Next Article in Journal
Cyclic Behavior of Partially Prefabricated Steel Shape-Reinforced Concrete Composite Shear Walls: Experiments and Finite Element Analysis
Previous Article in Journal
Enriching Building Information Modeling Models through Information Delivery Specification
Previous Article in Special Issue
A BIM Package with a NEC4 Contract Option to Mitigate Construction Disputes in the Kingdom of Saudi Arabia
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Conceptual Framework of Information Flow Synchronization Throughout the Building Lifecycle

by
Christopher-Robin Raitviir
* and
Irene Lill
Department of Civil Engineering and Architecture, Tallinn University of Technology, 19086 Tallinn, Estonia
*
Author to whom correspondence should be addressed.
Buildings 2024, 14(7), 2207; https://doi.org/10.3390/buildings14072207
Submission received: 13 June 2024 / Revised: 12 July 2024 / Accepted: 15 July 2024 / Published: 17 July 2024
(This article belongs to the Special Issue BIM Application in Construction Management)

Abstract

:
The construction industry’s reliance on traditional methods and fragmented workflows results in significant information loss, inefficiencies, increased costs, and errors. This study addresses these issues by integrating comprehensive urban planning with building information modeling (BIM) to create a seamless information flow throughout the building lifecycle. We propose a holistic framework that synchronizes data from planning to demolition, incorporating national and municipal digital twins. An imperative literature review and analysis of international best practices were conducted to develop a conceptual framework aimed at improving data accuracy and interoperability. Our findings underscore the importance of adopting open standards such as Industry Foundation Classes (IFC) and CityGML for effective information exchange. By implementing an information model (IM)-based approach in urban planning and public sector permit processes, project timelines can be streamlined, and regulatory compliance enhanced. This study concludes that continuous, integrated information flow facilitates more efficient, cost-effective construction practices and improved decision-making. Furthermore, this research illustrates the potential of digital twin technology to revolutionize the construction industry by enabling real-time data integration and fostering stakeholder collaboration, ultimately offering a robust framework for practitioners, and significantly enhancing the efficiency and accuracy of construction processes.

1. Introduction

Information loss in the construction industry is a significant problem primarily because it leads to inefficiencies, increased costs, and errors in construction projects. The fragmented nature of the industry, with multiple stakeholders and phases, often results in miscommunication and inaccurate data passed from one stage to the next. Additionally, the reliance on traditional methods and resistance to adopting new technologies can exacerbate this issue. To address it, previous research has focused on developing integrated digital solutions like building information modeling (BIM), which allows for better data management and collaboration. The primary focus of previous research has centered on the design phase of the building lifecycle, with extensive research into the use of digitally machine-readable information for rule checking started by Eastman et al. [1], which has extended over more than 15 years. Currently, it has been recognized that BIM can be beneficial for building permits by preventing information loss that occurs when digital information is converted to 2D drawings for the public sector permit process [2]. There are also several practical implementations of BIM-based permit processes, for example in Dubai, Estonia, and Geneva. Development of these began in 2020–2021 [3] and was fully implemented between 2023 and 2024. Efforts have also been made to integrate BIM with Geographic Information System (GIS) [4,5] and Lifecycle Assessment (LCA) tools [6,7] to track and manage information throughout a building’s lifecycle. Previously, the operational phase of the building lifecycle has been thoroughly researched, with integrations between BIM and GIS being notably highlighted with facility management (FM) contracts [8]. The problem lies with the data flow model. For seamless information flow, gaps leading to information losses need to be addressed. Almost all referenced research focuses on a small, fragmented part of the building lifecycle and does not integrate this with the previous and future steps; therefore, a holistic overview of the information flow is missing. The novelty of this work lies in its holistic approach, integrating comprehensive urban planning with BIM and digital twin technologies from the initial planning phase through to demolition. This integrated framework aims to ensure seamless information flow, enhance data interoperability, and improve decision-making across the entire building lifecycle while addressing gaps identified in previous studies that predominantly focus on isolated lifecycle phases. Excellent examples of information loss have been described in the academic literature by Eastman [9] and Borrmann [10], with illustrations and examples of the gaps in information flow. However, the foundation of the building lifecycle—urban planning (comprehensive plans and detailed zoning plans)—has not been thoroughly considered in the model. Additionally, the model lacks information exchange within public sector processes such as building permits or certificates of occupancy, as well as connections with national and municipal databases. The “MacLeamy curve” [11] illustrates the cost implications of decisions made in later phases but begins with the pre-design rather than the urban planning phase. Extensive BIM framework analysis has been made by Bilal Succar [12], where all the connections between different stakeholders are clearly indicated, but even there, the urban planning stage and necessary connections with public sector databases are missing.
This paper focuses primarily on the initial stages of the construction lifecycle, specifically the integration of comprehensive plans and detailed zoning plans into the building information model. This novel approach aims to address the gap in existing research and practices, which have predominantly concentrated on the construction and operational phases, often neglecting the foundational role of urban planning as the starting point of lifecycle information. The objective is to explore how information model-based planning can enhance the logical exchange of interoperable and trustworthy information throughout the building lifecycle and its integration into a cohesive framework. In the context of urban planning and BIM, an information model (IM)-based planning approach serves multifaceted functions. It integrates diverse datasets into a comprehensive framework to support decision-making, planning, and management of urban environments, facilitating the creation of detailed 3D city models that incorporate geospatial data and other relevant urban information [13,14]; in addition, this approach enhances the planning and operational efficiency of urban spaces and allows the verification of compliance with planning requirements during the approval process. Proposing a conceptual framework for synchronizing information throughout the building lifecycle introduces a new paradigm. It suggests a holistic approach to managing near-perfect data transfer, beginning with planning and extending through construction to demolition, in synchronization with national and/or municipal digital twins. This represents a significant departure from solutions currently prevalent in the industry. By aiming to facilitate an uninterrupted exchange of interoperable and reliable information, this and further related research directly contribute to mitigating issues of cost, efficiency, and errors in projects due to data loss, potentially leading to more efficient and cost-effective construction practices. The hypothesis is that public sector permit processes—from enforcing plans to issuing certificates of occupancy, which are currently the least digitized and rely on non-machine-readable formats—can significantly benefit from the proposed model. This could result in more efficient and error-free permit processes, significantly impacting project timelines and regulatory compliance.
The aim of this paper is to investigate the state of the art in digital construction research and identify gaps and obstacles in achieving smooth information flow. Based on analyses of research, practical models, and international best practices, a research plan, hypotheses, and a conceptual framework for conducting the research are established.

