ABSTRACT. The study focuses on the analysis of building management system (BMS), also known as building automation control system (BAS - BACS), which refers to a computer-based control system installed inside buildings to monitor and operate electrical and mechanical equipment. The development of new technologies has led to the emergence of smart buildings, that can collect data from devices and sensors using IoT (The Internet of Things) solutions. Thanks to Building Information Modeling (BIM), the successful adoption of these new digital technologies has been used increasingly in construction and facilities management. Despite the implicit integration of different systems, severe interoperability issues affect the integration of BMS operating on different fields. One often has to deal with various communication protocols and proprietary BMS platforms that use different communication modes. This document aims to analyze the data exchange between BMS and BIM through the study of file formats exported by the platforms to create an integration of IFC (Industry Foundation Classes) schema in BMS platforms, specifically using the BACnet protocol. In this way, it is proposed to use the existing standard (IFC) as a foundation for integrating communication between multiple platforms. This approach aims to streamline modes of communication and facilitate the creation of a digital twin.

ABSTRACT. A smart building relies on heterogeneous information systems, with data originating from different sources and represented in various formats. Semantic Web technologies allow connecting these disparate data sources by standardizing metadata with ontologies and enriching information with logical relationships. The latter enables not only shared understanding and interpretability by machines but also querying and reasoning capabilities. Brick and SOSA/SSN are such widely used ontologies in the smart building domain. These ontologies are currently used to semantically describe physical or virtual assets in a building. Building on these ontologies, we propose a semantic schema for a Model Predictive Controller (MPC) system. This MPC is designed as a Demand Side Management strategy for an office micro-grid system. The proposed semantic schema complements the use of Semantic Web technologies in the smart building. It allows the designed MPC application to seamlessly modify to a different building for both simulation and experimental purposes by communicating with necessary data sources with using the knowledge embedded in the semantic graphs.

ABSTRACT. The use of Building Information Models (BIM) in the construction industry is constantly increasing. However, the use of machine-readable data, machine processing, or the use of artificial intelligence has not. One of the barriers to digitalisation in the construction industry is the minimal use of metadata, despite significant efforts by companies, various interest groups, and authorities to standardise data content at different stages of the construction process. The study implemented a data platform that connects planning and procurement systems to national product data repositories, creating metadata that enable automated data flow and enrichment. This automation automatically converts as-designed data to as-built data, using the manufacturing industry's CAD/CAM systems data architecture as a reference model. The experiment demonstrated that automation is feasible with Manufacturing to Stock (MTS) products and enables the creation and management of location-specific Manufacturing Bill of Materials (M-BOM) required for procurement, logistics, construction, and building maintenance. This is achieved using the same principles as machine data processing, which is undertaken in the manufacturing industry as part of the Material Requirements Planning (MRP) process. A national reference model for MTS design and product data flow was published based on the experiments and research. The impact of this research is significant nationally and potentially at the EU level because it demonstrates that automation of data in construction is feasible despite the project-based nature of the industry utilising MTS products. Additionally, this opens the possibility of automating the calculation of the realised carbon footprint of MTS products as part of paced production. Furthermore, it revealed that the data model can be linked to ERP and product data repositories cost-effectively, provided that the metadata model is implemented appropriately. The research results pave the way for the digitalisation of other types of supply chain in the construction industry, such as Engineer to Order (ETO, e.g., precast concrete elements), Manufacturing to Order (MTO, e.g., kitchen furniture), and Assembly to Order (ATO, e.g., switchboard), by managing metadata in design and procurement data.

ABSTRACT. Architecture, Engineering, Construction and Operation (AECO) sector is characterised by a highly fragmented and scarcely interoperable framework throughout the building life cycle. Since building-related data collection and storing can be inaccurate and not coherent, facility management can be extremely complex. The use of a Digital Building Logbook, as a common repository for building information, would facilitate data availability and transparency for a variety of stakeholders involved in the construction process since most data in a paper-based format, out-of-date as-built data, or a lack of understanding about building components and systems make challenging, for example, the selection of the best refurbishment alternatives. Moreover, the heterogeneity of different sources makes fundamental the interoperability management to enable an enhanced information exchange. In this regard, the paper presents a framework for implementing the Digital Building Logbook utilising semantic web technologies. The proposed framework is built upon the use of ontologies and related data models following a federation approach, that allows the integration of data coming from different systems, using them within their domain. The result is a system that can act as a gateway for connecting different areas and data at different level of detail along the building life cycle, especially during the data-driven choices that are necessary in the operational stage.

ABSTRACT. Automated Code Compliance Checking in BIM models is a use pointed out as a promoter of greater productivity and reliability, especially in the design phase of AEC projects. Several application efforts have been made at different scales, but many barriers were encountered, such as the difficulty of transcribing rules written in human language into a structured and machine-readable language, the lack of modeling standards driven to automated checking, and the fact that the checker software code is not easily accessed. Currently, the evolution of neutral and open-source standards for information exchange turns this BIM use into a more versatile and scalable one. This paper presents the practical application of an automated code compliance checking process for accessibility rules, based on the neutral and open standards IFC and IDS, and presents the successes and limitations of this application, as well as the recommendations for its evolution.

ABSTRACT. The use of Building Information Modeling (BIM) is constantly advancing. BIM methods can be used to speed up the overall process of building construction by shortening the various phases. Several vendors have developed BIM checking software, especially in order to guarantee an error-free planning and execution phase. Current applications focus on coordination and quality assurance for participating contractors in the private sector. However, building authorities should also benefit from BIM methods, especially for automated code checking in the building permission process. As public authorities, they have additional requirements on BIM checking software. Consequently, these requirements have to be defined by building authorities to evaluate BIM checking software. The building authority of Vienna has shown great interest in developing automated building code checking in the past and was therefore selected to participate. In order to determine the relevant requirements expert workshops were held together with building authority agents. Major concerns regard the maintainability, availability, and expandability. These and other requirements were discussed and knock-out criteria were defined. This is followed by rating and ranking the previously determined parameters. Finally, a discussion is held based on the ranking of the requirements which can be used by the building authority of Vienna for future planning of automated building code checking.

