Abstract
PurposeThe use of digital inspection or e-inspection of transportation projects has been proven as an efficient method over the last decade. A wide range of studies were dedicated to developing and applying e-inspection techniques and technologies. However, there is a lack of a comprehensive systematic review and content analysis of using e-inspection in highway construction and maintenance projects. The main objectives of this study were to explore the current trend and identify relevant inspection technologies and their applications for highway construction projects.Design/methodology/approachA systematic review of 172 articles from 16 high-ranked academic journals in construction engineering and management published during 2000–2021 was conducted. This process resulted in 67 relevant articles included in the detailed content analysis. The analysis involved synthesizing six main construction elements and work types, nine typical inspection activities, and 23 technologies.FindingsThe result of the analysis showed that among the six construction elements and work types, bridge and hot mix asphalt (HMA) recorded the largest share of e-inspection research. For the nine inspection activities, progress monitoring of construction operations was the highest focused area of e-inspection research. The most common e-inspection technologies are geospatial tools, 3D modeling, and unmanned aircraft systems (UASs). Camera-based inspection has existed for decades, however, has limited research development. The critical success factors in implementing e-inspection in highway projects are sharing data among different technologies, inspector training, and reducing the cost of technology purchase.Originality/valueThis study is one of the first attempts to conduct a content analysis of the e-inspection implementation for highway projects. The findings of this study expose knowledge gaps in contemporary research related to implementation barriers such as cost of purchase and operation of e-inspection technologies and transferring data between technologies.
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