2. Methodology

To address the identified problem, an imperative literature review was conducted, examining the expansive topic of information flow and the lifecycle within the construction and urban planning sectors. Using carefully selected keywords explained in Figure 1, searches were performed using the PRISMA method (Preferred Reporting Items for Systematic reviews and Meta-Analyses) [15], focusing on titles, abstracts, and keywords.
Overall, 4548 articles from the period of 2016 to 2024 were retrieved. Initially, the time frame of 2020–2024 was utilized. If the returned results were less than 200, the period was adjusted to 2016–2024 to provide additional insight. In case too many articles were returned, the search was constrained by research area and keyword limitations to be more subject-specific. Subsequent screening based on the title, abstract, introduction, and conclusions narrowed the selection to 213 articles, which were stored in the Mendeley Reference Manager. Further meticulous content analysis finalized a selection of 56 significant articles for thorough investigation in the context of this research, ensuring a rigorous scope and relevance. Additionally, papers that were not identified through the screening but known to the authors as outstanding research in the field were considered.

3. State of the Art in Building Life Cycle Information Flow Research

Due to the broad scope of this research, which aims to provide an integrated picture of the information flow within the building lifecycle, the literature review is divided into the following subsections: urban planning, design and permits, construction, facility management, and digital twins.

3.1. Urban Planning

Urban planning is specifically emphasized, as this stage has not been thoroughly integrated into the building lifecycle information flow model. Previous research often categorizes the term “planning” as a subphase of construction design and fails to include city comprehensive plans and detailed zoning plans into the building lifecycle. Urban planning must be recognized as the foundational stage of the building lifecycle, as in this phase the initial information about the built environment is created, incorporating an asset of existing data such as utility networks, greenery, and transportation systems. Unfortunately, much of this information is not utilized effectively in terms of digital, lossless information flow. This inefficiency is largely because urban planning is still mostly conducted within a 2D non-machine-readable realm. Kalogianni et al. [16] have noted that the traditional approach to spatial planning is slow and prone to errors. In the cited research, the Land Administration Domain Model (LADM) is introduced to describe the spatial development chain, with suggestions for standard revision. LADM, implemented in ISO 19152, has been recently updated to its second edition [17]. Part 5—Spatial Planning and Part 6—Implementations—which are important regarding IM-based urban planning—are still in development [18,19]. LADM has been analyzed in a Croatian case study for land types and properties [20], marking a positive step toward IM-based urban planning. However, urban planning encompasses more than just spatial profiles and land uses. In addition to buildable areas, there are restrictions by nature, heritage, and climate protection zones; transportation layers; utility networks; greenery information, etc. Much of this data gain additional value when represented in 3D rather than 2D; however, it is crucial not to focus solely on the 2D vs. 3D distinction but to consider the importance of information embedded within these layers, which can bring significant value in later stages of the building lifecycle. To effectively capture this information, it is essential to apply an industry-approved standard format during its creation, such as Industry Foundation Classes (IFC) in ISO 16739 [21]. IFC is widely valued as a key facilitator for enhancing decision-making and delivery processes for buildings and public infrastructure assets throughout their entire lifecycle [22]. Guler [23] proposes alternative open standard-based options, such as CityGML [24], supplemented by CityJSON [25] for encoding the XML schema, to enhance efficiency in GIS tools. Different well-argued standards clearly demonstrate the need to investigate practical workflows of urban planning architects and to consider the next steps in the building life cycle. Therefore, the authors propose to draw a line between comprehensive plans that are most efficiently made with GIS tools and detailed zoning plans that can beneficially utilize BIM tools to be exported to IFC for further use in later design phases. One example would involve using IM planning within a BIM-based building permit process to compare construction designs against detailed zoning plan information through automated rule checking [26]. IM-based planning might be a very efficient and much-expected paradigm change in the context of seamless information flow; however, it cannot be implemented without challenges. The high expectations for IM planning are unlikely to be met without acknowledging the experiences of municipal planners and the broader changes required in planning culture, including the transition from traditional paper-based methods to IM, which necessitates a shift in planners’ mindsets, skills, and comprehensive discussions on its impact on planning quality and practices [27]. Lastly, significant integration between existing databases and IM-based planning is needed to mitigate information loss and duplication. Kalogianni et al. [28] propose a web-based system that includes data sourcing, processing and validation, storage and management, dissemination, and visualization. This model considers existing databases as data sources. Yet, it is limited to land administration systems due to the scope of the research and does not address the need for two-way information exchange with existing databases in the planning process. Such an exchange is crucial for reusing information in subsequent steps of the building lifecycle without duplications.

3.2. Design and Permits

After the enforcement of the detailed zoning plan, the following construction design phase is one of the most extensively researched areas, with the scientific literature unanimously highlighting BIM as the key component to mitigate information loss between the different stages: planning, preliminary design, and detailed design. Despite several inhibitors affecting BIM adoption, such as a missing holistic approach and limited knowledge of necessary changes [29], BIM adoption is globally on the rise. Stakeholders in the Architecture, Engineering, Construction, and Operations (AECO) industry rate their skill levels as rather high, particularly in North America, Oceania, Middle East Africa, and Europe [30]. Obtaining a building permit is an obligatory milestone in the construction design phase. The permit process, still predominantly based on 2D paper drawings or, in some cases, electronic drawings in PDF format, is a major contributor to information loss even though this gap could be easily addressed by implementing BIM technology to enhance transparency, efficiency, and reduce information loss through digitalization. The entire process, including all systems and components, must be considered, not just technology-driven alone [31]. Transition to BIM adoption for the public sector stakeholders responsible for building permits requires thorough analysis and implementation at the organizational level, encompassing the stages of initiation, planning, execution, and evaluation [32]. Automating the traditionally error-prone manual checks against the building code is one of the best examples of reusing information created in previous stages, such as urban planning and the design phase, by comparing designs against planning requirements. Noardo et al. [33] suggest using the IFC schema for compliance checking through a bottom-up approach within organizations to address end-user needs and highlight gaps between the theoretical and practical usage of the schema. Despite that, a top-down approach should precede the bottom-up approach to address the necessity for change and ensure management support. In contrast, Ismail et al. [34] propose using native formats such as Autodesk Revit to avoid challenges associated with IFC conversion. While this might simplify the designer’s workflow, the authors of the paper consider the use of open standards like IFC as the only viable approach for the entire lifecycle of building information flow with the aim of avoiding data losses. It is essential to mention that BIM is not only about IFC or other file formats or data schemas but mostly about information management. For automated compliance checking, information sources such as data sheets, datasets, and other documents are also necessary. The information stored in these sources should be as standardized as possible to prevent additional data loss or duplication. At a technological level, this approach is vital to break away from monolithic software tools and move toward adopting an ecosystem architecture that consists of multiple services operating with provided information as described by Beach et al. [35]. At the organizational level, automated compliance checking might have some negative impacts, such as the cost of software solutions, staff training needs, and the requirement for powerful hardware [36]. These impacts could be mitigated through web-based solutions and simple user interface principles provided by the public sector entity, like the owner of the building permit procedural environment or the national building registry. This approach serves the interest of obtaining quality information for public databases and increasing productivity in the AECO industry.