ABSTRACT. Mental healthcare facilities require special design considerations. For such buildings, new ways will be needed to evaluate building performance and ensure building compliance. In this regard, Building Information Modelling (BIM) can capture the required properties that can affect the patient’s psychological requirements. This paper identifies the key BIM properties of healthcare facility buildings to be considered for a Psychological-Based Code Compliance Checking BIM System. The key components of the methodology will be discussed based on the covered relevant literature. The main findings are about the identification of the key psychological factors, the architectural design parameters of healthcare facilities and their BIM requirements in relation to the psychological factors. From the identified list of factors and parameters, the proposed framework will be used as a Psychological-Based Code Compliance Checking BIM System for Healthcare facilities.

ABSTRACT. Despite advances in technology, especially in the field of building sciences, the traditional, manual, paper-based process of issuing building permits is still widely used. This process has its own characteristics, such as the need for users' expertise in the field of laws as well as familiarity with construction systems and components, the unsystematic approach of experts in checking compliance with laws, and the possibility of incorporating human weaknesses such as fatigue and distraction, which lead to an increase in errors and the overall cost of construction activities. With the introduction of new technologies such as GIS and BIM and their advancements, new opportunities have opened for mutations in this area. This article explores the capacities and opportunities of GIS-BIM integration in improving the process of issuing building permits.

Considering the importance of granting building permits and the need for an efficient workflow in this area, this article first presents the challenges and shortcomings of the current process for granting building permits in the traditional way. It then introduces the concept of BIM-GIS integration and its potential application in transforming and modernizing the building permit process. To achieve this goal, the article identifies the fundamental elements of GIS and BIM, determine their capabilities and functions, and present their similarities and differences to better understand the potential synergy between them through a comprehensive review and analysis of the existing literature.

By examining current and existing initiatives, the paper will paint a picture of practitioners' experiences and researchers' efforts in applying BIM-GIS integration in construction permitting. These overviews show tangible benefits of integration, such as Increased productivity and efficiency in the construction industry. Despite the incredible potential, the paper also identifies and presents the challenges and gaps in the existing practice of using GIS-BIM integration in the granting of building permits. Challenges such as Interoperability challenges, lack of a unified approach, lack of standardized systems, etc. The article explores a broader concept of BIM-GIS application for stakeholders in this field by identifying opportunities in this area.

This article speaks to the current paradigm shift from traditional approaches to more innovative and integrated approaches to building permitting supported by GIS-BIM integration. It thus underlines the potential for change through integration not only in simplifying regulatory procedures but also in expanding the boundaries of knowledge in the field of construction permitting.

ABSTRACT. 1. Introduction and Motivation

The construction industry faces significant challenges in the coming years, including a severe shortage of skilled workers and the need for digital transformation to achieve sustainability and climate protection goals. The industry must adapt to technological change and implement digital working methods, such as Building Information Modeling (BIM), to meet these challenges [1–3]. However, the lack of qualified professionals with digital knowledge and experience significantly limits the implementation of digitalization initiatives. There is an urgent need to strengthen education and training in universities, educational institutions, companies, and public institutions [4]. To address these challenges effectively, the education sector must overcome several key pain points [5, 6]: Firstly, there is a significant gap between the digital skills currently taught in educational institutions and the evolving needs of industries like construction. This discrepancy leads to a workforce inadequately prepared for the digital demands of modern job roles. Secondly, there is an urgent need for curriculum updates and the integration of hands-on, practical digital training, often lacking in traditional educational settings. This includes theoretical knowledge and applying digital tools and methodologies specific to construction-related industries. Furthermore, there is resistance to change within the education system, which can slow the adoption of new technologies and teaching methods. Educators need upskilling and continuous professional development to stay abreast of digital trends and tools. Additionally, access to cutting-edge digital resources and infrastructure is uneven, creating disparities in learning opportunities, especially in underprivileged or remote areas. To overcome these challenges, a collaborative effort is needed. Industry leaders, educational institutions, and policymakers must work together to develop curriculums responsive to the digital age's needs. Investments in digital infrastructure and teacher training are crucial, as is creating more experiential learning opportunities, such as internships and project-based learning, directly aligned with industry requirements.

2. Methodology To effectively address these significant challenges, it is essential to employ various strategies in collaboration. Among these, the sharing and dissemination of knowledge stand out as particularly crucial elements [6, 7]. Starting this process as early as possible is vital to facilitating success and overcoming obstacles.

Thus, this paper explores concepts and approaches for the introduction of an open platform that provides educators, students, professionals and employees in companies with broad public access to practical, software vendor-neutral use cases from various disciplines. Central to this concept is the utilization of open standards and interoperable data formats (Big open BIM) to facilitate seamless integration across various software and disciplines, thereby enhancing content accessibility for diverse groups [8]. To further enhance the platform's effectiveness and relevance, it will be structured based on use cases, as is already common practice in describing the structure of BIM-based projects. The platform's structure is envisioned to be use case-oriented, mirroring the organization of BIM-based projects. This approach enables quick identification and engagement with relevant content, catering to the specific needs and research focuses of educators, students, and professionals. Moreover, the platform is designed to be community-driven, promoting a collaborative environment for knowledge sharing and continuous development. Members of this community, including educators, students, and industry professionals, can contribute educational materials, practical use cases, and best practices. A feedback system will be incorporated, allowing users to rate and review content. This not only ensures the quality and relevance of the materials but also provides insights into the community's needs, guiding future improvements of the platform.

