Digital Twin (DT) technology, as the evolution of Building Information Modeling (BIM), has emerged to address global concerns regarding the environmental impacts of the construction industry and to meet sustainability indicators. Despite numerous studies targeting the integration of DT and sustainability, there is a noticeable gap in creating a comprehensive overview of the efforts and future directions in this field. Therefore, this research aims to provide both a scientometric analysis and a thematic review of 235 papers extracted from the Scopus database. These papers, all published between 2017 and 2024, focus on previous efforts, current trends, and future directions of using the Digital Twin for construction sustainability. In addition, 34 papers that were cited more than 20 times were classified by the application into four categories: simulation, technology integration, smart systems, and literature review. Furthermore, regarding the application of smart systems in sustainability, the authors discussed applications of BIM-DT in smart construction, smart buildings, smart infrastructures, and smart cities based on the most-cited papers. Subsequently, five research gaps were identified and suggested for future investigation. The research gives a holistic insight into the current trend of DT among researchers, previous achievements, and future directions.

Research projects have indicated development of several technical solutions for the management of construction activities. However, little attention has been paid to the issues regarding the adoption and implementation of these techniques. This study investigates the perception of Automated Data Collection (ADC) technology usage in construction, and identifies reasons why available ADC technology has not been fully introduced in construction. A comprehensive literature review carried out in this research identifies barriers to the adoption of ADC technology. In total, 19 key factors are identified as barriers for adoption of ADC technology in construction, and validated through an international questionnaire survey. According to the results, process related factors play an essential role in adopting automated data acquisition technologies in the construction industry. In order to form the backbone of technology adoption in real scenarios, and to identify driving factors in this field, this paper also introduces an implementation framework for ADC technology in the construction industry.

Building Information Modelling (BIM) has created a fundamental change in the field of designing and management of construction projects. Due to the visual and parametric capabilities of BIM, it improves the efficiency of the task. In the design phases, the BIM drawings and plans prepared by individual designers, are integrated and reviewed in a federated model. In this process, several clashes have occurred that can be detected by BIM tools such as Autodesk Navisworks. these clashes are including a large number of irrelevant clashes, that require no changes or have a clear resolution. Therefore improvement of clash detection accuracy is a majority for the success of BIM applications. In this article, clashes which detected by BIM tools are automatically grouped to determine the priority of resolving and to identified irrelevant clashes. Also, the results of Autodesk Navisworks have been used to improve the process of clash detection. This study used naviswork`s API and coded a plugin to automatically improve clash detection. research`s plugin provide a basis for prioritizing clashes for their resolution. The case study showed that applying the proposed plugin can be identified importance and irrelevant clashes.

Purpose: The site layout has a significant impact on the efficiency of construction operations. Planning an effective site layout partly involves identifying and positioning temporary facilities such as tower cranes and areas on the jobsite for materials storage. This study proposes an approach to optimizing the type and location of the tower crane and material supply point on construction sites.Design/methodology/approach: The problem is formulated into an integer linear programming (ILP) model considering the total cost of material transportation as the objective function and site conditions as constraints. The efficacy of the approach is demonstrated by finding the optimum site layout for a numerical example. The proposed model is validated and verified using two methods.Findings: Results indicate that the proposed model successfully identifies the type and location of the tower crane and the location of material supply point, leading to approximately 20% cost reduction compared with when such features of a site layout are decided solely based on experience and educated guesses of the construction manager.Originality/value: The primary contribution of this study is to present a modified linear mathematical model for site layout optimization that exhibits improved performance compared with previous models. The type and location of the tower crane and the material supply point as decision variables are extracted directly from solving the proposed model. The proposed model will help enhance time and cost efficiency on construction sites.