3.3. Construction

During the construction phase, a significant amount of previously created information is needed, particularly quality information from the design phase. Changes and delays during this phase can be very costly because the opportunity for effective decision-making typically occurs at the beginning of the design phase. Studies have shown that problems in data quality cost the global economy USD 1.8 trillion annually and are directly responsible for 14% of rework during construction, which could be avoided by preventing information loss and improving data quality [37]. Unfortunately, the literature does not focus enough on this issue, often highlighting the benefits of using BIM in specific aspects of the construction stage or relying on the literature reviews [38]. In addition to the extra costs, there is a significant waste of time due to information problems, which can account for up to 59% of the total time used in the construction process [39]. Despite the fact that the use of BIM can drastically reduce the costs associated with changes on building sites [40], more emphasis is needed on standardizing information flow. The narrow application of information technology is insufficient to address the problems of information quality and accessibility effectively. As a result of the growing market size of offsite construction, including the use of prefabricated elements, the demand for accurate information from the design phase has significantly increased. This information is essential for simulation and the use of robotics in the assembly process [41]. Considering that construction has a remarkably high accident rate, the example of information collaboration between different stages of the building lifecycle to reduce safety risks, presented by Rodrigues et al. [42], is very helpful.

3.4. Facility Management

Operations and maintenance constitute the longest and most costly phase of the building lifecycle [43]. Therefore, it is crucial to ensure that all vital information about the assets is seamlessly transferred at this stage. BIM is extensively recognized for enhancing building data management throughout the building lifecycle. However, integrating complex FM semantic data presents significant challenges, including the need to stay abreast of rapid technological advancements, align the supply and demand of data, and fully leverage BIM data for decision support [44]. Implementing open standards such as IFC and Construction Operations Building information exchange (COBie) is essential for effective asset information management (AIM) as it ensures long-term interoperability, enables structured data exchange, and supports consistent data validation throughout the building lifecycle, thereby enhancing the efficiency and effectiveness of FM [45]. The increase in cost-effective maintenance for existing buildings—which is particularly important for public sector clients—through integrating BIM and FM while leveraging technologies such as IoT and Big Data is demonstrated by Pavón et al. [46]. This approach can transform outdated public buildings into smart, efficient, and sustainable infrastructures with relatively low investments, enhancing operational efficiency, reducing energy consumption, and enabling the reuse of idle but necessary information. During the FM phase, there is a need to continuously keep AIM information, ideally transferred from the project information model (PIM) up to date. Failure to properly update and manage BIM-FM models can lead to unsuccessful implementation and errors in FM [47]. Although there are many previously highlighted benefits of using open standards, geometric changes in the PIM in IFC format—such as combining or dividing rooms by adding or removing walls, and adding new MEP systems—are almost impossible but extremely vital for FM. Some open-source software, such as BlenderBIM (v0.0.240602), offer minor options for geometric changes but these are insufficient for the needs of FM. Therefore, some information, at least in the architectural discipline, should be updated using native BIM tools. Another issue is the utilization of all the information on site by maintenance workers. If they must perform their tasks using 2D drawings and email content, it disrupts the information flow chain and contributes to a decrease in productivity. The integration of augmented reality in FM enhances BIM’s capabilities by improving real-time visualization, interaction, and collaboration, leading to more efficient maintenance operations and better decision-making throughout the building lifecycle [48].
Another crucial milestone in FM is the partial or full demolition of a building before reconstruction, which marks the final stage of the lifecycle before starting over again. The main issue that needs to be addressed is the significant amount of waste generated during demolition. Integrating BIM with Web Map Service technologies optimizes demolition waste management by accurately estimating waste volume, improving transportation route planning, enhancing efficiency, reducing costs and carbon emissions, and promoting sustainable practices [49]. Additionally, artificial intelligence-powered systems significantly enhance the efficiency and accuracy of sorting and classifying construction and demolition waste through advanced sensors and deep learning techniques, while simultaneously contributing to the optimization of logistics and transportation to reduce costs and save time, leading to substantial cost savings, increased safety, and improved environmental sustainability [50]. Waste management should be proactive rather than reactive; therefore, it must be addressed as much as possible during the design phase to ensure all relevant information for reusing and recycling the materials. Utilizing BIM and LCA in the construction lifecycle, particularly during demolition, is crucial for accurately assessing environmental impacts, maximizing reuse and recycling, and reducing carbon emissions and resource consumption through precise data to support sustainable waste management strategies [51]. The integration of IFC as a universal openBIM format enables the effective management of construction and demolition waste by providing a comprehensive data repository for evaluating waste indicators and supporting sustainable construction practices [52].
Conclusively, it is important to acknowledge that for better decision-making and the creation of the best possible urban environment, the information processed and used in FM needs to flow back to the beginning of the building lifecycle—urban planning and construction design—in the form of open data through public sector digital twins and databases. Therefore, information flow is not one-directional, and to the best of the authors’ knowledge, this point has not been addressed in previous research and needs further investigation.

3.5. Digital Twins

An additional subsection on digital twins was included to elaborate on its relationship with different phases of the building lifecycle. The term “digital twin” (DT) in the AECO industry is being studied increasingly each year, with the number of articles in the Scopus database growing from 29 in 2018 to 847 in 2023. DT in the built environment is like a ”layer cake”, consisting of the DT of the product, building, city, and country, with each layer adding more information but reducing specificity. At the building level, BIM is insufficient for information flow due to its lack of semantic completeness, real-time data integration, and interoperability with IoT and AI technologies, necessitating a DT to provide a holistic, dynamic representation of construction assets for real-time monitoring, simulation, and optimization throughout the asset’s lifecycle [53]. The integration of DTs with existing building management systems (BMS), BIM, and GIS can significantly enhance real-time monitoring and predictive maintenance. This synergy fosters a more dynamic interaction between physical and digital assets, thereby providing actionable insights and optimizing building performance throughout its lifecycle [54]. At the city level, practitioners often assume that a 3D model of the city is its DT; however, a true city digital twin (CDT) offers advanced features such as real-time data integration, two-way human–machine interaction, and autonomous operations, while 3D city models are limited to static representations and basic visualizations. Therefore, it is important to distinguish these terms and avoid misusing the concept of a CDT. Masoumi et al. [55] categorize the maturity levels of CDTs, ranging from simple data gathering and 3D mapping at lower levels to fully autonomous operations and self-management at the highest level, noting that most current implementations are at mid-level maturity, incorporating real-time data but lacking full automation and comprehensive system integration. Therefore, it is important for further research to discover how the inhibitors of achieving higher maturity in CDTs could fully benefit from these systems in a seamless information flow schema. For creating CDTs, Souza and Bueno [56] introduce the term City Information Modeling (CIM) as an integration of BIM, GIS, and up-to-date urban databases. They address the possibility of using open standards like IFC and CityGML for cross-referencing data without information loss but highlight that these standards are not yet sufficiently developed to capture all necessary information from the built environment. In addition to urban databases being up-to-date, data should be open and transparent to avoid limitations in the use of CDTs [57]. As to the use of technologies to implement DTs, the research literature predominantly features small-scale experiments and case studies to demonstrate digital twin applications, revealing a clear gap in showcasing industry-level implementations [58]. As a positive example of larger-scale implementation, Salles et al. [59] highlight that the use of CDT through CIM enhances urban planning from a sustainability perspective by integrating and calculating various sustainability indicators such as passive solar planning, ventilation potential, urban network connectivity, and land use efficiency. Their approach can clearly enhance the quality of information for better decision-making at the start of the building lifecycle—urban planning—where the cost of changes is the lowest. As stated before, it is not only about the technology but the people using it. In the context of CDTs, the importance of a user-centric approach is through public participation embracing the technology that CDT can offer. This concept enables broad citizen participation and collaboration among stakeholders by adopting advanced visualization techniques in virtual and augmented reality, which facilitate better communication, consensus-building, and decision-making in urban planning [60]. Additionally, DTs facilitate enhanced collaboration among stakeholders by providing a shared platform for data visualization and decision-making [61]. Advanced virtual and augmented reality features enable stakeholders to engage interactively with the digital model [62], fostering more effective communication and consensus-building throughout the planning and operational phases.