3. Conclusions & Outlook The conceptualization of this open BIM educational platform aims to serve as a comprehensive resource for learning and collaboration, fostering a vibrant community that contributes to the digital transformation of the construction industry. This will enable students, trainees, and employees in the construction industry to learn practical skills that would otherwise have to be acquired later at a high cost through trial and error in projects. By shifting the focus to the early years of training, the positive effects are maximized at low cost, and the platform significantly contributes to preventing further delays in the urgently needed digital transformation of the construction industry. This platform is poised to play a pivotal role in democratizing education in digital planning, construction, and operation, offering equal opportunities regardless of location. It stands as a pathfinder for an improved and more inclusive training framework, covering the entire lifecycle of construction projects. The location-independent nature of the platform ensures that educators and students, especially in German-speaking regions and beyond, have equitable access to resources. This initiative is expected to significantly contribute to mitigating delays in the digital transformation of the construction industry, promoting early and interdisciplinary training in a cost-effective manner.

4. References [1] DIN EN ISO 19650-1:2019-08, Organisation und Digitalisierung von Informationen zu Bauwerken und Ingenieurleistungen, einschließlich Bauwerksinformationsmodellierung_(BIM)_- Informationsmanagement mit BIM_- Teil_1: Begriffe und Grundsätze (ISO_19650-1:2018); Deutsche Fassung EN_ISO_19650-1:2018, Berlin. [2] J. Beetz, A. Borrmann, C. Koch, and M. König, Eds., Building Information Modeling: Technology Foundations and Industry Practice, 1st ed. Cham: Springer International Publishing; Imprint: Springer, 2018. [3] C. M. Eastman, P. M. Teicholz, R. Sacks, and G. Lee, BIM handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors / by Chuck Eastman, Paul Teicholz, Rafael Sacks, Ghang Lee. Hoboken, New Jersey: Wiley, 2018. [4] PricewaterhouseCoopers GmbH, "Die Bauindustrie in anspruchsvollen Zeiten: Die Baubranche in anspruchsvollen Zeiten," 2023. [Online]. Available: https://www.pwc.de/de/managementberatung/capital-projects-and-infrastructure/herausforderungen-der-deutschen-bauindustrie.html [5] Y. Brandenburger, F. Weise, and S. Steinbach, "DigiLearnBIM – Digitale Transformation in der Bildung," in KOMPETENZEN FR DIE DIGITALE TRANSFORMATION 2020: Digitalisierung der arbeit -, L. Lehmann, D. Engelhardt, and W. Wilke, Eds., [S.l.]: MORGAN KAUFMANN, 2021, pp. 357–380. [6] A. M. McCarthy, D. Maor, A. McConney, and C. Cavanaugh, "Digital transformation in education: Critical components for leaders of system change," Social Sciences & Humanities Open, vol. 8, no. 1, p. 100479, 2023, doi: 10.1016/j.ssaho.2023.100479. [7] F. Peterson, T. Hartmann, R. Fruchter, and M. Fischer, "Teaching construction project management with BIM support: Experience and lessons learned," Automation in Construction, vol. 20, no. 2, pp. 115–125, 2011, doi: 10.1016/j.autcon.2010.09.009. [8] T. Maile, N. Bartels, and R. Wimmer, "Integrated life-cycle orientated teaching of the big-open-BIM method," in Proceedings of the 2023 European Conference on Computing in Construction and the 40th International CIB W78 Conference, 2023.

ABSTRACT. The Industry Foundation Classes (IFC) represent the cornerstone of Building Information Modelling (BIM), serving as a universal and standardized schema for information exchange in the construction industry. The extensive range of IFC classes poses a risk of element misclassification. Wrongly classified elements undermine data reliability, analytical processes, estimations and quantity take-offs. The study addresses the issue by introducing convolutional neural networks (CNN) trained to recognize individual elements based on their geometry. Comparing machine-identified entities with those labelled by a human allows the detection of potential mistakes. The application is designed to enhance the accuracy of model validation. The model efficiency is substantiated through rigorous testing on a large dataset of categorized IFC elements extracted from hundreds of BIM models. The accuracy and performance are analysed and discussed with the proposed method's limitations. The development of this CNN-based approach marks a stride towards more efficient and data-driven design and construction processes, paving the way for further advancements in automated BIM data validation.

ABSTRACT. In the planning and design of new projects, team members often rely on existing technical documents to make informed decisions. A question-answering system can significantly aid in this process using Large Language Models (LLMs) like GPT-4 for specialized fields such as Architecture, Engineering, and Construction (AEC). However, they face challenges such as inaccurate information retrieval, limited access to domain-specific data, inadequate prompt customization, and hallucinations. This paper addresses these issues by developing a generative question-answering system for technical documents, using retrieval-augmented generation (RAG) and prompt engineering. The system leverages a vectorized database with domain-specific embeddings and employs semantic similarity for efficient passage retrieval. By integrating retrieved domain knowledge into the LLM through prompts, the system aims to enhance the accuracy and relevance of generated information. The expert evaluation compared the developed advisor to traditional search methods including Google and document databases, showing superior performance in all LLM-Assisted evaluation metrics, especially search efficiency.

