Construction Engineering Research Articles

Research on BIM sub-model data of construction engineering based on MVD

BIM technology has been widely applied to various stages of construction projects in China. The data required at each stage and scenario of construction projects varies, necessitating the definition of target BIM data according to data needs. When BIM software generates IFC models, different MVD templates can be configured to output BIM sub-models. To study the characteristics of data configuration for different MVDs, this article takes construction projects as an example and designs an analysis experiment for BIM sub-model output based on MVD. It analyzes the differences and characteristics of IFC model data from both the overall project level and the professional component level according to key indicators, with the aim of providing references for construction project personnel to select matching MVDs, ensuring the effectiveness of BIM sub-models, and meeting the needs of business scenario applications.

Virtual Value Engineering in Investment and Construction Activities

Statement of the problem. The Russian investment and construction industries continue to grow, and there is a growing demand for services related to designing and implementing new projects. The introduction of innovative technologies and improvements to construction processes are essential parts of investment and construction efforts in today's world. Engineering plays a significant role in investment and construction projects, as it is involved both in the planning phase and during the implementation stages. Cost engineering is a concept that refers to a set of techniques and tools used to manage the expenses of a project throughout its lifecycle. The integration of investment and construction engineering services with the latest technological advancements is a new but already popular trend in the construction market. Results. This study emphasizes the importance of an integrated approach to facility design, considering the unique characteristics of modern technology and the requirements of participants in investment and construction projects that require operational involvement in project management. Conclusions. The paper supports the introduction of «virtual engineering», which can create a more comfortable environment for all stakeholders in an investment or construction project.

Toward Smart Urban Management: Integrating Geographic Information Systems and Geology for Underground Bearing Capacity Prediction in Casablanca City, Morocco

To effectively manage the sustainable urban development of cities, it is crucial to quickly understand the geological and geotechnical attributes of the underground. Carrying out such studies entails significant investments and focused reconnaissance efforts, which might not align seamlessly with large-scale territorial planning initiatives within a city accommodating more than 3 million inhabitants, like Casablanca in Morocco. Additionally, various specific investigations have been conducted by municipal authorities in recent times. The primary aim of this study is to furnish city managers and planners with a tool for informed decision-making, enabling them to explore the geological and geotechnical properties of soil foundations using Geographic Information Systems (GISs) and geostatistics. This database, initially intended for utilization by developers and construction engineers, stands to economize a substantial amount of time and resources. During the urban planning of cities and prior to determining land usage (five- or seven-floor structures), comprehending the mechanical traits (bearing capacity, water levels, etc.) of the soil is crucial. To this end, geological and geotechnical maps, along with a collection of 100 surveys, were gathered and incorporated into a GIS system. These diverse data sources converged to reveal that the underlying composition of the surveyed area comprises silts, calcarenites, marls, graywackes, and siltstones. These formations are attributed to the Middle Cambrian and the Holocene epochs. The resultant geotechnical findings were integrated into the GIS and subjected to interpolation using ordinary kriging. This procedure yielded two distinct maps: one illustrating bearing capacity and the other depicting the substratum. The bearing capacity of the soil in the study zone is rated as moderate, fluctuating between two and four bars. The depth of the foundation remains relatively shallow, ranging from 0.8 m to 4.5 m. The outcomes are highly promising, affirming that the soil in Casablanca boasts commendable geotechnical attributes capable of enduring substantial loads and stresses. Consequently, redirecting future urban planning in the region toward vertical expansion seems judicious, safeguarding Casablanca’s remaining green spaces and the small agricultural belt. The results of this work help to better plan the urban development of the city of Casablanca in a smarter way, thus preserving space, agriculture, and the environment while promoting sustainability. In addition, the databases and maps created through this paper aim for a balanced financial management of city expenditures in urban planning.

A Remote Monitoring System for Wind Speed and Direction Based on Non-Contact Triboelectric Nanogenerator