3.6. Summary of the State of the Art

The literature review highlights the necessity of integrating all phases of the building lifecycle—from urban planning, design and permits, construction, and facility management—into a cohesive, holistic picture. Urban planning is emphasized as the foundational stage, in which initial information about the built environment is created. This information should flow seamlessly into subsequent phases to enhance decision-making and reduce costs, especially given that changes are least expensive at the planning stage. The previously analyzed literature often exhibits fragmentation, with studies focusing narrowly on specific phases without considering the preceding or following stages. This fragmented approach fails to recognize the interconnected nature of the building lifecycle, leading to inefficiencies and information loss. The use of open standards, such as IFC, LADM, and CityGML, is vital for ensuring interoperability and preventing information loss across different stages of the building lifecycle. Even with some highlighted shortcomings in maturity, these standards facilitate the seamless exchange and integration of data, which is essential for creating an efficient and effectively built environment. The adoption of open standards supports structured data exchange and long-term interoperability, enhancing the overall quality of information and decision-making processes throughout the building lifecycle.
To address these gaps, there is a need for research that connects multiple lifecycle phases, ensuring a continuous and integrated information flow.

4. Conceptual Framework

4.1. Disruption of Information Flow

The AECO industry faces significant information loss due to its fragmented workflows. Previous research has primarily focused on individual lifecycle phases, neglecting the integration of urban planning with subsequent stages. The proposed solution emphasizes adopting a holistic digital framework, integrating BIM from the urban planning phase through to operation. This framework should utilize open standards, such as IFC and CityGML, to ensure interoperability and seamless data exchange across all phases. Implementing synchronized digital workflows can mitigate inefficiencies, enhance data accuracy, and reduce costs, ultimately leading to more efficient and error-free construction practices. Figure 2 depicts the suggested information flow diagram, highlighting the differences between conventional, digitally fragmented, and digitally synchronized workflows.
Compared with previous approaches, urban planning stages are added to the timeline, and the digital workflow is divided into fragmented and synchronized sub-flows.
The conventional workflow line (in red) shows a jagged, stepwise increase in information level, indicating significant information loss and inefficiencies between stages. The deepest drops occur between the planning–design, design–construction, and construction–operation phases. The first drop is due to the lack of consideration of planning in the building lifecycle model, while the subsequent drops are largely influenced by the dominant design–bid–build procurement model, which hinders the desired flow of information.
The digital fragmented workflow line (in light grey) provides a smoother but still segmented increase in information level. This suggests some improvements but has persistent gaps in information flow, addressing the outcome of implementing previous research without a holistic approach.
The digital synchronized workflow line (in black) demonstrates a continuous and smooth increase in information level, representing the ideal scenario with minimal information loss and high efficiency throughout all phases. The smooth transition in digital synchronized workflows from “Comprehensive plans” through to “Operation” suggests the benefits of early-stage integration and continuous data management.
The diagram highlights the critical transition points (ovals in light blue) between comprehensive plans, detailed zoning plans, and conceptual design, indicating a significant area where traditional workflows experience information loss and digital workflows have not yet been widely implemented. Consequently, the focus of future research centers on detailed zoning plans.

4.2. Research Focus

Achieving a digitally synchronized information flow is essential to address the disruption of information flow, yet it is not easy to achieve. To tackle this, the proposed conceptual framework for the research, shown in Figure 3, integrates BIM and GIS from urban planning through to operation within governmental and municipal digital twin platforms. Integrating BIM and GIS from urban planning through to operation ensures a continuous flow of information while enhancing spatial analysis and visualization capabilities. This integration significantly improves decision-making processes by providing a comprehensive view of urban and construction environments, thereby facilitating better coordination among stakeholders.
This approach is structured around three key research questions (RQ) and hypotheses (H), which suggest that integrating stakeholders on digital twin platforms, bridging GIS and BIM at the detailed zoning planning stage, and implementing IM-based processes in urban planning and permits will reduce information gaps and enhance data accuracy:
  • RQ1: how can central technical solutions in public sector digital innovation platforms enhance information flow?
H1 posits that bringing various AECO stakeholders onto a shared digital twin platform at the governmental or municipal level will foster better collaboration and minimize information loss. This involves leveraging central databases containing up-to-date, accessible information for analyzing, visualizing, and simulating, which allows for harnessing bits of information into a comprehensive system;
2.
RQ2: how should GIS and BIM processes be coordinated throughout the construction lifecycle, and where is their intersection?
H2 identifies the detailed zoning planning stage as the critical juncture where GIS (used in comprehensive planning) and BIM (utilized in construction design) should intersect, ensuring a seamless transition of data. Detailed zoning plans should be created with tools that enable IFC export, facilitating public participation and the reuse of information in commonly used construction design software. By implementing H1, the transfer toward GIS via the CityGML standard can be implied, allowing detailed zoning plans to be available in both GIS and BIM formats, which will benefit all stakeholders;
3.
RQ3: What changes are needed on the level of governmental information flow management, and how can their impact be measured?
H3 highlights that the current urban planning and municipal permit processes, such as building permits and certificates of occupancy, are major obstacles to the efficient exchange of standardized information due to the need to duplicate information in non-machine-readable 2D formats. By adopting IM-based processes and enabling automated rule checking, these barriers could be conquered and will facilitate lossless exchange of standardized information among stakeholders throughout the building lifecycle.
Future research should consider incorporating Multi-Criteria Decision Making (MCDM) methodologies, such as Multi-Criteria Decision Analysis (MCDA) or Complex Proportional Assessment (COPRAS) [63,64]. These approaches offer a robust framework for evaluating diverse decision-making scenarios, thereby enhancing the precision and efficiency of planning and permitting processes. By employing MCDM/MCDA or COPRAS, the model can systematically evaluate multiple criteria, optimizing the decision-making process within urban planning and construction management.