ABSTRACT. Co-creation refers to the highest level of community engagement in project planning/scoping. Traditional engagement mechanisms tokenized the engagement or focused on information sharing. Advanced engagement approaches engage communities in decision-making, where professionals (such as planners and engineers) design a project based on the profile of community needs and using their technical knowledge. State-of-the-art means for communicating and profiling the community in this type of engagement is to use games designed by professionals. Through developing and using a game, professionals can deliver basic information to citizens more effectively and also solicit their feedback. Co-creation aims to engage the community in innovating/developing the solution itself—not just choosing between already developed designs. The community has local knowledge that is as valuable as the technical knowledge of professionals. Both collaborate to generate new solutions. In this approach, if games are used, then professionals and citizens have to be players. The interactions, profiling and discovery of knowledge must be two-way. IPD brings a similar mentality of collaboration and evolutionary decision-making to the construction industry. All parties share their knowledge and work together to find an acceptable solution to project challenges. Missing in the IPD co-creation model is the engagement of communities. Recently, community concerns and objections have derailed many (large) projects. This research work developed a framework for evolutionary two-way gaming in IPD projects that include citizens (C) as co-creators. First, all stakeholders are profiled through chatting—each is invited to write and debate the needs, the challenges, and what defines a good solution. If possible, the profile is enriched through text mining of reports (published by project teams) or newspaper articles (that typically reflect community issues). Next, a knowledge graph is developed to represent the key concepts of the debates between professionals and citizens. This is combined with a base ontology that represents the most fundamental concepts in the domain. Then, using the above an archetype game is selected for the team based on the specific nature of the project knowledge graph. Finally, a set of games is offered to the team from a repository of games in the platform. In summary, after profiling the project and the stakeholders and using knowledge graphs a set of games is selected for the participants.

ABSTRACT. Building information modeling (BIM) holds the potential to streamline the building energy analysis process by providing geometry, materials, envelope properties, internal gains, and ventilation systems. The IFC (Industry Foundation Classes) standard facilitates data transfer for this purpose. However, the IFC scheme allows information to be organized and represented in different ways, causing interoperability challenges between software and information loss. This study addresses these issues by proposing a methodology for developing an energy modeling data dictionary. Based on the BuildingSmart Data Dictionary (bSDD) methodology, the proposed data dictionary aligns with the IFC schema and incorporates information about the building materials' thermal properties. The proposed structure includes information classification systems and allows for diverse energy code integration. In doing so, the organized and classified information can be mapped to energy analysis software. This initiative resolves current challenges and establishes a blueprint for creating data dictionaries across various domains, expanding its utility beyond energy modeling

ABSTRACT. Building permitting is a complex and often inefficient process due to limited digitalization and automation, for example the interpretation of fire safety regulations. This research addresses these challenges by investigating the reuse of ontologies to improve the building permitting process. The study focuses on aligning domain-specific ontologies, such as the Ontology-based Building Permit Review (OntoBPR) and the Fire Safety Ontology (FiSa), using the Simple Knowledge Organization System (SKOS). The methodology involves identifying potential use cases, analyzing concept similarities, and mapping relationships with SKOS properties. Two primary use cases illustrate how FiSa can be integrated into the building permit review process and used in content checks. The findings demonstrate that a structured approach to ontology alignment can enhance communication among ontology developers and promote the reuse of concepts. This research underscores the need for further investigation to address interoperability issues in general and improve regulatory compliance in construction.

ABSTRACT. The construction industry is characterized by fragmentation due to the distinct phases, as well as the complex structure of the industry itself. The numerous processes involve diverse stakeholders each requiring seamless integration through the accurate transfer of information to maintain its integrity. Different information models both those defined by standards and industry-specific, complicate the choice of models to adopt, impacting interoperability. This research aims to develop a methodology to address this issue by unifying existing ontologies developed for different information models. The approach combines elements of the Modular Ontology Modelling methodology, and the Level of Information Need (LOIN). This methodology is currently being evaluated in collaboration with multiple companies in the Swedish AEC industry as part of an ongoing project. Results suggest using standardized machine-readable data templates, industry accepted data dictionaries and ontologies based on standards enable unambiguous exchange of information along the value chain of a construction project.

ABSTRACT. This paper investigates the symbiotic relationship between Heritage Building Information Modeling (HBIM) and Level of Information Need (LOIN) in the realm of heritage building management. Recognizing the generic nature of Level of Development (LOD) standards in HBIM, we underscore the significance of defining specific information requirements tailored to architects' needs. Employing the ISO 7817-1 standard as a guiding framework, our study focuses on the implementation of LOIN principles in a Moroccan heritage building for pathology diagnosis. First, a literature review on HBIM and LOIN is presented, a case study is illustrated and later results of a survey and interviews are analyzed and discussed. The paper is one of the first publications that shows how LOIN can be applied in HBIM for the erosion aspect of pathology analysis. Despite the current implementation of HBIM among architects in Morocco is very limited, the majority of interviews believes that the LOIN approach can improve effective definition of deliverables to drive more accurate conservation activities. To increase the HBIM maturity in the country, more training and fundings should be provided as well as collaboration between academia, industry and heritage organizations.

ABSTRACT. The construction and operation of buildings accounts for the largest share of both global final energy consumption and energy-related greenhouse gas emissions. However, the construction sector has the greatest potential for significant reductions in energy consumption compared to other large manufacturing sectors. The negative environmental effect in building operations can be reduced by optimizing facility management without having to renovate the building. The approach of optimizing facility management through digital methods, specifically digital twins, is suggested in this paper as a means to mitigate the negative environmental impact of building operations. The main challenge in optimizing facility management through digital twins is not new buildings, but existing buildings. More than 80% of existing buildings in the EU were built before 1990. The typical situation in existing buildings is that a lot of information is missing or very incomplete. This means that there is typically no reliable basis, neither in paper nor in digital form, on which the necessary optimization of facility management can be planned and carried out. This paper reports on the infrastructure requirements and challenges in creating digital twins of existing buildings from the results of a third-party funded project. For the purposes of this research, a digital twin is not only a static BIM model, but also includes real-time and long-term life data of a building. In order to be able to create BIM models for existing buildings, the required information must first be defined as an Information Delivery Manual (IDM), as there are currently no established standards for this purpose. Various methods such as photogrammetry, laser scanning and non-destructive material testing tools are then used to collect the necessary IDM data. To record life data, various sensor technologies are being investigated for use in facility management. A building will be equipped with sensors and linked to the corresponding BIM model to create the desired digital twin. The sensor data and other data such as weather data are stored in the Digital Twin database. Based on the evaluation of sensor data, predictive maintenance, optimized use and space utilization, and an improvement in user behavior should then be possible. As part of the practical knowledge gained, the paper provides insights into the integration and hosting of the different data structures and devices of different technologies. In addition, it provides a framework for optimizing facility management through digital twins as a starting point for future research in artificial intelligence.