Wind speed and wind direction sensors are crucial sensor categories in the Internet of Things (IoT), particularly vital in fields such as meteorological monitoring, construction engineering, transportation engineering, and ocean engineering. However, power supply remains a key limiting factor for the widespread application of these sensors in large-scale sensor networks. In this paper, a self-powered, non-contact wind speed and direction sensor based on the triboelectric nanogenerator (SD-TENG) is proposed. The optimized wind speed measurement structure has a start-up wind speed as low as 0.2m/s and exhibits good linearity in the range of 0.2-29m/s. Additionally, the sensor demonstrates high temperature and humidity resistance, with a voltage attenuation of 2.4% at 45°C ambient temperature and 9.8% at 95% relative humidity. For wind direction measurement, the design of non-uniform electrodes enhances the recognition capability of different channels. To meet the demands of remote monitoring, we have designed an advanced signal processing circuit that can directly convert the raw output of a wind speed sensor into wind speed information and upload it to a cloud platform via a host. This system not only records and displays wind speed data in real-time but also features historical data storage and alarm functionalities, enhancing the intelligence and automation levels of wind speed monitoring. Additionally, users can access and analyze wind speed data through both computer and mobile devices, ensuring the system's efficiency and reliability. This work provides crucial technical support for the advancement of smart cities, clean energy, and environmental monitoring, thereby promoting the application and dissemination of IoT technology in the environmental field.

Realisation of secondary vocational education programmes in high-tech training areas in LPR, DPR, Kherson and Zaporozhye regions in the aspect of career needs

Introduction. Special attention in the conditions of active technological development and digitalisation of the economy is paid to training specialists mastering secondary vocational education (hereinafter – SVE). This interest is based on the demand in the labour market for such specialists who will be able to make a significant contribution to the development of high-tech industries. To secure the successful implementation of SVE programmes in Donetsk People’s Republic (hereinafter – DPR), Lugansk People’s Republic (hereinafter – LPR), Zaporozhye and Kherson regions, it is necessary to ensure compliance with the learners’ career needs. For this purpose, it is necessary to take into account the needs of the labour market as well as the dominant industrial areas in these territories. The aim of the article is to analyse the current state of the SVE system in LPR, DPR, Zaporozhye and Kherson regions in high-technology training programmes in the context of the career needs of the new regions. Research methods. The quantitative and qualitative analysis was implemented using the number of the involved educational institutions: DPR (64), LPR (60), Zaporozhye (14), Kherson (4) and Kemerovo regions (84). Results. The large number of institutions makes it possible to implement the “Professionalisation” programme in the above regions, but at the moment no localisation of territories is available, including technological clusters. The comparative analysis of the SVE institutions in DPR and Kuzbass regions revealed the predominance of high-tech fields: computer science and engineering (13 and 11), mechanical engineering (12 and 15), land transport engineering and technology (16 and 10), construction engineering and technology (8 and 14). The SVE training areas in DPR are characterised by more programmes in the field «Economics and management» (24) and «Electrical and heat engineering» (17). Conclusion. The survey results can serve as a basis for designing a teacher training system aimed at the realisation of SVE programmes and supplementary education programmes in high-tech training areas in the said regions.

IoT—A Promising Solution to Energy Management in Smart Buildings: A Systematic Review, Applications, Barriers, and Future Scope

The use of Internet of Things (IoT) technology is crucial for improving energy efficiency in smart buildings, which could minimize global energy consumption and greenhouse gas emissions. IoT applications use numerous sensors to integrate diverse building systems, facilitating intelligent operations, real-time monitoring, and data-informed decision-making. This critical analysis of the features and adoption frameworks of IoT in smart buildings carefully investigates various applications that enhance energy management, operational efficiency, and occupant comfort. Research indicates that IoT technology may decrease energy consumption by as much as 30% and operating expenses by 20%. This paper provides a comprehensive review of significant obstacles to the use of IoT in smart buildings, including substantial initial expenditures (averaging 15% of project budgets), data security issues, and the complexity of system integration. Recommendations are offered to tackle these difficulties, emphasizing the need for established processes and improved coordination across stakeholders. The insights provided seek to influence future research initiatives and direct the academic community in construction engineering and management about the appropriate use of IoT technology in smart buildings. This study is a significant resource for academics and practitioners aiming to enhance the development and implementation of IoT solutions in the construction sector.

Experimental investigation on tailoring compressive properties and energy absorption of 3D printed gradient star re-entrant hybrid auxetic structure