4.3. Information Flow Scheme

To illustrate the essential integration of information, the following section describes the chart that captures the interaction between different phases and promotes the central role of public sector services. The analyses of the state of the art in Section 3 revealed gaps, fragmentation, and interruptions in current information flow. Based on these insights, the flowchart was built to address these problems. The proposed scheme in Figure 4 delineates an integrated workflow for urban planning, design, construction, and operation using BIM and GIS technologies. It highlights the pivotal role of a digital twin (DT) interface combined with the public sector database (DB) layer and the building owner’s Common Data Environment (CDE). This integration ensures a synchronized digital workflow, facilitating seamless data exchange and enhanced interoperability across the entire lifecycle, as advocated by adopting open standards like IFC and CityGML.
Green and red lines on the figure describe the flow between public sector services and processes, whereas green indicates input from the public sector and red signifies output toward them. Black lines characterize internal movements and interactions between processes and services that might not involve the public sector. Blue lines highlight possible interactions between the owner and the public sector in the DT interface. Numbers on the lines indicate the sequence of information exchange where it is two-directional, and sequence is important.
The process begins with surveys, including geological, dendrological, noise, and environmental assessments, which feed data into either national or municipal DBs. It is vital that these DBs are utilized first to obtain the most valid data, which are then validated on site by the survey conductor. Thereafter, information should be sent back to the DB and reused in other processes via the DT interface. Surveys can also be sub-processes of subsequent phases; therefore, they are not always the initial step but the same principles should be followed.
This information is then utilized in the planning phase, involving the creation of comprehensive plans managed via GIS (CityGML) and detailed zoning plans managed through BIM (IFC). These plans undergo stages of initiation, participation, and enforcement, interacting with the DT and public sector DBs, particularly the Planning Registry, to ensure comprehensive integration and compliance.
The design phase follows, encompassing conceptual design, building permits, and technical design stages, all receiving necessary basic information through the DT interface and providing created data to DBs, particularly building permit information and technical data of the building to the Building Registry. This workflow ensures that the planning and building registries are updated with precise data, facilitating the transition to the construction phase.
In the construction phase, advanced techniques such as 4D and 5D BIM modeling and data capture (e.g., 360-degree photos and laser scanning) are employed. This phase progresses through the as-built BIM to the issuance of usage permits (certificates of occupancy), with continuous data integration into the DT and public sector DBs, ensuring that the Building Registry remains current and accurate.
The final phase is operation, which includes handover and asset information management (AIM) activities. This phase ensures that the operational stage is informed by the latest as-built data maintaining an ongoing feedback loop with the owner’s CDE for adequate data. DT will provide insights for future developments, and through the public sector DT interface, additional contextual data could be obtained. Utilizing the proposed scheme in integration with BIM to manage demolition waste facilitates accurate tracking of material quantities and types, allowing for effective sorting, recycling, and disposal processes, which minimizes environmental impact and maximizes resource recovery. This system ensures that demolition projects are managed efficiently, reducing both costs and carbon emissions.
Overall, the figure illustrates a sophisticated and highly integrated approach to urban development, leveraging BIM and GIS technologies to ensure data-driven decision-making and efficient management throughout the project lifecycle. The DT interface acts as a central hub, facilitating real-time data exchange and integration across all phases and stakeholders, thereby promoting transparency, compliance, and effectiveness. By leveraging public sector data registers, the DT interface ensures compliance with all regulatory requirements and utilizes the most current information for planning, construction, and maintenance activities. The integration of the DT interface with public sector data registers significantly enhances the accuracy and reliability of urban planning and building management processes. This relationship ensures that data from various public records, such as land use, zoning, and infrastructure databases, are seamlessly incorporated into the digital twin. Additionally, the procedural IT environment needs to be integrated with the Planning Registry and Building Registry to reuse the existing information in IM-based permit processes. This integration enables automated rule checking and helps to avoid duplication and human errors in validation.
Comparing the models by B. Succar [12] and the one presented in Figure 3 reveals similarities in their shared goal of improving information flow in the construction industry but significant differences in scope and emphasis. Succar’s framework primarily addresses the maturity stages, implementation steps, and knowledge visualization within BIM, aiming to systematically investigate and classify BIM’s diverse fields. In contrast, our framework integrates urban planning with BIM, focusing on synchronizing the information flow from planning to demolition and incorporating national and municipal digital twins. This approach emphasizes the practical implementation of BIM throughout the entire building lifecycle, targeting specific inefficiencies in public sector permits and regulatory compliance.

5. Discussion

Achieving an integrated and seamless information flow throughout the building lifecycle presents several challenges. This section highlights key obstacles identified during the research, including the handling of static versus dynamic information, the difficulty of embedding existing data into new models, and the varied requirements of different types of developers. By focusing on these critical issues, future research can develop flexibility in the proposed framework and data flow scheme that ensures suitability and enhances the needed accuracy.
One of the primary challenges is managing the flow of static versus dynamic information. Buildings represent static data, whereas elements like trees grow over time, both above and below ground. This dynamic nature necessitates accurate prediction and continual updating of information to avoid future clashes with other structures. For instance, tree roots may interfere with underground utility networks, and their canopies may conflict with building facades. Thus, an integrated model must consider these changes and facilitate real-time updates to ensure ongoing accuracy and prevent conflicts.
Another significant challenge is incorporating existing information, such as utility networks and existing buildings, into new models. This process, often referred to as managing information legacy, is fraught with difficulties. Underground utility networks are particularly problematic because they are not always accurately documented or mapped. Embedding existing data into new BIM and GIS models requires meticulous validation and integration to ensure that the legacy information is both accurate and compatible with new datasets. Inaccurate legacy data can lead to costly errors and rework during construction and subsequent phases.
The AECO industry is characterized by a diversity of developer types, each with distinct information flow requirements. Large public developers, such as real estate agencies and local municipalities, have often the resources to maintain comprehensive information management systems. In contrast, private sector developers, who primarily sell their developments or retain only a small fraction, may not invest as heavily in long-term data management. Single developers, typically building private houses for personal use, have the least complex information requirements. The proposed information flow model must be flexible enough to accommodate these varying needs to ensure that all stakeholders can benefit from integrated digital workflows without being overwhelmed by unnecessary complexity.