ABSTRACT. Current research often focusses on the use of Digital Twins for data collection and visualization and Machine Learning for data analysis to develop prediction models. However, these research lack discussion on how data to develop predictive models/twin needs to be selected and how they contribute to the models’ accuracy and effectiveness. In this paper the authors focus their attention on how the data needs to be selected for the development of accurate and cost-effective prediction models. The paper developed two machine learning models, one containing redundant data and another with redundant data combined as single data points. During testing, both models achieved similar accuracy of 0.86, highlighting that redundant data did not add to the accuracy of the predictive model/twin. The results also show that collection of redundant variables can be eliminated to reduce the cost of data capture and storage.

ABSTRACT. The continuous streaming of data from a sensor network is essential for a digital twin to mirror its physical counterpart in real-time. Missing or interrupted data limits the digital twin functionality but can be difficult to detect when data is communicated at a change of value. . Any disruption in data streaming can compromise building surveillance or lead to overlooked critical alerts. Although setting basic thresholds can sometimes be effective, a more sophisticated approach requires monitoring data counts using statistical methods such as Poisson or Normal models based on either average hourly counts or segmented hourly counts. By understanding the unique streaming patterns of each controller, these models are less susceptible to errors, reducing the incidence of false alarms, ensuring more accurate streaming, and notifying users immediately about any significant deviations from the expected data counts. This paper presents the development of such an approach implemented on a Building Automation System for a large multi-use building, which consists of over 14,000 points for the HVAC systems that report whenever a change of value above a defined threshold is observed. Data is collected from thousands of sensors and gathered by controllers wired to the building's private network. Before transmission to cloud services, streaming software structures the records with appropriate formatting. This data is then archived in a timeseries database for subsequent analysis. The streaming quality model functions in a two-tiered approach. Initially, an appropriate model is determined for each controller. This is accomplished by fitting the count distribution with known statistical distributions, such as the Poisson or Normal distribution. Algorithms like Expectation-Maximization determine the parameters of these distributions. In the subsequent phase, the calibrated models operate in the cloud, assessing on an hourly basis whether the count aligns with the expected range. If deviations exceed a set threshold, an alert is triggered. A case study implementation of this approach for a full-building digital twin is presented, showcasing both the need for and value of this approach.

ABSTRACT. In recent years, the Digital Twin (DT) has become an extremely popular technology in the Architecture, Engineering, Construction, and Operation industry (AECO). Its application benefits not only the design and construction phase of the building life cycle but also the operation and maintenance (O&M), supporting a more efficient facility management (FM). The DT most widespread applications are real-time monitoring, simulation, diagnosis, and performance prediction. DT allows to detect anomalies before they occur and make diagnosis, helping the decision-making process, and thanks to the presence of IoT, to control the conditions of the building, capturing current conditions such as temperature, humidity, noise, and occupancy. Supporting the sustainable transition of the built environment, the main outputs of DT implementation are the improvement of asset performance and building management. However, its application in FM is progressing slowly, largely due to the complexity of buildings, which involve various components. Given the projected scenario, the paper investigates the literature on the digital transformation in FM, identifying the advantages and disadvantages of digital technologies adoption and DT implementations. To outline the most common barriers that slow down this digital transformation in the FM market, the research develops a set of questions to collect opinions from a survey to FM operators. The study represents a preparatory investigation to compare academia and industry experiences on the introduction of digital technologies in the built environment during O&M.

ABSTRACT. The lack of clearly defined and validated information requirements in model-based projects significantly limits the benefits of Building Information Modelling (BIM). This study addresses this issue by examining the Information Delivery Specification (IDS), a new open standard developed by buildingSMART for specifying exchange information requirements in BIM models. Drawing upon the Brazilian Standard for BIM Objects, which is still under development and aims to establish requirements for BIM object creation based on various model uses, this paper presents an approach to using the IDS standard to encode attribute requirements related to model uses. The research employs the ABNT Standard for BIM Objects as a foundation and demonstrates how it is possible to use IDS to bridge the gap between the model use-based requirements and the IFC schema, that is based on object types. The results indicate that employing open standards like IDS enhances information management efficiency throughout BIM project workflows, promoting more reliable data exchange and coordination. This study contributes to the ongoing efforts to optimize BIM implementation by providing a structured and automated approach to defining and validating information requirements.

ABSTRACT. Road infrastructure is a complex system of heterogeneous subsystems that influence each other. Due to their different characteristics, the individual subsystems road and bridge are often considered separately during their operation. Thus, effects resulting from the interaction between the subsystems can only be analyzed manually and with a high curatorial effort for specific assets. Therefore, the management of the individual subsystems can benefit from a comprehensive, overarching data management of all subsystems. This paper presents how to enable cross-domain analysis of roads and bridges using graph-based representation of legacy data. The approach permits the consideration of specific granularities and focuses primarily on mapping the different spatial reference systems, enabling the implementation of location-based queries across different subsystems. To validate our approach, we demonstrate the application based on real-world data from the German infrastructure administration.

ABSTRACT. The paper assesses the information delivery specification (IDS) and tries to identify functional and non-functional aspects of IDS implementations. IDS is becoming an essential tool for the consistency, accuracy, completeness, and reliability of project information throughout BIM project delivery. Through a review of IDS, its implementations in selected solutions, we use a process centred method for the identification of advancements and gaps that may serve as input to continual improvement of project information requirements management. We also propose criteria for the assessment of IDS, we explore checkability of requirements, and expose the potential of historical data from past compliance checks. The results were obtained based on real-world case study with in-depth analysis of practical applicability of automated information compliance checking, in addition, we analysed IFC mapping issues and workflows, and summarised findings in the SWOT matrix. The research may contribute to a better management of information requirements and to the automation of compliance checking. The results offer some valuable insights for practitioners and developers or researchers working on the quality and reliability of information in BIM models.

