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The crane plays an essential role in modern construction sites as it supports numerous operations and activities on-site. Additionally, the crane produces a big amount of data that, if analyzed, could significantly affect productivity, progress monitoring and decision-making in construction projects. This paper aims to show the usability of crane data in tracking the progress of activities on-site.

This paper presents a pattern-based recognition method to detect concrete pouring activities on any concrete-based construction sites. A case study is presented to assess the methodology with a real-life example.

The analysis of the data helped build a theoretical pattern for concrete pouring activities and detect the different phases and progress of these activities. Accordingly, the data become useable to track progress and identify problems in concrete pouring activities.

The paper presents an example for construction practitioners and researcher about a practical and easy way to analyze the big data that comes from cranes and how it is used in tracking projects' progress. The current study focuses only on concrete pouring activities; future studies can include other types of activities and can utilize the data with other building methods to improve construction productivity.

The proposed approach is supposed to be simultaneously efficient in terms of concrete pouring detection as well as cost-effective. Construction practitioners could track concrete activities using an already-embedded monitoring device.

While several studies in the literature targeted the optimization of crane operations and of mitigating hazards through automation and sensing, the opportunity of using cranes as progress trackers is yet to be fully exploited.

In this study, a critical literature review was utilized in order to provide a clear review of the relevant existing studies. The literature was analyzed using the meta-synthesis technique to evaluate and integrate the findings in a single context.

Digital transformation in construction requires employing a wide range of various technologies. There is significant progress of research in adopting technologies such as unmanned aerial vehicles (UAVs), also known as drones, and immersive technologies in the construction industry over the last two decades. The purpose of this research is to assess the current status of employing UAVs and immersive technologies toward digitalizing the construction industry and highlighting the potential applications of these technologies, either individually or in combination and integration with each other.

The key findings are: (1) UAVs in conjunction with 4D building information modeling (BIM) can be used to assess the project progress and compliance checking of geometric design models, (2) immersive technologies can be used to enable controlling construction projects remotely, applying/checking end users’ requirements, construction education and team collaboration.

A detailed discussion around the application of UAVs and immersive technologies is provided. This is expected to support gaining an in-depth understanding of the practical applications of these technologies in the industry.

The review contributes a needed common basis for capturing progress made in UAVs and immersive technologies to date and assessing their impact on construction projects. Moreover, this paper opens a new horizon for novice researchers who will conduct research toward digitalized construction.

The utilisation of emerging technologies for the inspection of bridges has remarkably increased. In particular, non-destructive testing (NDT) technologies are deemed a potential alternative for costly, labour-intensive, subjective and unsafe conventional bridge inspection regimes. This paper aims to develop a framework to overcome conventional inspection regimes' limitations by deploying multiple NDT technologies to carry out digital visual inspections of masonry railway bridges.

This research adopts an exploratory case study approach, and the empirical data is collected through exploratory workshops, interviews and document reviews. The framework is implemented and refined in five masonry bridges as part of the UK railway infrastructure. Four NDT technologies, namely, terrestrial laser scanner, infrared thermography, 360-degree imaging and unmanned aerial vehicles, are used in this study.

A digitally enhanced visual inspection framework is developed by using complementary optical methods. Compared to the conventional inspection regimes, the new approach requires fewer subjective interpretations due to the additional qualitative and quantitative analysis. Also, it is safer and needs fewer operators on site, as the actual inspection can be carried out remotely.

This research is a step towards digitalising the inspection of bridges, and it is of particular interest to transport agencies and bridge inspectors and can potentially result in revolutionising the bridge inspection regimes and guidelines.

The intricate dynamics of ChatGPT adoption among Indian students are discussed while exploring the factors outlined by Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). By assessing these factors, this study aims to unravel their impact on the behavioral intention to use ChatGPT.

While evaluating ChatGPT's adoption dynamics, this study analyses the UTAUT2 core factors and perceived benefits. Real-time data from 638 business and management students in India were collected through purposive sampling and a cross-sectional survey. An in-depth examination using IBM SPSS and AMOS revealed the patterns that regulate ChatGPT reception in educational settings.

Habit emerges as a powerful predictor, which aligns with the Habit Loop Theory's cues, routine and rewards. Perceived benefits significantly influence adoption, and traditional factors like performance expectancy and social influence exert no influence. The insignificance of effort expectancy challenges conventional understanding, unveiling novel aspects of student tech adoption.

There is a need for guidelines to ensure fair and responsible use of ChatGPT among students. While ChatGPT presents advantages like task automation and personalized learning, integrating it into the existing education system requires careful planning to harness its benefits effectively.

With the recent introduction of Generative-AI tools, understanding student acceptance and application is essential. This research sheds light on this emerging technology, emphasizing the importance of analyzing technology acceptance for its successful adoption.

In recent years, the emergence of Industry 4.0 technologies as a way of increasing productivity has attracted the attention of the manufacturing industry. This study aims to investigate the relationship between Industry 4.0 technologies and lean tools (LTs) by measuring how the internalisation of LTs influences the adoption of Industry 4.0 technologies and how the synergy between them helps improve productivity in European manufacturing firms.

Results from 1,298 responses were used to analyse linear regression and study the correlation between the use of LTs and Industry 4.0 technologies.

Results show that the companies analysed tend to implement more Industry 4.0 technologies when their level of lean internalisation is high.

This study provides useful information for managers of manufacturing firms by showing the correlation between LT internalisation and Industry 4.0 technologies, corroborating that optimal implementation of these technologies is preceded by a high level of LT internalisation. Furthermore, although there are studies showing the relationship between LTs and Industry 4.0 technologies, none consider the intensity of their implementation.