Abstract Heritage buildings are highly vulnerable to structural degradation due to aging materials, environmental exposure, and natural disasters, necessitating intelligent and realâtime monitoring solutions. The current study proposes a dew computingâenabled digital twin framework integrated with Explainable Artificial Intelligence (XAI) for structural risk evaluation and health prediction of heritage infrastructure. The framework combines Internet of Thingsâbased sensing, dewâfogâcloud computing architecture, blockchainâbased data security, and a hybrid deep learning model to enable efficient, low latency, and reliable monitoring. Temporal structural data are processed using a Convolutional Neural NetworkâGated Recurrent Unit (GRU) model for feature extraction and timeâseries prediction of the Structural Health Index, while a Random Forest (RF) classifier categorizes structural risk into safe, degraded, and critical states. Shapley Additive explanationsâbased XAI is incorporated to enhance interpretability and support expert decisionâmaking. Experimental evaluation on a simulated dataset of 45,212 instances demonstrates the effectiveness of the proposed approach. The GRUâbased model achieves high prediction performance with an accuracy of 94.42%, sensitivity of 94.85%, specificity of 97.01%, and F1âscore of 94.43%. Regression analysis shows low prediction errors (Mean Absolute Error: 0.0158, Root Mean Squared Error: 0.0198) and a high coefficient of determination (), indicating strong agreement between predicted and actual structural states. The RF classifier further achieves 94.64% accuracy in structural risk classification. The framework exhibits low latency (~0.000195 s per sample), high reliability under noisy conditions (up to 99%), and strong scalability across increasing dataset sizes. Overall, the proposed system provides a robust, scalable, and interpretable solution for proactive Structural Health Monitoring and riskâaware maintenance of heritage buildings, significantly improving realâtime decisionâmaking and longâterm conservation strategies.
The digitalization of the architecture, engineering, and construction (AEC) industry has demonstrated the revolutionary potential of integrating blockchain technology with building information modelling (BIM). However, the selection of the most appropriate blockchain solution is a multiple-criteria decision-making (MCDM) problem, which is usually influenced by conflicting criteria and deep uncertainty. To overcome this, the present study proposes an extended Fermatean fuzzy weighted aggregated sum product assessment (Extended FF-WASPAS) model. Unlike existing Fermatean fuzzy WASPAS (FF-WASPAS) methods, which are based on a single expert and may be biased, the proposed model incorporates the evaluations of multiple decision makers (DMKs) through a consensus-driven mechanism to ensure unbiased and accurate results. A case study is conducted to evaluate five leading blockchain platforms, Hyperledger Fabric, Polkadot, Tezos, Ethereum, and Algorand, under eight BIM-related criteria. The result indicates that Ethereum is the best blockchain platform to digitalize BIM compared to the other platforms because it is scalable, interoperable, secure, and has a wide range of applications in the real world. Sensitivity analysis over a wide range of parameter values, as well as DMKs assigned with different weight sets, confirmed the stability of the ranking. Furthermore, a quantitative comparative analysis with FF multiple criteria group decision-making (FF-MCGDM) and FF-WASPAS approaches, as well as a qualitative analysis with existing models in various fuzzy environments, confirms the robustness and reliability. Overall, the study provides a strong, interpretable, and consensus-based decision-support framework with high practical value for AEC stakeholders who wish to deploy secure, transparent, and efficient blockchain-enabled BIM solutions.