ABSTRACT. Graph is potential for building information storage and query. A new graphical representation of IFC (Industry Foundation Classes) data has been developed, referred to as IFC-Graph. However, many aspects are not clear about querying information from this graphical IFC data. This study aims to explore the query of information from IFC-Graph by using graph query language. One IFC model was converted into IFC-Graph and used for validation. Experiments were carried out to query individual instances and their relations by using Cypher. The results show that a) IFC-Graph can support building information query, b) Cypher can be used to query individual instances and the complex relations between instances, such as spatial structure and space boundary. C) Cypher is more efficient in query relations compared with IFC parser. This study can contribute to digital twin development and usage by providing an effective way for building information query.

ABSTRACT. The Architecture, Engineering, Construction, and Operation (AECO) industry is beginning to explore the potential of Digital Twins. These applications range from prototyping to simulations, incorporating technologies like Building Information Modeling (BIM), the Internet of Things (IoT), and Artificial Intelligence (AI). The industry is at an early stage of Digital Twins maturity, focusing on integrating dynamic, predictive, or simulated data. However, there’s ambiguity regarding advanced Digital Twins, with terms like cognitive, prescriptive, autonomous and intelligent Digital Twins used inconsistently. This research aims to clarify and standardize terminology and understanding of next-generation Digital Twins, focusing on the last two maturity levels. This research will provide AECO practitioners with a comprehensive understanding of these advanced Digital Twins, guiding their selection based on specific needs and advancing research for more accessible and cost-effective Digital Twins while maintaining functionality. Ultimately, this research aims to unlock the full potential of Digital Twins in the AECO industry.

ABSTRACT. Digital twins have emerged over the last decade as a potential solution to enable the monitoring and improvement of several aspects of built assets across the different stages of their lifecycle. The services offered by digital twins include comfort, energy consumption, air quality, and security, among many others. Their development has required addressing significant challenges related to different aspects of the digitalization of built assets, including integration of heterogenous data from different sources and device types, data security and secure access to guard against unauthorized access and cyber-attacks, and deployment of software components on heterogeneous execution platform/environments composed, for example, of IoT devices and cloud. However, little emphasis has been placed so far on the iterative development and evolution of digital twins to adapt to ever changing environments, while responding to evolving user requirements and objectives.

In the field of software engineering and digital transformation, DevOps has established itself over the last decade as the leading paradigm to improve software processes. This approach has allowed software organisations to increase their agility to adapt to constantly evolving environments to deliver solutions faster, with higher quality, and that are adaptable to user needs. DevOps aims at integrating the development (Dev) and operations (Ops) phases into a seamless, end-to-end, continuous process flow, and emphasizes continuous integration and delivery, as well as quick feedback loops. It enables continuous improvement through automation and monitoring at every stage, from design to deployment, including planning, development, testing, integration, release preparation (building/packaging), and monitoring. Its adoption by industry leaders such as Amazon, Netflix, Google, and Facebook has led to spectular progress.

This paper proposes a DevOps approach for the development and evolution of digital twins for built assets. It leverages best-practices in software engineering and DevOps to support the systematic development, deployment, and monitoring of digital twins. The approach focuses on three main aspects: 1- DevOps infrastructure to automate the continuous integration (CI), deployment (CD), and monitoring of digital twins; and 2- software/system architecture, based on microservices, to enable the independent development and composition of different aspects of built assets (e.g. comfort, energy consumption, air quality, and security); and 3- methodology to support the systematic and iterative development and evolution of digital twins to adapt to continuously changing environments, requirements, and needs. The development of the proposed approach is based on experience gained in the development of various digital twins of existing built assets.

ABSTRACT. The facility and asset management (FAM) industry faces significant challenges in optimizing building energy consumption and Heating, Ventilation, and Air Conditioning (HVAC) system efficiency amidst increasing energy load demands and global climate variability. This paper addresses the industry shift toward operational technological solutions like digital twins (DTs) that harness predictive and analytical capabilities. The focus of this research is on determining the steps required in integrating the predictive and analytical capabilities of machine learning (ML) models into DT platforms to forecast energy consumption and enhance HVAC system optimization in the built environment. This study employs a review of the literature and develops a framework that merges ML models with DT platforms using Application Programming Interfaces (APIs). The proposed framework consists of data extraction, predictive analytics, and data ingestion layers. The findings demonstrate that ML integration in DT platforms can forecast building energy consumption and other relevant performance parameters. By conducting a comprehensive literature review and developing an integration framework, this research shows that the convergence of ML and DTs can enhance energy efficiency and sustainability by facilitating dynamic energy management strategies in the FAM industry.

ABSTRACT. Information Modelling and Management (IMM) can promote the digital and green transition of construction Public Procurement through the definition of environmental awarding criteria and bids compliance checking during the call for tender. The research proposes a model-based, open-source approach for managing and reducing waste quantities starting from the tendering phase. An Italian Design-Build (DB) procurement is exploited as significant case study to test the methodology. The paper shows how current bids evaluation process was mapped and redefined through BPMN 2.0, identifying the parameters for waste quantities through the IFC standard. Then, user-friendly interactive dashboards were developed for visualizing and comparing bids scores. A data-driven and semi-automated evaluation procedure is provided, enabling tendering procedure streamlining, transparency, and sustainability enhancement.