6. Conclusions

This paper hypothesizes that integrating comprehensive plans and detailed zoning plans into the building information model can enhance data flow throughout the building lifecycle, starting from urban planning. The principal findings highlight significant data loss at transition points in traditional workflows, the advantages of employing open standards such as IFC and CityGML, and the need for a holistic approach that spans all lifecycle stages. The recommendations advocate for the adoption of IM-based processes in urban planning, providing permits, and the utilization of digital twin platforms to improve data management and interoperability.
Unlike previous studies, this work extends the application of BIM to include the urban planning phase, thereby underscoring its foundational role. It proposes a more integrated approach using digital twin platforms, facilitating a seamless and continuous flow of information, thus enhancing efficiency and accuracy across all phases of the building lifecycle. The novelty of this study lies in its comprehensive framework that integrates urban planning with BIM and DT technologies, which has not been thoroughly explored in prior research. The anticipated outcome of this research is a more efficient and cost-effective construction process, characterized by reduced errors and enhanced regulatory compliance. This study presumes the feasibility of adopting open standards and digital twin platforms among various stakeholders in the AECO industry.
Several limitations have been identified that could impact the successful implementation of the proposed framework. Resistance to change from stakeholders accustomed to traditional workflows presents a significant challenge. Additionally, the disparity in technological adoption and digital proficiency across different regions and stakeholders can impede the framework’s deployment. Substantial initial investments in training, infrastructure, and technology are required, which may not be feasible for all stakeholders, particularly smaller companies or public sector entities with limited budgets. However, the most important limitations are related to data. Integrating existing legacy data with new digital frameworks poses technical challenges, necessitating considerable effort to ensure data accuracy and compatibility. The framework’s effectiveness could be constrained by the availability of open data, as not all regions or stakeholders have policies or infrastructure supporting open data sharing. This lack of open data can obstruct the seamless integration and flow of information essential for the proposed model.
Future research should concentrate on the practical implementation of the proposed framework, addressing potential barriers, and investigating the impact of real-time data integration and automation in urban planning and construction processes.

Author Contributions

Writing original draft, C.-R.R., supervision and conceptualization, I.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Fostering Sustainable University-Industry Techno-Entrepreneurial Collaborations and Innovations in Asian Universities (FOUNTAIN) project (number: ERASMUS-EDU-2022-CBHE-101082309) co-funded by the Erasmus+ Programme and the Housing Decarbonisation Skills for Climate, Health, and Jobs (Skills4Deca) project (number: DIGITAL-2022-SKILLS-03-SPECIALISED-EDU-101123311) co-funded by the Digital Programme of the European Union. The European Commission support to produce this publication does not constitute an endorsement of the contents, which reflect the views only of the authors, and the Commission cannot be held responsible for any use that may be made of the information contained therein.

