Key tools
COGITO Tool | Visualization | Description |
Work Order Definition and Monitoring tool (WODM) |
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The WODM is the tool used for defining work order templates, generating work orders and executing/monitoring the defined workflow. The definition of work order templates and generation of work orders are conducted using the tool’s UI, but a workflow can also be imported from a BPMN file. Work orders execution can be monitored through communication using the WOEA tool. |
Work Order Execution Assistance tool (WOEA) |
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The Work Order Execution Assistance tool (WOEA) is an app for smart glasses supporting work order execution and reporting. The worker is guided via smart glasses through the work order, which enables immediate reporting of the results of the work. WOEA can work online or offline and provides hands-free operation support. The app also enables Remote Assistance through video call with remote annotations. |
Digital Twin Platform (DTP) |
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The Digital Twin Platform (DTP) is the core of the entire toolchain. It supports both the necessary information management as well as the semantic (and pragmatic) alignment among the COGITO services and data pre-processing systems, while enabling interoperability with existing and emerging standards and data formats covering numerous domains. |
Process Modelling and Simulation tool (PMS) |
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The Process Modelling and Simulation tool allows to define and simulate both the construction business process model as well as the operative workflow model.
This allows the user to identify process steps that are critical for the successful implementation of the project exposing optimization opportunities to minimize time and/or cost. The combination with real-world data is supported by data mining algorithms and statistical methods and allows the calibration of the simulation model to the actual process occurring on the construction site. |
Digital Twin visualisation with AR (DigiTAR) |
DigiTAR is a software package for commercial AR head-mounted displays (HMDs) to help visualise and interact in situ with the output of the QC tools (location, type and severity of geometric and visual defects) and Safety tools (location and type of safety hazards and expected mitigation measures). | |
GeometricQC Tool (gQC) |
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The GeometricQC tool controls automatically the geometric quality of the executed works against the specified geometric dimensions and tolerances given as-built 3D data acquired onsite. The as-built 3D data is (dense laser scanned) point clouds acquired on site. The specified dimensions are obtained from the as-design BIM model (part of the DT) and the specified tolerances are obtained from ISO/CEN standards used by industry (and translated digitally to enable the automated process). The QC results are modelled and semantically linked to the BIM/DT model. |
VisualQC (vQC) |
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The Visual QC tool automatically detects in colour images (visual spectrum) common visual defects of constructed/erected concrete components and their severity. The QC results are modelled and semantically linked to the BIM/DT model. |
Digital (Visual) Command Centre (DCC) |
The DCC renders the 3D BIM model, IoT data and other data and annotations generated by the QC, H&S and Workflow tools (available through the DT platform). The DCC will help the Project Manager to monitor through visualisation the progress, QC defects and H&S issues; The DCC is solution to visualise/navigate the DT data, but not edit it. | |
Visual Data Pre-Processing Tool |
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Visual Data Pre-Processing tool provides functionalities that detect and recognize equipment in the construction site based on advanced deep learning algorithms. It provides a User Interface (UI) in order for the surveyor to be able to upload the necessary files and information. |
BlckChain Platform Tool |
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The Blockchain Platform tool will allow the deployment of smart contracts, through the SLA Manager. It will interact with the Work Order Definition and Monitoring tool and based on the operative workflow model it will provide blockchain-based smart contracts in order to enhance transparency and to provide trusted means to verify the completion of construction tasks, asset release, etc. |
BlockChain SLA Manager |
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The Blockchain SLA Manager has a local DB with already designed SLAs that include predefined rules and KPIs. WODM could fetch the SLAs through the SLA Manager in order to bind relevant stakeholders with the respective KPIs. Then WODM inform the SLA Manager with the results and SLA Managers saves the SLA with the respective Stakeholders on the local DB. BC can fetch the completed SLA with the assigned stakeholders and the respective configurations to initiate & instantiate the Smart Contract operation. |
SafeConAI |
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The SafeConAI tool identifies regions in the BIM model where (specific types of) hazards are, suggests and adds mitigation measures to the model. It uses as input a 4D BIM of as-planned construction project, consisting of n time steps, where each time step corresponds to stage of construction of the asset. Six types of hazards in four major categories are considered (slips, trips, fall from height, caught-in between, struck-bys, electrocutions), and one or two specific safety code entries are considered for each of these hazards (i.e. approximately 6-12 safety codes total). |
ProActive Safety |
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The ProActiveSafety tool utilizes behavioural data of resources (equipment and personnel) on the construction site to avoid close-calls, accidents, and collateral damage. Location data from the Location Data Acquisition Tools is analysed to predict trajectories of resources and detect imminent close-calls and accidents by cross-checking those trajectories with potential hazards based on previous experiences/observations, rules, and the probability of hazards given the dynamic nature of the work environment. |
VirtualSafety |
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The VirtualSafety tool provides personalized construction safety education and training, focusing on the top 6 hazards: Slips/trips/falls from height, caught-in between, struck-by, and electrocution. The highly realistic VR provides easy-to-use, reliable safe learning environment and technology that assists advanced HSE decision making and provide personalized feedback in a safe learning environment |
Geometric Data Acquisition (GDA) Tools |
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The Geometric Data Acquisition Tool(s) are employed on-site to acquire 3D geometry of the site. Within COGITO, laser scanning will be principally used because of the accuracy required for geometric QC. However, other tools like photogrammetric systems (e.g. UAV mounted) may also be considered for other purposes. |
Visual Data Acquisition (VDA) Tools |
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The Visual Data Acquisition Tool(s) are employed on-site to acquire 2D visual data of the site. Within COGITO, images in the visual spectrum are primarily considered, and these images may be acquired using any camera mounted a wearable AR system (e.g. DigiTAR), a phone, a mobile computer, etc. |
Location Data Acquisition (LDA) Tools |
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The Location Data Acquisition tool(s) gather raw IoT data that are coming from sensorial devices installed or worn on the construction site and generate datasets that can be directly stored in the COGITO Digital Twin platform. The tools are used to capture location data about the workforce, machinery, and materials. |