Purpose Fused filament fabrication (FFF) is a widely used 3D printing technique for the fabrication of mechanical metamaterials with intricate geometries. Gradient strategy is applied to geometric parameters of gradient star re-entrant hybrid auxetic (GSRA) structure. Deformation behaviour is studied under compressive loading. The purpose of this study is to investigate the influence of gradient geometric parameters on mechanical properties, namely, specific strength (SS), specific modulus (SM) and specific energy absorption (SEA). Design/methodology/approach Response surface methodology (RSM) is implemented for the design of experiments of gradient geometric parameters to minimize the number of experimental tests. Acrylonitrile butadiene styrene material is used for the fabrication of GSRA structures by FFF technique. The best set of gradient parameters has been optimized maximizing all three responses using RSM and artificial neural network optimization technique. Findings During compressive testing, row-wise deformation is observed with two-stage plateau regions, which results in increase in SEA of the structure. Furthermore, based on analysis of variance and 3D response plots, it is found that height gradient is the most influencing gradient geometric parameter on SS and SM, whereas the wall thickness gradient has maximum influence on SEA. Meanwhile, the interaction effect of wall thickness gradient and height gradient has maximum influence on SS, SM and SEA. Research limitations/implications This study of applying gradient strategy to geometric parameters is limited to GSRA structure under compressive loading. In addition, findings are valid within the selected range of gradient geometric parameters. These findings are useful for the selection of gradient geometric parameters to maximize SS, SM and SEA of GSRA structure simultaneously. These outcomes pave the way for designing light-weight gradient hybrid auxetic structures in the field of construction, aerospace, automobile and biomedical engineering. Originality/value Limited experimental study is available on investigating the influence of gradient geometric parameters on mechanical properties, namely, SS, SM and SEA, and deformation behaviours of hybrid auxetic structures. This study directly addresses the above research gaps.

Harnessing social marketing for interdisciplinary health management: enhancing public health outcomes

Abstract Social marketing in health leverages the principles of traditional marketing to influence behaviours that benefit individuals and communities. It involves using marketing techniques to promote public health initiatives, aiming to change attitudes and behaviours towards healthier choices. By strategically framing health messages, social marketing can effectively reach diverse populations, encouraging them to adopt practices that enhance their wellbeing. This approach not only increases awareness about health issues but also empowers people to take proactive steps in managing their health, ultimately leading to improved public health outcomes. Showcasing a forward-thinking approach to public health management, this plenary session seeks to shed light on the transformative role of interdisciplinary collaboration in enhancing health outcomes. Recognising that health and wellbeing are influenced by a myriad of actors beyond the healthcare sector, there is a growing imperative to empower professionals from diverse disciplines with health management principles. By effectively ‘social marketing’ health management to those outside the traditional health sector, such as in architecture, urban planning, construction, education, transportation, and manufacturing, health-oriented decision-making can be seamlessly integrated across these fields. The session will highlight innovative approaches for engaging non-health stakeholders in decision-making processes, leveraging the expertise of health management and public health professionals. By facilitating a dialogue between health professionals and experts from other sectors, the session will explore the potential and challenges of intersectoral partnerships, and challenge policymakers, health managers, and stakeholders in the health sector to actively engage non-health professionals in their pursuit of improved health outcomes for European citizens. Case studies from across Europe where interdisciplinary collaborations have led to social programming and infrastructure developments that enhance health and wellbeing will be presented. The case study ‘Compassionate leadership’ will delve into how organisation leaders can harness their health management capacity to foster a supportive environment that prioritises wellbeing. ‘Health-centric design in public spaces’ will demonstrate the impact of designing public areas with a focus on health, showcasing how thoughtful urban planning can significantly enhance community health. The third case study, ‘Architecture for better health and healing’ will highlight the role of architectural design in promoting health and recovery, emphasising the importance of creating spaces that support healing. Finally, ‘Educating to health’ will underline the significance of educating young people to healthy habits, sustainability, and physical and mental wellbeing, illustrating how this can lead to healthier communities. By fostering broader interdisciplinary collaboration, it is possible to unlock innovative solutions to health challenges and ultimately create healthier, more resilient communities across Europe. Moderator Tiago Correia Instituto de Higiene e Medicina Tropical, Universidade NOVA de Lisboa, Portugal, and Board Member of the EHMA Speakers/Panellists Marina Macchiaiolo Rare Diseases and Medical Genetics Unit, Bambino Gesù Children’s Hospital, Italy, and President of the Italian Committee for the United World Colleges Stefano Capolongo Department of Architecture, Construction Engineering and Built Environment (ABC), Politecnico di Milano, Italy

The Impact of a Non-Uniform and Transient Magnetic Field on Natural Convective Jeffrey Fluid Flowing over a Heated Porous Plate: A Comparitive Study