Data Availability Statement

This research is designed to be published as open-source material and be available for interested parties.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of this study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Eastman, C.; Lee, J.-M.; Jeong, Y.-S.; Lee, J.-K. Automatic rule-based checking of building designs. Autom. Constr. 2009, 18, 1011–1033. [Google Scholar] [CrossRef]
  2. Plazza, D.; Röck, M.; Malacarne, G.; Passer, A.; Marcher, C.; Matt, D.T. BIM for public authorities: Basic research for the standardized implementation of BIM in the building permit process. IOP Conf. Ser. Earth Environ. Sci. 2019, 323, 012102. [Google Scholar] [CrossRef]
  3. Noardo, F.; Malacarne, G. Workshop Report European Spatial Data Research I EUnet4DBP International Workshop on Digital Building Permit DIGITAL BUILDING PERMIT: A STATE OF PLAY. Available online: https://www.eurosdr.net/sites/default/files/uploaded_files/eurosdr_eunet4dbp.pdf (accessed on 5 May 2024).
  4. Liu, X.; Wang, X.; Wright, G.; Cheng, J.C.P.; Li, X.; Liu, R. A State-of-the-Art Review on the Integration of Building Information Modeling (BIM) and Geographic Information System (GIS). ISPRS Int. J. Geo-Inf. 2017, 6, 53. [Google Scholar] [CrossRef]
  5. Fonsati, A.; Cosentini, R.M.; Tundo, C.; Osello, A. From Geotechnical Data to GeoBIM Models: Testing Strategies for an Ex-Industrial Site in Turin. Buildings 2023, 13, 2343. [Google Scholar] [CrossRef]
  6. Zubair, M.U.; Ali, M.; Khan, M.A.; Khan, A.; Hassan, M.U.; Tanoli, W.A. BIM- and GIS-Based Life-Cycle-Assessment Framework for Enhancing Eco Efficiency and Sustainability in the Construction Sector. Buildings 2024, 14, 360. [Google Scholar] [CrossRef]
  7. Kylili, A.; Georgali, P.-Z.; Christou, P.; Fokaides, P. An integrated building information modeling (BIM)-based lifecycle-oriented framework for sustainable building design. Constr. Innov. 2022, 24, 492–514. [Google Scholar] [CrossRef]
  8. Ismaeil, E.M.H. Asset Information Model Management-Based GIS/BIM Integration in Facility Management Contract. Sustainability 2024, 16, 2495. [Google Scholar] [CrossRef]
  9. Eastman, C.M. BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers, and Contractors; Wiley: Hoboken, NJ, USA, 2008. [Google Scholar]
  10. Borrmann, A.; König, M.; Koch, C.; Beetz, J. Building Information Modeling: Why? What? How? In Building Information Modeling; Springer: Cham, Switzerland, 2018. [Google Scholar] [CrossRef]
  11. Johnson, J.; Motor, T.; North, M. Collaboration, Integrated Information and the Project Lifecycle in Building Design, Construction and Operation. 2004. Available online: https://kcuc.org/wp-content/uploads/2013/11/Collaboration-Integrated-Information-and-the-Project-Lifecycle.pdf (accessed on 5 May 2024).
  12. Succar, B. Building information modelling framework: A research and delivery foundation for industry stakeholders. Autom. Constr. 2009, 18, 357–375. [Google Scholar] [CrossRef]
  13. Liu, Z.; Liu, Y.; Osmani, M. Integration of Smart Cities and Building Information Modeling (BIM) for a Sustainability Oriented Business Model to Address Sustainable Development Goals. Buildings 2024, 14, 1458. [Google Scholar] [CrossRef]
  14. El-Mekawy, M.; Östman, A.; Hijazi, I. A Unified Building Model for 3D Urban GIS. ISPRS Int. J. Geo-Inf. 2012, 1, 120–145. [Google Scholar] [CrossRef]
  15. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews Systematic reviews and Meta-Analyses. BMJ 2021, 372, 71. [Google Scholar] [CrossRef] [PubMed]
  16. Kalogianni, E.; Dimopoulou, E.; Thompson, R.J.; Lemmen, C.; Ying, S.; van Oosterom, P. Development of 3D spatial profiles to support the full lifecycle of 3D objects. Land Use Policy 2020, 98, 104177. [Google Scholar] [CrossRef]
  17. ISO 19152-1:2024; Geographic Information—Land Administration Domain Model (LADM)—Part 1: Generic Conceptual Model. International Organization for Standardization: Geneva, Switzerland, 2024. Available online: https://www.iso.org/standard/81263.html (accessed on 12 May 2024).
  18. ISO/DIS 19152-5; Geographic Information—Land Administration Domain Model (LADM)—Part 5: Spatial Plan Information. International Organization for Standardization: Geneva, Swizerland. Available online: https://www.iso.org/standard/81267.html (accessed on 12 May 2024).
  19. ISO 19152-6; Geographic Information—Land Administration Domain Model (LADM)—Part 6: Implementation Aspects. International Organization for Standardization: Geneva, Switzerland. Available online: https://committee.iso.org/sites/tc211/home/projects/projects---complete-list/iso-19152-6.html (accessed on 26 May 2024).
  20. Tomić, H.; Ivić, S.M.; Roić, M.; Šiško, J. Developing an efficient property valuation system using the LADM valuation information model: A Croatian case study. Land Use Policy 2021, 104, 105368. [Google Scholar] [CrossRef]
  21. ISO 16739-1:2024; Industry Foundation Classes (IFC) for Data Sharing in the Construction and Facility Management Industries —Part 1: Data Schema. International Organization for Standardization: Geneva, Switzerland, 2024. Available online: https://www.iso.org/standard/84123.html (accessed on 26 May 2024).
  22. EUBIM Task Group. Handbook for the Introduction of Building Information Modelling by the European Public Sector Strategic Action for Construction Sector Performance: Driving Value, Innovation and Growth; EUBIM Task Group: Brussels, Belgium, 2017; Available online: https://www.eubim.eu/downloads/EU_BIM_Task_Group_Handbook_FINAL.PDF (accessed on 27 May 2024).
  23. Guler, D. Implementation of 3D spatial planning through the integration of the standards. Trans. GIS 2023, 27, 2252–2277. [Google Scholar] [CrossRef]
  24. CityGML—Open Geospatial Consortium. Available online: https://www.ogc.org/standard/citygml/ (accessed on 26 May 2024).
  25. Ledoux, H.; Ohori, K.A.; Kumar, K.; Dukai, B.; Labetski, A.; Vitalis, S. CityJSON: A compact and easy-to-use encoding of the CityGML data model. Open Geospat. Data Softw. Stand. 2019, 4, 4. [Google Scholar] [CrossRef]
  26. Van Berlo, L.; Dijkmans, T.; Stoter, J. Experiment for Integrating Dutch 3d Spatial Planning and BIM for Checking Building Permits. Available online: http://www.ruimtelijkeplannen.nl (accessed on 26 May 2024).
  27. Nummi, P.; Staffans, A.; Helenius, O. Digitalizing planning culture: A change towards information model-based planning in Finland. J. Urban Manag. 2023, 12, 44–56. [Google Scholar] [CrossRef]
  28. Kalogianni, E.; van Oosterom, P.; Dimopoulou, E.; Lemmen, C. 3D Land Administration: A Review and a Future Vision in the Context of the Spatial Development Lifecycle. ISPRS Int. J. Geo-Inf. 2020, 9, 107. [Google Scholar] [CrossRef]
  29. Chowdhury, M.; Hosseini, M.R.; Edwards, D.J.; Martek, I.; Shuchi, S. Comprehensive analysis of BIM adoption: From narrow focus to holistic understanding. Autom. Constr. 2024, 160, 105301. [Google Scholar] [CrossRef]
  30. Safour, R.; Ahmed, S.; Zaarour, B. BIM Adoption around the World. Int. J. BIM Eng. Sci. 2021, 4, 31–44. [Google Scholar] [CrossRef]
  31. Fauth, J.; Bloch, T.; Noardo, F.; Nisbet, N.; Kaiser, S.-B.; Gade, P.N.; Tekavec, J. Taxonomy for building permit system—Organizing knowledge for building permit digitalization. Adv. Eng. Inform. 2024, 59, 102312. [Google Scholar] [CrossRef]
  32. Ullah, K.; Raitviir, C.; Lill, I.; Witt, E. BIM adoption in the AEC/FM industry—The case fo issuing building permits. Int. J. Strateg. Prop. Manag. 2020, 24, 400–413. [Google Scholar] [CrossRef]
  33. Noardo, F.; Wu, T.; Ohori, K.A.; Krijnen, T.; Stoter, J. IFC models for semi-automating common planning checks for building permits. Autom. Constr. 2022, 134, 104097. [Google Scholar] [CrossRef]
  34. Ismail, A.S.; Ali, K.N.; Iahad, N.A.; Kassem, M.A.; Al-Ashwal, N.T. BIM-Based Automated Code Compliance Checking System in Malaysian Fire Safety Regulations: A User-Friendly Approach. Buildings 2023, 13, 1404. [Google Scholar] [CrossRef]