ABSTRACT. Building Information Modelling (BIM) is a driving force for automated building permit checking. There is a consensus among the industry that the use of open data standards is crucial to this process. The Industry Foundation Classes (IFC) open data standard provides a good base for automated permit checking worldwide. It has a large semantic definition of classes (objects/entities) being supported by almost all software tools in the Architecture, Engineering and Construction (AEC) domain. The use of IFC has technically been proven to be useful and efficient for digital building permit checking. BIM modelling according to data requirements in IFC is a crucial factor for trusted results. However, there is a growing number of examples where the delivered IFC datasets are inconsistent or have missing information leading to unreliable results of automated code compliance checks. For example, providing values for properties inconsistent with the geometry representation can lead to a false positive result in a digital building permit check. The lack of sufficient information can result in checks not being executed during the digital permit checking procedures. Therefore, this paper explores measures to improve the information reliability of BIM models for automated building permit checking processes. The paper provides industry examples and risks of inconsistent IFC requirements. Evaluation results of known solutions to check IFC datasets without assuming semantic reliability are presented. The paper concludes with recommendations for government organisations, architects, engineers and technology providers.

ABSTRACT. Designers must investigate solutions that represent the best trade-off between the results of different design options. This entails a quantitative assessment of safety levels. Key Performance Indicators (KPIs) facilitate this assessment by providing a clear and concise visualization of safety levels in buildings. This paper concerns fire safety design of buildings, focusing on the structural components’ fire resistance. Technically, we developed a framework, integrated in a BIM environment, to implement performance-based assessments of structural elements, ensuring that fire safety objectives are met. Fire safety performances are tracked by means of a KPI identified for its representativeness. The visualization of the KPI in BIM models highlights critical elements and enables a quick refinement of design solutions. The outcome is a BIM information-rich model handed over to facility managers, to track the performances of structural components and timely implement renovation actions in the use phase of buildings.

ABSTRACT. An Environmental Impact Assessment (EIA) is a planning and decision-making tool utilized to assess the potential positive and negative effects of proposed construction projects on the environment. EIA helps decision makers to identify and assess potential impacts early on, during a project's planning stage. Risks of construction activities on the human health and risks of harming the environment can be reduced by identification of the adverse environmental impacts and implementation of mitigation measures. Environmental aspects are categorized into nine domains, including: air emissions; water emissions; waste generation; use and contamination of land; resource consumption; local issues; transport issues; effects on biodiversity; and incidents, accidents and potential emergency situations (EMAS, 2001). The local issues include, but are not limited to, noise, vibration, dust, odour, and visual appearance. Each of these factors poses distinct challenges, from noise and vibration affecting the well-being and comfort of nearby residents, to dust and odour compromising air quality and public health, and visual appearance impacting the aesthetic and cultural value of communities.

Local issues are a significant source of environmental impact for numerous construction projects, as highlighted in the literature review. Current approaches to managing local environmental issues face several limitations that hinder their effectiveness. A notable absence of standardized protocols and procedures exists for conducting thorough noise, vibration, and dust analyses, as well as for proactively implementing mitigation measures at the design stage of the construction projects. This lack of established norms contributes to uncertainties and inconsistencies in assessing and addressing these environmental concerns pre-emptively. Furthermore, several research efforts have concentrated on the prediction and mitigation of the construction local issues, such as noise by providing sophisticated management approaches and simulation techniques (Kwon et al., 2016). However, there is a need for practical and user-friendly impact simulation tools.

A thorough examination of the existing approaches reveals significant shortcomings in conducting environmental impact assessments, notably the underutilization of advanced computational and analytical technologies. The implementation of Building Information Modeling (BIM) techniques is poised to transform how environmental studies are conducted. However, there are a few research works benefiting from the integration of the BIM tools and local issue assessment. BIM simplifies the process of managing, and data sharing, and aids in integrating mitigation strategies during the planning, construction, and the operational phases of a project. BIM also supports the decision-making process through modeling, visualization, and simulation techniques, enhancing the EIA process (Najjar et al., 2017). On the other hand, 2D and 3D BIM models facilitate initial screenings and scoping phases but are inadequately equipped for comprehensive preliminary and full environmental assessments, which demand a nuanced incorporation of temporal changes. The full environmental assessments necessitate more in-depth 4D analysis to incorporate temporal variations (Ismaeel and Lotfy, 2022).

This paper aims to evaluate the current theories and practices employed in assessing local environmental impacts within construction projects, with a particular focus on the utilization of EIA tools and approaches. The limitations of current EIA practices in effectively managing local environmental issues are identified and analyzed. A comprehensive understanding of the challenges and limitations faced by current EIA methodologies in addressing local environmental issues in construction projects, contributing to the body of knowledge in environmental management and construction studies. In addition, the potential of BIM techniques and 4D simulation in enhancing the effectiveness and comprehensiveness of environmental impact assessment is examined. The paper seeks to contribute to the enhancement of EIA practices in construction, ensuring that environmental considerations are more effectively integrated into project planning and execution processes.

References European Union. Regulation (EC) No. 761/2001 of the European Parliament and of the Council of 19 March 2001. allowing voluntary participation by organisations in a community eco-management and audit scheme (EMAS). Ismaeel, W.S. E., and Lotfy, R. A. E. (2022). An integrated building information modelling‐based environmental impact assessment framework. Journal of Clean Technologies and Environmental Policy, 25:1291–1307. Kwon, N., Park, M., Lee, H. S., Ahn, J., and Shin, M. (2016). Construction noise management using active noise control techniques. Journal of Construction Engineering and Management, 142(7):04016014. Najjar, M., Figueiredo, K., Palumbo, M., Haddad, A. (2017). Integration of BIM and LCA: evaluating the environmental impacts of building materials at an early stage of designing a typical office of building. Journal of Building Engineering, 14:115–126.

ABSTRACT. The integration of the GIS and BIM domains attracts unbroken attention in research, because using data from the two worlds in conjunction promises better use of the data, more comprehensive insight and holistic analysis. With the integration of the two domains' data, new use cases become feasible, which are not within the realms of the single domains. Researchers have previously studied various operational modes of integration, from conversion, linking, to interconnected retrieval or generic integration method. Besides a particular integration method, most of the works are also dedicated to a particular pair of schemas, predominantly and most notably the pair of buildingSMART's IFC for digital building models and OGC's CityGML for 3D city models.