Examining the effects of varying transient magnetic fields and their orientations on boundary layers aids in understanding the flow in complex surface geometries, turbulence control, drag reduction, aircraft and ship design, groundwater management, and the study of construction and coastal engineering. The study introduces a novel dynamics of the boundary layer of a natural convective Jeffrey fluid flowing over an erect porous moving plate under the influence a non-uniform and transient magnetic field M ˜ that grows exponentially over time with α as an accelerating parameter. The governing partial differential equations (PDEs) were non-dimensionalized using similarity variables and then solved analytically using the perturbation technique. The impact of various thermosphysical properties including chemical reactions, thermal source, Jeffrey fluid parameter and plate permeability on the fluid flow were presented graphically utilizing finite difference approximation(FDA) technique in MATLAB ODE15s solver. The study highlighted a notable decrease in shear stress (skin friction) by introducing M ˜ to the vertical plate results in the reduction of momentum boundary layer, accompanied by an increment in thermal boundary layer. Also, the results shows that increasing the magnitude of α leads to decrease the velocity and increase the temperature distribution curve. Additionally, the concentration profile was also found to decrease with stronger chemical reactions. Furthermore, key parameters like heat and mass flux were estimated and discussed through comparison tables. Understanding the effects of unsteady and externally applied increasing magnetic field M ˜ on viscous fluid flow have potential applications in biomedical engineering, such as the design of magnetic drug delivery systems and the analysis of blood flow in human body.

Research on Collaborative Management of BIM (Building Information Modeling) in Engineering Projects

Abstract: The research on collaborative management of Building Information Modeling (BIM) in engineering projects aims to explore the application of BIM technology in construction engineering and its impact on collaborative management. BIM technology creates digital 3D models, centrally manages project information, promotes information sharing and collaboration, and improves project management efficiency. In construction projects, BIM technology can effectively solve the problems of difficult information sharing and poor information transmission, thereby making collaborative management more efficient. In addition, the application of BIM technology in the design, bidding, and construction stages can ensure the smooth transmission of information and improve the efficiency of collaborative management. Research has shown that the application of BIM technology in structural design significantly improves design quality and demonstrates its wide applicability. However, despite the significant advantages of BIM technology in collaborative management, there are still some challenges, such as trust issues and technical operational difficulties. Through in-depth research and application of BIM technology, more efficient collaborative management models can be provided for future engineering projects, promoting the development of the construction industry.

Exploring the Interaction and Impact of Green Building Design on People and Space

Abstract: With the progress and development of society, people's living standards improve at the same time, environmental pollution and resource shortages environmental problems also come. Construction engineering is one of the largest energy-consuming industries in China, and the implementation of a sustainable development strategy has become a top priority. Therefore, the state put forward the concept of greening and sustainable development, and green building has become a mainstream design concept. The purpose of this paper is to elaborate on the principles and design points of green building design and to study and discuss the application cases of green building design. Analyze the interaction and impact of green building design on people and space by analyzing the effects and impacts of the implementation of different designs in green building design cases, including focusing on siting design, ventilation design, energy efficiency design, recyclable design, plant design, and lighting design. Summarise the importance of applying green building design concepts and effective designs that have a positive impact on people. The results of the study can provide practical suggestions on improving the sustainability and eco-friendliness of green buildings for green building design stakeholders, such as architects, policymakers, and related stakeholders, and this study has certain reference values and significance.

Integrated Machine Learning and Region Growing Algorithms for Enhanced Concrete Crack Detection: A Novel Approach

In the field of construction engineering, the cracking of concrete structures is a common engineering problem, which has a great impact on the overall stability and service life of the engineered structure. During structural repair, crack detection is the most critical step. Automatic detection significantly reduces the engineering cost and human factor error compared with manual detection. However, due to the changeable environment of the project site and different image specifications, using a single algorithm makes it difficult to balance high efficiency and high accuracy. In this study, we designed a combined recognition method including the region growth algorithm and machine learning regression that can achieve a tradeoff between accuracy and efficiency. Firstly, the regression method learns the image features of the dataset and the specific region growth threshold, and the regression function is trained by using the open-source dataset to determine the region growth threshold using the characteristics of the images included in the tests. The region growth algorithm is used to expand the threshold from the seed points of the image to obtain the crack recognition results. The results show that this method improves the accuracy of SSIM by 7% compared with the traditional region growth algorithm, and does not significantly increase the computational cost, with an increase of 0.78 s per photo process. Compared with the deep learning method, the recognition accuracy of SSIM is decreased by 5.96%, but it takes less resources and has high efficiency.