  35. Beach, T.; Yeung, J.; Nisbet, N.; Rezgui, Y. Digital approaches to construction compliance checking: Validating the suitability of an ecosystem approach to compliance checking. Adv. Eng. Inform. 2024, 59, 102288. [Google Scholar] [CrossRef]
  36. Andrich, W.; Daniotti, B.; Pavan, A.; Mirarchi, C. Check and Validation of Building Information Models in Detailed Design Phase: A Check Flow to Pave the Way for BIM Based Renovation and Construction Processes. Buildings 2022, 12, 154. [Google Scholar] [CrossRef]
  37. Riddell, T. Bad Construction Data Costs Industry $1.8 Trillion Worldwide—MSUITE. Available online: https://www.msuite.com/bad-construction-data-costs-industry-1-8-trillion-worldwide/ (accessed on 15 May 2024).
  38. Chen, Y.; Huang, D.; Liu, Z.; Osmani, M.; Demian, P. Construction 4.0, Industry 4.0, and Building Information Modeling (BIM) for Sustainable Building Development within the Smart City. Sustainability 2022, 14, 10028. [Google Scholar] [CrossRef]
  39. Xu, S.; Luo, H. The information-related time loss on construction sites: A case study on two sites. Int. J. Adv. Robot. Syst. 2014, 11, 128. [Google Scholar] [CrossRef]
  40. Barlish, K.; Sullivan, K. How to measure the benefits of BIM—A case study approach. Autom. Constr. 2012, 24, 149–159. [Google Scholar] [CrossRef]
  41. Chong, O.W.; Zhang, J.; Voyles, R.M.; Min, B.-C. BIM-based simulation of construction robotics in the assembly process of wood frames. Autom. Constr. 2022, 137, 104194. [Google Scholar] [CrossRef]
  42. Rodrigues, F.; Baptista, J.S.; Pinto, D. BIM Approach in Construction Safety—A Case Study on Preventing Falls from Height. Buildings 2022, 12, 73. [Google Scholar] [CrossRef]
  43. Saghatforoush, E.; Trigunarsyah, B.; Heravi, A.; Too, E.; Heravitorbati, A. Extending Constructability Concept to Include Operation and Maintenance Issues. 2011. Available online: http://eprints.qut.edu.au/41571/ (accessed on 26 May 2024).
  44. Pärn, E.A.; Edwards, D.J.; Sing, M.C.P. The building information modelling trajectory in facilities management: A review. Autom. Constr. 2017, 75, 45–55. [Google Scholar] [CrossRef]
  45. Patacas, J.; Dawood, N.; Kassem, M. BIM for facilities management: A framework and a common data environment using open standards. Autom. Constr. 2020, 120, 103366. [Google Scholar] [CrossRef]
  46. Pavón, R.M.; Alberti, M.G.; Álvarez, A.A.A.; Del Rosario Chiyón Carrasco, I. Use of bim-fm to transform large conventional public buildings into efficient and smart sustainable buildings. Energies 2021, 14, 3127. [Google Scholar] [CrossRef]
  47. Lin, Y.C.; Hsu, Y.T.; Hu, H.T. BIM Model Management for BIM-Based Facility Management in Buildings. Adv. Civ. Eng. 2022, 2022, 1901201. [Google Scholar] [CrossRef]
  48. Amin, K.; Mills, G.; Wilson, D. Key functions in BIM-based AR platforms. Autom. Constr. 2023, 150, 104816. [Google Scholar] [CrossRef]
  49. Huang, Y.; Pan, L.; He, Y.; Xie, Z.; Zheng, X. A BIM–WMS Management Tool for the Reverse Logistics Supply Chain of Demolition Waste. Sustainability 2022, 14, 16053. [Google Scholar] [CrossRef]
  50. Fang, B.; Yu, J.; Chen, Z.; Osman, A.I.; Farghali, M.; Ihara, I.; Hamza, E.H.; Rooney, D.W.; Yap, P.-S. Artificial intelligence for waste management in smart cities: A review. Environ. Chem. Lett. 2023, 21, 1959–1989. [Google Scholar] [CrossRef] [PubMed]
  51. Wang, S.; Wu, Q.; Yu, J. BIM-Based Assessment of the Environmental Effects of Various End-of-Life Scenarios for Buildings. Sustainability 2024, 16, 2980. [Google Scholar] [CrossRef]
  52. Schamne, A.N.; Nagalli, A.; Soeiro, A.A.V.; Martins, J.P.d.S.P. BIM in construction waste management: A conceptual model based on the industry foundation classes standard. Autom. Constr. 2024, 159, 105283. [Google Scholar] [CrossRef]
  53. Boje, C.; Guerriero, A.; Kubicki, S.; Rezgui, Y. Towards a semantic Construction Digital Twin: Directions for future research. Autom. Constr. 2020, 114, 103179. [Google Scholar] [CrossRef]
  54. Hauer, M.; Hammes, S.; Zech, P.; Geisler-Moroder, D.; Plörer, D.; Miller, J.; van Karsbergen, V.; Pfluger, R. Integrating Digital Twins with BIM for Enhanced Building Control Strategies: A Systematic Literature Review Focusing on Daylight and Artificial Lighting Systems. Buildings 2024, 14, 805. [Google Scholar] [CrossRef]
  55. Masoumi, H.; Shirowzhan, S.; Eskandarpour, P.; Pettit, C.J. City Digital Twins: Their maturity level and differentiation from 3D city models. Big Earth Data 2023, 7, 1–36. [Google Scholar] [CrossRef]
  56. Souza, L.; Bueno, C. City Information Modelling as a support decision tool for planning and management of cities: A systematic literature review and bibliometric analysis. J. Affect. Disord. 2021, 207, 108403. [Google Scholar] [CrossRef]
  57. Cureton, P.; Hartley, E. City Information Models (CIMs) as precursors for Urban Digital Twins (UDTs): A case study of Lancaster. Front. Built Environ. 2023, 9, 1048510. [Google Scholar] [CrossRef]
  58. Tuhaise, V.V.; Tah, J.H.M.; Abanda, F.H. Technologies for digital twin applications in construction. Autom. Constr. 2023, 152, 104931. [Google Scholar] [CrossRef]
  59. Salles, A.; Salati, M.; Bragança, L. Analyzing the Feasibility of Integrating Urban Sustainability Assessment Indicators with City Information Modelling (CIM). Appl. Syst. Innov. 2023, 6, 45. [Google Scholar] [CrossRef]
  60. Dembski, F.; Wössner, U.; Letzgus, M.; Ruddat, M.; Yamu, C. Urban digital twins for smart cities and citizens: The case study of herrenberg, germany. Sustainability 2020, 12, 2307. [Google Scholar] [CrossRef]
  61. Zheng, H.; Liu, T.; Liu, J.; Bao, J. Visual analytics for digital twins: A conceptual framework and case study. J. Intell. Manuf. 2023, 35, 1671–1686. [Google Scholar] [CrossRef]
  62. Martins, N.C.; Marques, B.; Alves, J.; Araújo, T.; Dias, P.; Santos, B.S. Augmented reality situated visualization in decision-making. Multimedia Tools Appl. 2021, 81, 14749–14772. [Google Scholar] [CrossRef]
  63. Kumari, R.; Mishra, A.R. Multi-criteria COPRAS Method Based on Parametric Measures for Intuitionistic Fuzzy Sets: Application of Green Supplier Selection. Iran. J. Sci. Technol. Trans. Electr. Eng. 2020, 44, 1645–1662. [Google Scholar] [CrossRef]
  64. Taherdoost, H.; Madanchian, M. Multi-Criteria Decision Making (MCDM) Methods and Concepts. Encyclopedia 2023, 3, 77–87. [Google Scholar] [CrossRef]
Figure 1. The literature review process.
Figure 1. The literature review process.
Buildings 14 02207 g001
Figure 2. Suggested information flow diagram (adapted from Eastman 2008 [9] and Borrmann 2018 [10]).
Figure 2. Suggested information flow diagram (adapted from Eastman 2008 [9] and Borrmann 2018 [10]).
Buildings 14 02207 g002
Figure 3. Conceptual framework of the research.
Figure 3. Conceptual framework of the research.
Buildings 14 02207 g003
Figure 4. Information flow scheme between processes and public databases/services. Abbreviations: GeoDB—geological database, GreDB—greenery database, PR—Planning Registry, BR—Building Registry, AR—Assets Registry.
Figure 4. Information flow scheme between processes and public databases/services. Abbreviations: GeoDB—geological database, GreDB—greenery database, PR—Planning Registry, BR—Building Registry, AR—Assets Registry.
Buildings 14 02207 g004
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Raitviir, C.-R.; Lill, I. Conceptual Framework of Information Flow Synchronization Throughout the Building Lifecycle. Buildings 2024, 14, 2207. https://doi.org/10.3390/buildings14072207

AMA Style

Raitviir C-R, Lill I. Conceptual Framework of Information Flow Synchronization Throughout the Building Lifecycle. Buildings. 2024; 14(7):2207. https://doi.org/10.3390/buildings14072207

Chicago/Turabian Style

Raitviir, Christopher-Robin, and Irene Lill. 2024. "Conceptual Framework of Information Flow Synchronization Throughout the Building Lifecycle" Buildings 14, no. 7: 2207. https://doi.org/10.3390/buildings14072207

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop