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COnstruction-phase diGItal Twin mOdel

Periodic Reporting for period 3 - COGITO (COnstruction-phase diGItal Twin mOdel)

Período documentado: 2022-11-01 hasta 2024-04-30

In order to reduce construction project durations, lower costs, and enhance workplace safety within the construction industry, COGITO has been committed to advancing digitalisation by aligning Digital Twins with Building Information Models (BIMs) and constructing a digital Construction 4.0 toolbox. In alignment with the project objectives, within COGITO, a comprehensive set of services has been developed and provided to achieve the following aims: timely detection and mitigation of safety hazards to protect workers (Objective 3); swift identification of quality defects (Objective 2); and real-time workflow management on construction sites (Objective 2). To ensure seamless integration among the various components of the COGITO architecture, advanced methods and technologies have been implemented within the Digital Twin platform, which forms the core of this toolkit (Objective 1). The COGITO Digital Twins ecosystem relies on harmonised interfaces, standardised data structures, ontologies, communication protocols, and data formats, delivering a reusable and extensible construction digital twin. The COGITO toolbox has been pre-validated in an actual medium-scale infrastructure project, and thoroughly tested through demonstrations in two real construction sites to showcase its value and gather feedback from its practical use (Objective 4). Beyond technical efforts, COGITO partners have engaged in extensive standardisation activities to promote COGITO's proposals on construction standardisation, data modelling, and linked open data to relevant standardisation bodies, committees, and working groups (Objectives 5 and 6). Furthermore, COGITO has placed significant emphasis on the involvement of various construction industry stakeholders, such as construction managers, workers, quality managers, health and safety personnel, and BIM managers. Their active participation in all research, innovation, standardisation, demonstration, and communication activities has been crucial for the successful implementation of the project and realising its anticipated impacts. COGITO has established a collaborative and engaging framework known as the COGITO Living Lab, where stakeholders were able to exchange opinions, experiences, and knowledge. This framework adhered to agile principles, ensuring the delivery of an innovative solution that genuinely meets the needs of all stakeholders (Objective 6).
During the first reporting period, management activities resulted in the delivery of two main documents: the Quality Assurance Plan, which defines the management and operation framework of COGITO to ensure high-quality results according to the Grant Agreement, and the Data Management Plan. Technical activities primarily focused on establishing the project's foundation. Key outcomes included the elicitation of stakeholder requirements, the definition of the evaluation methodology, a regulatory and market analysis, and the detailed design of the system architecture. Additionally, significant effort was made to identify and analyze relevant existing data models and ontologies, leading to the development of the COGITO ontology network.
In the second reporting period, the main achievements included: planning the dissemination, communication, exploitation, and standardization of COGITO results; engaging stakeholders in Living Lab activities, and dissemination and communication efforts, along with preparing materials to familiarize them with COGITO tools; and delivering the first version of the integrated COGITO ecosystem. Functional tools for Quality Control, Health & Safety, and Workflow Management were developed and documented. Moreover, as-planned and as-built data from a medium-scale infrastructure construction project were collected and used for pre-validating the tools.
During the third reporting period, significant work and achievements included: the deployment and demonstration of the COGITO solution in pre-validation cases and validation sites; the delivery of the second and third versions of the integrated system; finalizing the COGITO communication, exploitation, and standardization plans; engaging stakeholders in Living Lab activities and preparing materials for lessons learned and best practices; and evaluating the COGITO system's performance and impact. The evaluation, conducted by professionals with relevant roles associated with the pilot partners, covered all areas of impact and included both quantitative and qualitative assessments. The quantitative evaluations were very encouraging, and the qualitative evaluations further confirmed the potential and capacity of the COGITO solution to broadly deliver the expected impact.
Significant progress beyond the state of the art was made in several components of the integrated COGITO solution and the development of COGITO data models and ontologies compliant with existing standards, to the extent possible, for promotion to standardisation bodies. Specifically, the Digital Twin Platform advanced beyond the state of the art by providing a modular yet fully extensible framework for change management, updating, consistency checking, and version control of Digital Twin data. For the Health & Safety services, an existing digital twin application was extended and adapted to follow a more standardised approach, enhancing the H&S checking prototype with more complex rules and addressing expected computational runtime issues. To tackle these issues, a novel probabilistic Deductive Abductive Logic Programming framework was developed to infer higher-level hypotheses of potential construction site hazards based on likely, tentative explanations. Additionally, advanced machine learning techniques were implemented to process up-to-date data, enabling the rapid detection and prediction of hazardous situations in dynamic construction sites. In the context of Quality Control, a novel visual data processing pipeline was developed, advancing beyond the current state of the art by expanding the scope and effectiveness of automated QC to detect structural geometric inconsistencies, cracks, or other structural defects. For the Scan-vs-BIM Geometric QC, algorithms implementing existing Standard Test Methods for Geometric QC were created to automatically apply to BIM objects matched with reality capture data. Furthermore, the robustness of an existing Scan-vs-BIM solution for matching as-built reality capture point clouds to as-designed BIM elements was significantly improved. Regarding the potential impact of the project, comprehensive evaluations covering all areas of impact were conducted, including both quantitative and qualitative assessments. The quantitative evaluations were very encouraging, and the qualitative evaluations further confirmed the potential and capacity of the COGITO solution to broadly deliver the expected impact.
COGITO offering in a nutshell