This study presents SmartMix Web3, a framework combining ensemble machine learning and blockchain technology to optimize low-carbon concrete design. It addresses two key challenges: (1) the limitations of conventional models in predicting concrete performance, and (2) ensuring data reliability and overcoming collaboration issues in AI-driven sustainable construction. Validated with 61 real-world experiments in Cameroon and 752 mix designs, the framework shows major improvements in predictive accuracy and decentralized trust. To address the first research question, a stacked ensemble model comprising Extreme Gradient Boosting (XGBoost)âRandom Forest and a Convolutional Neural Network (CNN) was developed, achieving a 22% reduction in Root Mean Square Error (RMSE) for compressive strength prediction and embodied carbon estimation compared to traditional methods. The 29% reduction in Mean Absolute Error (MAE) results confirms the superiority of Extreme Learning Machine (EML) in low-carbon concrete performance prediction. For the second research question, SmartMix Web3 employs blockchain to ensure tamper-proof traceability and promote collaboration. Deployed on Ethereum, it automates verification of tokenized Environmental Product Declarations via smart contracts, reducing disputes and preserving data integrity. Federated learning supports decentralized training across nine batching plants, with Secure Hash Algorithm (SHA)-256 checks ensuring privacy. Field implementation in Cameroon yielded annual cost savings of FCFA 24.3 million and a 99.87 kgCO2/m3 reduction per mix design. By uniting EML precision with blockchain transparency, SmartMix Web3 offers practical and scalable benefits for sustainable construction in developing economies.
Blockchain aggregators play an instrumental role in the evolution of blockchain technology, serving as pivotal enablers of interoperability, efficiency, and user accessibility in an increasingly decentralized digital world. However, the literature on this emerging technology is scarce and is not systematized, making it harder for practitioners and researchers to understand the field. In this paper, we systematize bridge aggregators, a type of blockchain aggregators. We present an exhaustive analysis of a diverse array of token and message aggregators, each distinguished by its unique architecture. Our research delves into critical aspects of these aggregators, encompassing their functionality, security measures, pricing models, and latency. This research aims to provide readers, users, and developers with insightful and actionable information, facilitating informed navi-gation through the complex landscape of blockchain aggregators. We explore our findings and compare them with our intuitive expectations. We show that there is a value in centralizing token aggregators. Message aggregators are found to be more powerful but less efficient in transaction cost and latency. Finally, we propose a set of future research directions for practitioners.
Increasing expectancy for efficiency in the delivery of building projects and the adoption of lean production processes for construction has made the necessity for the development of an integrated system for cost estimating, cost monitoring, cost control, and payments in the construction lifecycle important. Existing 5D BIM tools are used to estimate the cost of projects during the preconstruction period. There is a lack of integration between the 5D BIM models, existing progress monitoring tools, and payment systems used in construction. Lack of standardization in the use of model elements through the project lifecycle has also been identified as one of the factors limiting automation in 5D BIM. Construction project monitoring can be automated by combining modern technologies that allow for visualization of building progress (Laser scanners, computer vision) with 5D BIM cost estimation tools. These project monitoring tools can be combined with Artificial Intelligence (AI), and Smart contracts to develop an integrated lifecycle system for cost management in construction. This paper examines existing systems used in 5D BIM to develop integrated practices and systems that will streamline the process of cost estimating, cost monitoring, cost control, and cash flow in the construction supply chain. This will reduce the inefficiency that exists today with traditional contracts and payment applications that do not interact with the 5D BIM application. By leveraging a standardized classification ID system throughout a project life cycle and applying AI and smart contract, features like cost estimation cost control, and payments can be fully streamlined, integrated, and automated. A case study of an existing construction project utilizing 5D BIM was examined. According to the study, 5D BIM is used in the pre-construction stage of a cost estimation project. It was also revealed that 5D BIM improves project cost visualization and budget control.
To rationalize and automate public civil engineering works, it is crucial to directly utilize the information produced by the contractor for quality/ as-built inspection, and progress measurement.In this study, a highly reliable common data environment that utilizes blockchain and smart contracts to ensure tamper resistance and traceability of construction management information on quality and progress was developed and proved through verification tests in two project sites.