Many works highlight the differences between the BIM and GIS domains and contrast them by example of these most prominent schemas of each domain. However, despite standardization efforts, in reality the data and information modelling landscapes of the domains in themselves are not as homogeneous as they appear in the light of such study. There are subdomains within each the BIM and GIS domain with different views and representations of the built environment as well as varying approaches to modelling, ecosystems of tooling for data acquisition and management - and therefor also more than one pertinent standard in each domain. Thus, integrating pairs of schemas is not sufficient, we must extend the horizon by looking at how to integrate more than two schemas.

In this paper we present a study on a use case driven approach to integrating multiple schemas, namely IFC, CityGML, IndoorGML and OpenStreetMap. Instead of a generic integration, at this point, we look only at a specific operational mode of integration which is conversion from building models into data sets for city maps and navigation services. This is guided by the practical aim of a feasibility study carried out recently: how to enhance and extend city maps and navigation models with indoor information originating from planning processes.

Simply lumping together isolated pairwise considerations can certainly cover the ground of the various facets of both domains, but not assure consistency overall. It seems likely that compared to pairwise model integration, with multiple models, complexity increases substantially and even subtle inconsistencies between two models potentiate to significant impact. The study was conducted as an experiment to get a first heuristic understanding of the increase in complexity, to identify and try-out different viable methods of forming sub sets or super sets of the models, or complementary structures to the models. These identified model pieces are then to assembled in an intermediate model in order to facilitate the conversion via a mediating step.

The full paper will describe the identified mediating model elements, demonstrate the details of the intermediate model and how it bridges the partially contrasting modelling paradigms of IFC and the target formats. We also show the implementation of the conversion from the digital building model to the intermediate model and simultaneous identification of model requirements. The proof-of-concept implementation has been tested with a set of sample data and we show the results. We discuss the limitations of the study, challenges and opportunities to develop a more formal approach to multiple schema integration which also takes into account the different operational integration modes beyond conversion.

ABSTRACT. Construction projects frequently face delays, presenting significant challenges to effective project management. Identifying the causes of these delays and determining which stakeholders are responsible for addressing them is crucial for effective mitigation. While progress reports from construction sites offer valuable insights into project status, they are primarily used for contract management. Consequently, despite containing crucial data on project delays, they are often underutilised for delay management. Moreover, manual comprehension and analysis of these reports further complicate the identification of delay causes, hindering thorough analysis. To address this issue, this research proposes an automated delay inference method using natural language processing (NLP) techniques. By leveraging large language models (LLMs), the aim is to extract critical project information, including delay causes, from 44 weekly progress reports. These causes are then categorised based on their location and nature. Finally, a flowline diagram is generated to visualise the planned and actual construction programmes. The gaps between them are explained by the identified delay causes and their impact on project completion, providing instant insights for effective decision-making. This approach aims to enhance the accuracy and efficiency of delay analysis in construction projects, ultimately improving project management.

ABSTRACT. Nowadays construction scheduling relies on enrichment of BIM objects with additional attributes commonly expressed as time scheduling and cost estimation parameters. Typical approaches based on the assignment of static attributes present some limitations because this kind of information cannot manage the assignment of a BIM object to multiple activities based on its involvement in multiple construction processes. Instead, an approach based on interrelated information classes allows the application of robust procedures and standardized data models. The study examines the possibility of using IFC classes both as product and process models which can be correlated according to standardizable procedures. At the same time, grouping and assigning works to digital process models makes it possible to use knowledge graphs and RDF. Additionally, IfcOWL ontology maintains IFC standardization. This aspect is essential to avoid the creation of new ontologies. Besides in the AEC Industry, real-time information coming from various sources is quite typical. As a result, cloud collaboration based on linked data models (LDM) is becoming a reference to support collaboration among different stakeholders. Moreover, it is possible to use libraries of predefined process templates related to openBIM databases. This article demonstrates how IFC protocols solve typical inconsistencies of modeling with not standardized time scheduling and cost estimation parameters, keeping the potential of LDM but offering an already operational and implementable standard rather than relying on the definition of new cost or process ontologies.

ABSTRACT. In the early phases of construction projects, initial client-set durations often face challenges due to evolving project dynamics. Despite extensive research on accurate planning, practical case studies indicate shortcomings in early-phase predictions, with analytical planning methods underutilized despite technological advancements. This study investigates analytical methodologies used in research for master scheduling in construction projects, aiming to identify gaps and potentials for further research. A systematic literature review of 386 relevant sources categorized methodologies into statistical analyses, extrapolations, predictive techniques, and optimization methods. While statistical analyses are prevalent, predictive methods and optimizations are less explored, indicating a need to adopt advanced analytical methods for robust master scheduling models in construction projects. Addressing comprehensible methods at an advanced analytical level is crucial for enhancing effectiveness and applicability in this context.

ABSTRACT. The construction industry has abundant data but lacks sufficient actionable information. Deriving such information is crucial for addressing one of its primary challenges: insufficient productivity. This paper presents a workflow to extract, analyse and present available productivity data on sites in a consistent manner. It was demonstrated using data from structural frames of 11 buildings, totalling 116 floor levels. Seventy-five percent of the levels were found to spend over 3 worker-hours per m2 of floor area on average. Additionally, most buildings exhibited cubic learning curves, showing performance improvements in mid-levels due to worker familiarisation. However, unlike previous studies, all the buildings demonstrated significantly poorer labour productivity towards the end. This might be due to not minimising the workforce proportionally to reduced work, coupled with complexities in logistics and design on higher levels. While having a learning curve does not signify good performance, its shape was found to reflect labour management practices on projects.