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The noise and dust particles caused by the construction transport are by most stakeholders experienced as disturbing. The purpose of this study is to explore how sonification can support visualization in construction planning to decrease construction transport disturbances.

This paper presents an interdisciplinary research project, combining research on construction logistics, internet of things and sonification. First, a data recording device, including sound, particle, temperature and humidity sensors, was implemented and deployed in a development project. Second, the collected data were used in a sonification design, which was, third, evaluated with potential users.

The results showed that the low-cost sensors used could capture “good enough” data, and that the use of sonification for representing these data is interesting and a possible useful tool in urban and construction transport planning.

There is a need to further evolve the sonification design and better communicate the aim of the sounds used to potential users. Further testing is also needed.

This study introduces new ideas of how to support visualization with sonification planning the construction work and its impact on the vicinity of the site. Currently, urban planning and construction planning focus on visualizing the final result, with little focus on how to handle disturbances during the construction process.

Showing the potentials of using low-cost sensor data in sonification, and using sonification together with visualization, is the result of a novel interdisciplinary research area combination.

This paper aims to focus on 11 digital technologies (i.e. building information modeling, artificial intelligence and machine learning, 3D scanning, sensors, robots/automation, digital twin, virtual reality, 3D printing, drones, cloud computing and self-driving vehicles) that are portrayed in future trend reports and hype curves. The study concentrates on the current usage and knowledge of digital technologies in the Swedish architecture, engineering and construction (AEC) industry to gain an insight in the possible expectations and future trajectory of these digital technologies.

The study applies an abductive approach which is based on three different types of methods. These methods are a literature and document study which focused on 11 digital technologies, two workshops with industry (13 participants) and an online survey (N = 84).

The paper contributes to a current state analysis of the Swedish AEC industry concerning digital technologies and discusses the trajectory of these technologies for the AEC industry. The paper identifies hype factors, in which the knowledge of a digital technology is related to its usage. From the hype factors, four zones that show different stages of digital technology usage and maturity in the industry are induced.

The contribution of the paper is twofold. The paper shows insight into opportunities, the current barriers, use and knowledge of digital technologies for the different actors in the AEC industry. Furthermore, the study shows that the AEC industry is behind the traditional Gartner hype curves and contributes with defining four zones for digital technologies for the Swedish AEC industry: confusion, excitement, experimentation and integration.

The purpose of this paper is to investigate the potential integration of deep learning (DL) and digital twins (DT), referred to as (DDT), to facilitate Construction 4.0 through an exploratory analysis.

A mixed approach involving qualitative and quantitative analysis was applied to collect data from global industry experts via interviews, focus groups and a questionnaire survey, with an emphasis on the practicality and interoperability of DDT with decision-support capabilities for process optimization.

Based on the analysis of results, a conceptual model of the framework has been developed. The research findings validate that DL integrated DT model facilitating Construction 4.0 will incorporate cognitive abilities to detect complex and unpredictable actions and reasoning about dynamic process optimization strategies to support decision-making.

The DL integrated DT model will establish an interoperable functionality and develop typologies of models described for autonomous real-time interpretation and decision-making support of complex building systems development based on cognitive capabilities of DT.

The research explores how the technologies work collaboratively to integrate data from different environments in real-time through the interplay of the optimization and simulation during planning and construction. The framework model is a step for the next level of DT involving process automation and control towards Construction 4.0 to be implemented for different phases of the project lifecycle (design–planning–construction).

Construction 4.0 technology is a novel innovative technology that has been proved to enhance project performance. However, information on the concept's awareness, adoption readiness and challenges in developing economies is still scanty. The purpose of the study is to appraise awareness, adoption readiness and challenges of Construction 4.0 technologies in Nigeria to bring to the fore the state of art of these innovative technologies in the study area.

The study used a convenient sampling technique to select 129 construction professionals (architects, engineers and quantity surveyors) in Osun State, Nigeria, who provided data for the study through a closed-ended structure questionnaire survey. The quantitative data supplied were analysed using frequency, percentile, Cronbach's alpha, mean score (MS) analysis and analysis of variance (ANOVA).

The overall awareness level of construction professionals in the study area about Construction 4.0 technologies is at a moderate level (MS = 3.03). The analysis of each component of the Construction 4.0 technologies shows that BIM (MS = 3.69) has the highest level of awareness, while augmented reality (MS = 2.51) has the least awareness level. More results show a significant difference in the opinion of the respondents, a significant difference in the respondents on 36% of the components of Construction 4.0 technologies. The adoption readiness of the Nigerian construction industry (NCI) to Construction 4.0 technologies is at an initial level (MS = 2.86). However, the 3D printing (MS = 3.36) and augmented reality (MS = 2.49) have the highest and lowest adoption readiness ratings, respectively. There is no significant difference in how respondents ranked the NCI adoption readiness on 73% of the components of Construction 4.0 technologies. The main challenges of Construction 4.0 technologies in the study area are lack of standardisation (MS = 4.02), lack of investment in research and development and cost of implementation (MS = 3.87) each. The result shows that there is perfect unanimity in the way respondents ranked the challenges of Construction 4.0.

The study provided information on the status quo of Construction 4.0 technologies in the NCI to enhance improvement in practice and the attendant project delivery.

The study attempted to bring to the fore the state of the art on awareness, adoption readiness and challenges of Construction 4.0 technologies in Nigeria. The study's information will be valuable to improve project delivery.