologies such as RFID, WSN, and digital imaging for their use in construction. This integrated use of technologies, along with information models (e.g., BIM models) is expected to enhance the efficiency of automated site data acquisition. It is also hoped that this review will prompt researchers to investigate fusion-based data capturing and processing. |
| first_indexed | 2024-03-10T20:21:34Z |
| format | Article |
| id | doaj.art-b39b9e5510414498a2379e2aa39d8d36 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T20:21:34Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-b39b9e5510414498a2379e2aa39d8d362023-11-19T22:11:36ZengMDPI AGApplied Sciences2076-34172020-04-01108284610.3390/app10082846Automated Data Acquisition in Construction with Remote Sensing TechnologiesOsama Moselhi0Hassan Bardareh1Zhenhua Zhu2Centre for Innovation in Construction and Infrastructure Engineering and Management (CICIEM), Department of Building, Civil and Environmental Engineering, Concordia University, 1455 de Maisonneuve Blvd, West, Montreal, QC H3G 1M8, CanadaDepartment of Building, Civil and Environmental Engineering, Concordia University, Sir George Williams Campus, 1455 De Maisonneuve Blvd. W., Montréal, QC H3G 1M8, CanadaDepartment of Civil and Environmental Engineering, University of Wisconsin-Madison, 2258 Engineering Hall, 1415 Engine Drive, Madison, WI 53706, USANear real-time tracking of construction operations and timely progress reporting are essential for effective management of construction projects. This does not only mitigate potential negative impact of schedule delays and cost overruns but also helps to improve safety on site. Such timely tracking circumvents the drawbacks of conventional methods for data acquisition, which are manual, labor-intensive, and not reliable enough for various construction purposes. To address these issues, a wide range of automated site data acquisition, including remote sensing (RS) technologies, has been introduced. This review article describes the capabilities and limitations of various scenarios employing RS enabling technologies for localization, with a focus on multi-sensor data fusion models. In particular, we have considered integration of real-time location systems (RTLSs) including GPS and UWB with other sensing technologies such as RFID, WSN, and digital imaging for their use in construction. This integrated use of technologies, along with information models (e.g., BIM models) is expected to enhance the efficiency of automated site data acquisition. It is also hoped that this review will prompt researchers to investigate fusion-based data capturing and processing.https://www.mdpi.com/2076-3417/10/8/2846automated data acquisitionremote sensing technologiesautomated progress reportingdata fusiontracking resources |
| spellingShingle | Osama Moselhi Hassan Bardareh Zhenhua Zhu Automated Data Acquisition in Construction with Remote Sensing Technologies Applied Sciences automated data acquisition remote sensing technologies automated progress reporting data fusion tracking resources |
| title | Automated Data Acquisition in Construction with Remote Sensing Technologies |
| title_full | Automated Data Acquisition in Construction with Remote Sensing Technologies |
| title_fullStr | Automated Data Acquisition in Construction with Remote Sensing Technologies |
| title_full_unstemmed | Automated Data Acquisition in Construction with Remote Sensing Technologies |
| title_short | Automated Data Acquisition in Construction with Remote Sensing Technologies |
| title_sort | automated data acquisition in construction with remote sensing technologies |
| topic | automated data acquisition remote sensing technologies automated progress reporting data fusion tracking resources |
| url | https://www.mdpi.com/2076-3417/10/8/2846 |
| work_keys_str_mv | AT osamamoselhi automateddataacquisitioninconstructionwithremotesensingtechnologies AT hassanbardareh automateddataacquisitioninconstructionwithremotesensingtechnologies AT zhenhuazhu automateddataacquisitioninconstructionwithremotesensingtechnologies |