Absorption and Release mechanism of superabsorbent polymers and its impact on shrinkage and durability of internally cured concrete – A review

Superabsorbent polymers (SAP) are considered as a promising assortment of chemical admixtures which present novel prospects for influencing the properties of cementitious materials in the fresh, setting, and hardened states. However, the diversity of commercial SAP, especially in terms of monomers, crosslinking agents, and synthesis methods, still poses many obstacles in their large-scale application. Therefore, this review aims to shed light on intrinsic absorption and release mechanism of various SAP and its impact on rheological properties, mechanical properties, shrinkage properties, and durability for cementitious materials. Our research findings indicate significant differences in the water absorption and release mechanisms between ionic and non-ionic SAP. The swelling of non-ionic SAP is dependent on the osmotic pressure formed between the polymer network and the solution. In contrast, ionic SAP not only exhibits osmotic properties but also generates charged hydrophilic groups in solution, which is a crucial factor contributing to polymer swelling. The water absorption characteristics of SAP facilitate the regulation of early cement matrix hydration and ensure the long-term stability of the concrete structure. These attributes are crucial for maintaining stable development in cement hydration and ensuring the overall structural integrity over time. The knowledge gleaned from this review offers a robust framework for the further research work on SAP and serves as support for practical application of internally cured concrete in construction engineering that need to withstand challenging environmental conditions.

Real-time data sensing and digital twin model development for pavement material mixing: enhancing workability and optimisation

ABSTRACT An essential aspect of pavement construction sustainability is its low-energy consumption and emissions. The study of pavement materials workability tests holds significant importance in terms of achieving well-mixed conditions with low-energy consumption. The complex components of the material and the uncertain kinematic behaviours of aggregates during mixing make this process challenging. And, few studies of the signal response of pavement materials have been found in the field of civil engineering. For this purpose, an accurate evaluation and monitoring approach for mixing are needed. In this paper, a wireless real-time sensing method is used to monitor the dynamic behaviour of aggregates during mixing. A 3D digital twin model, combining data-sensing techniques and numerical simulation, has been proposed for rapid identification of the mixing material. This model has been validated via a data-fusion algorithm. The application of this model makes a contribution to the data-intensive analysing jobs and decision-making tasks in pavement construction engineering.

A Review of Stoichiometric Nickel Sulfide-Based Catalysts for Hydrogen Evolution Reaction in Alkaline Media

Efficient and cost-effective catalysts for hydrogen evolution reaction (HER) are essential for large-scale hydrogen production, which is a critical step toward reducing carbon emissions and advancing the global transition to sustainable energy. Nickel sulfide-based catalysts, which exist in various stoichiometries, show promise for HER in alkaline media. However, as single-phase materials, they do not demonstrate superior activity compared to Pt-based catalysts. This review highlights recent strategies to enhance the HER performance of nickel sulfides, including heteroatom doping, heterostructure construction, and vacancy engineering, tailored to their different stoichiometric ratios. The study also examines synthesis methods, characterizations, and their impact on HER performance. Furthermore, it discusses the challenges and limitations of current research and suggests future directions for improvement.

Harnessing the power of ChatGPT to promote Construction Hazard Prevention through Design (CHPtD)

PurposeConstruction Hazard Prevention through Design (CHPtD) is recognized as a pivotal strategy for enhancing workplace safety. Despite its theoretical potential, practical implementation faces challenges, particularly regarding designers' familiarity with field-level operations and hazard recognition. This study aims to investigate whether ChatGPT can address these challenges by assisting in hazard recognition during CHPtD sessions.Design/methodology/approachThe research utilized a randomized controlled experiment to assess ChatGPT as an intervention in supporting hazard recognition during CHPtD sessions. The study involves 162 civil and construction engineering student participants, representing future professionals. Participants engaged in hazard recognition during CHPtD sessions either with or without the assistance of ChatGPT.FindingsParticipants who utilized ChatGPT during CHPtD sessions demonstrated a significant improvement in hazard recognition, identifying approximately 40% more hazards compared to those who did not use ChatGPT. These findings underscore the efficacy of ChatGPT in supporting CHPtD efforts.Practical implicationsThe results highlight the practical utility of harnessing ChatGPT in CHPtD sessions to enhance hazard recognition and ultimately promote workplace safety. By leveraging ChatGPT, designers and engineers can better anticipate and mitigate potential hazards during the design phase, thus creating a safer working environment for field workers.Originality/valueThis research contributes to addressing the challenges associated with implementing CHPtD by introducing ChatGPT as a valuable tool to support hazard recognition. By demonstrating the effectiveness of ChatGPT in enhancing hazard identification during CHPtD sessions, this study offers a novel approach to promoting the adoption of CHPtD and advancing workplace safety initiatives.