Zongliang Zhang, Sherong Zhang, Zhiyong Zhao, Lei Yan · 6 authors
Improving the design efficiency of hydropower hub buildings and promoting the application of intelligence in engineering construction and operation management have been critical issues in hydropower engineering construction. The major challenges are mainly reflected in the difficulties of multidisciplinary collaboration and the inefficient coordination of work involving multiple parties. This paper proposes a building information modeling (BIM)-based technology system architecture for digital design, intelligent construction, and intelligent operation, which combines BIM technology with geographic information system (GIS), computer aided engineering (CAE), internet of things (IoT), artificial intelligence (AI), and other technologies. The proposed system includes a BIM-based multiprofessional forward collaborative design method, a BIM-based engineering construction management model, and a real-time safety analysis and evaluation technology system based on actual measured safety information and construction. The hydroelectrical engineering BIM (HydroBIM) comprehensive control platform is developed. In the planning and design stage, the platform enables the whole process and full-professional collaborative digital design. In the engineering construction management stage, it supports the whole process and all-round information management and control of contract, schedule, quality, safety, and investment. In the operation management stage, the platform facilitates the integrated management of engineering safety evaluation, early warning, and emergency plan based on monitoring data and the consistency criterion of positive and negative evaluation. The application of this technology in more than 20 engineering, has proven to improve the efficiency of design and analysis of hydropower hub buildings and the intelligence level of engineering construction and operation management, and overcome the difficulties of multi-professional collaboration in the design stage and low efficiency of multi-participant coordination in the construction stage.
The construction industry is becoming increasingly interested in blockchains, and relevant publications have blossomed in recent years. This study provided a state-of-the-art review of blockchain research in the industry in order to better comprehend the fast-evolving technology. A systematic method integrating quantitative and qualitative analyses was used to capture the research status, challenges, and future directions based on 141 publications published between 2017 and 2021. The distributions of 141 papers were quantitatively analyzed in terms of chronology, geography, journal, and research type. The majority of blockchain applications focused on the construction stage, while progress payment management and supply chain management were the top two topics. Different blockchain applications throughout the entire lifecycle of building projects were also introduced through qualitative analyses. Finally, this research indicated the challenges and future directions of blockchain research in the construction industry. This review provides valuable information to help construction researchers and practitioners understand blockchain research advances and better determine research opportunities.
Typically, on-site construction quality inspection (OCQI) is manually conducted, and its effectiveness highly depends on the self-discipline of responsible personnel. Furthermore, construction quality information is still recorded on paper, with the risk of document loss and data manipulation, jeopardizing quality accountability. Blockchain has attracted increasing attention from the construction industry because it can record information in an immutable and transparent way and automate some businesses with smart contracts. These properties can tackle information fraud and improve the automation level of OCQI. Unfortunately, very few documented blockchain solutions for OCQI exist. To fill the theoretical knowledge gap, the design thinking approach was adopted to present a blockchain-based conceptual framework. The consortium network and Hyperledger Fabric (HLF) were selected as the suitable blockchain type and development platform for OCQI. The consensus process in HLF and smart contractsâbased compliance checking are illustrated. Moreover, the benefits of integrating the Internet of Things (IoT) and ontology technology with blockchain are analyzed in detail, which can facilitate the coevaluation of these three technologies. Finally, a prototype system was developed to vividly show the theoretical feasibility. The proposed blockchain solution can be fine-tuned and evaluated in future research. Challenges hindering the practical implementation of blockchains are systematically discussed within the technologyâorganizationâenvironment (TOE) theory, which can be reused in future investigations to identify construction stakeholdersâ concerns on adopting blockchains.
The ITC Digital Library has an ambition to provide a single point of entry to scholarly and research publication from the domain of construction informatics alias construction information technology. We believe that works, in full text, should be available for free, to the researchers, students and the industry.
Nicola Moretti, Juan Diego Blanco Cadena, Antonino Mannino, Tiziana Poli · 5 authors
Occupancy monitoring in smart buildings has great potential to improve their operational performance. One of the most common applications concerns the dynamic adaptation of indoor conditions according to the occupancy variation. However, other implementations are possible. Occupancy data could also enhance maintenance smart contracts management, especially if coupled with a contractsâ management system as blockchain through which it is possible to achieve higher reliability and trust in transactions. In this article, a methodology to monitor occupancy data with a low-cost network, composed by a set of ultrasonic sensors, is presented. To ensure the collection of consistent data, different tests were performed for defining a convenient configuration for their installation. Following the proposed methodology, gathered data are processed and stored into a digital asset model associated with the building maintenance plan. Once a predefined threshold is reached, the system triggers a maintenance alert to the contractor to activate cleaning operations. The proposed approach enables an enhancement of the automation of maintenance management operations in a cost-effective manner. However, further validation trials are required to test the flexibility of its application in different space types.
Konstantina Siountri, Emmanouil Skondras, Dimitrios D. Vergados
Building information modeling (BIM) is a revolutionary technology that provides all the necessary mechanisms to achieve end-to-end communication, data exchange and information sharing between project actors, leading to smarter outcomes for communities and more efficient projects for AEC service providers. 3D models generated in the context of engaging in the BIM process and as-delivered physical assets through building management systems (BMS) adopt Internet of Things (IoT) architectures and services. However, the orchestration of IoT devices in a highly modular environment with many moving parts and inter-dependencies between the stakeholders of this environment, lead to many security issues. This article focuses on applying novel technologies in the construction industry, such as BIM, IoT, and Blockchain, but also on examining their interconnection and interoperability on a proposed system architecture on a case of a building (museum), where efficient security, management and monitoring are considered crucial factors for the unobstructed operation of the organization that hosts.
In India, we are facing various challenges due to improper management of road construction process. Mostly the contracts of road constructions are manipulated by political leaders or some corrupted personalities. This leads to low quality roads, traffic issues due to extended work on road and various frauds during procurement of raw material and wages of labors. With the help of artificial intelligence, we can determine the duration within which road construction will be completed for particular area, how much raw material is expected, how much labors should be appointed and many more. Blockchain will assure the integrity of contracts within stakeholders. After completion of road, by reviewing user's feedback we can determine quality of road or any maintenance related things by applying Machine learning strategy. Ultimately it will explore an expert system for whole life process of Road Construction which leads to Industry 4.0 in India.
Increasing attention has been paid since the early 1990s to improving the quality of road networks in Latin America. The region has been broadly impacted by the new thinking on what constitutes good road management which gained currency at that time. The foundations of a regional approach towards implementing reforms were created under the PROVIAL program and a number of countries received advice and technical assistance. Since then varied progress has been made along five main dimensions: increasing funding for road conservation; reforming existing road management institutions; extending private sector participation; introducing new forms of contracting; and decentralizing road management. Some measurable progress has been made on network quality. Expenditure on roads is however less than it needs to be, shortfalls in public resources only partially offset by increased private sector flows, and there has been no clear shift from investment to maintenance. Countries have not generally followed PROVIAL recommendations on road user based funding for maintenance. Greater success has been achieved in implementing the recommendations on contracting with considerable progress in the employment of performance-based contracting and the development of a range of options from CREMA style long term concessions to micro-enterprises for routine maintenance. A challenge will be pursue decentralization more actively as a means to address lagging network quality at sub-national level. For the covering abstract see ITRD E139491.
Private-ownership of roads in Nigeria is still at the deliberation stage. In other words roads (tarred and untarred) are owned by Federal, State and Local authorities in Nigeria. Most of these roads, however, share a common characteristic of being âunsafe at any speedâ, at any time of the day. This is as a result of the low quality of the road components, structures and patterns. For example, road surfaces are undulating and rough. Also, the poor standard of road infrastructure like guard railings/barriers; pavement marking and signs; illumination levels, traffic signals, horizontal/vertical alignment and sight lines contribute largely to the increasing carnage on Nigerian road network. This trend persists because authorities in Nigeria have practically relegated to the background regular road safety audit operations. This is an inevitable aspect of modern methods of road administration and management, which determines a number of traffic potentials concerning highway high collision locations; protection of errant vehicles from light poles, trees, ditches, replacement of damaged and missing signs, street lighting, capacity and level of service analysis. Finally, this paper suggests commissioning of a National Road Research Fund, with a view to developing an efficient road safety audit operational system. Also, the introduction of private initiatives and a Community-based Approach in road administration, as well as decentralization of road administration framework at all levels, will greatly help âengineer outâ potentially unsafe features across Nigerian roads, towards a better road traffic environment in the 21st century.