Preliminary Insights on Moisture Content Measurement in Square Timbers Using GPR Signals and 1D-CNN Models

Accurately measuring the moisture content (MC) of square timber is crucial for ensuring the quality and performance of wood products in wood processing. Traditional MC detection methods have certain limitations. Therefore, this study developed a one-dimensional convolutional neural network (1D-CNN) model based on the first 8 nanoseconds of ground-penetrating radar (GPR) signals to predict the MC of square timber. The study found that the mixed-species model exhibited effective predictive performance (R2 = 0.9864, RMSE = 0.0393) across the tree species red spruce, Dahurian larch, European white birch, and Manchurian ash (MC range 0%–133.1%), while single-species models showed even higher accuracy (R2 ≥ 0.9876, RMSE ≤ 0.0358). Additionally, the 1D-CNN model outperformed other algorithms in automatically capturing complex patterns in GPR full-waveform amplitude data. Moreover, the algorithms based on full-waveform amplitude data demonstrated significant advantages in detecting wood MC compared to those based on a traditional time–frequency feature parameter. These results indicate that the 1D-CNN model can be used to optimize the drying process and detect the MC of load-bearing timber in construction and bridge engineering. Future work will focus on expanding the dataset, further optimizing the algorithm, and validating the models in industrial applications to enhance their reliability and applicability.

Application Analysis of BIM Technology in Construction Engineering Cost Management

With the rapid development of information technology, Building Information Modeling (BIM) technology has gradually occupied an important position in the construction industry. With the introduction of BIM technology, the cost control of construction projects can be greatly improved [1]. The use of this technology can not only reduce the project approval time but also improve the quality of the project. In addition, it can also help the construction personnel to solve the project changes, maintenance costs, insurance rates, and other related issues, so that the operation of the project is more efficient and economical. This paper will discuss the role of BIM technology in depth, and explore the advantages and disadvantages of each link through the research of the project, to provide a reference for the promotion of this new project. By constantly adjusting the application strategy, the goal is to meet the current market demand.

Methods to mitigate the impact of work environment on the measurement of building surface temperature by unmanned aerial vehicle onboard thermal imaging system

With the widespread adoption of UAVs and compact infrared cameras, UAV infrared remote sensing technology has extensive applications in qualitative research fields such as finding thermal bridges and air tightness detection in construction projects, but less in quantitative research, mainly due to its large temperature measurement error. When measuring temperature with UAV-mounted thermal imaging cameras, factors such as operational wind conditions and operation methods, in addition to the inherent accuracy of the instrument, can introduce measurement errors. To investigate the impact of operational wind conditions on temperature measurements by UAV-mounted thermal imaging cameras, both field and laboratory experiments were conducted to analyze the error characteristics caused by wind conditions. Devices were designed to mitigate the impact of wind on temperature measurements, and their effectiveness was validated through experiments. Based on these findings, methods were developed for reducing the influence of wind conditions on temperature measurements in UAV operations. The results indicate that wind condition errors primarily affect the stability of temperature data. Under the influence of wind conditions, the temperature data recorded by thermal infrared cameras exhibit periodic and significant fluctuations, with a temperature difference of approximately 4.7 °C between the highest and lowest points within a single cycle, constituting the main source of measurement error. However, by following the prescribed measurement procedures, the temperature measurement error can be reduced by 32 %, from ±5 °C to ±1.6 °C, approaching the accuracy of tripod-mounted thermal imaging cameras. This establishes a foundation for quantitative research in low-altitude infrared remote sensing.

Digital twins for engineering structures—An Industry 4.0 perspective

AbstractThe term “digital twin” is becoming increasingly prevalent in both research and politics with regard to infrastructure structures. Industry is making significant advancements in the fields of automation and autonomy. While numerous definitions are in circulation, some of which are identical, many are similar in nature. This work examines the digital twin from its original industry perspective and considers its relevance to the constructional engineering sector. The objective of this study is to provide an overview of the current approaches in the Industry 4.0 and constructional engineering industry, examining the associated technical opportunities and challenges. The study compares the definitions, requirements and projects executed in this field. The technologies under examination are contrasted on the basis of their position within the data model. The preliminary findings suggest that some solutions for Industry 4.0 have already been developed for the construction engineering sector. However, it must be acknowledged that some solutions have yet to be fully validated.