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19th International Conference on computing in Civil and Building engineering, ICCCBE 2022

作者： Kosse, Simon Vogt, Oliver Wolf, Mario König, Markus Gerhard, Detlef Chair of Computing in Engineering Ruhr University Bochum Germany Digital Engineering Chair Ruhr University Bochum Germany

ISBN: (纸本)9783031353987

For efficient and sustainable use of precast concrete modules, all relevant information must be collected digitally and in real-time and made available in digital twins. Digitization should be carried out in such a way that continuous quality management is possible at all times. This also includes whether the produced concrete modules also meet all the requirements from the initial design. For example, the precast concrete parts must be able to absorb certain forces or have precise connections and joining options. The Requirements Interchange Format (ReqIF) can be used to describe requirements digitally and exchange them between different IT systems and stakeholders. The creation of automated quality control (QC) protocol for the flow production process can be implemented based on this already structured and formalized requirements format. In this paper, the Asset Administration Shell (AAS) from the context of Industry 4.0 is enhanced to enable the formal description and automated verification of requirements for precast concrete based on the ReqIF interchange format. For this purpose, a smart service integrates the ReqIF-compliant requirements into an AAS submodel. Via this smart service, a mapping assistance tool lets stakeholders assign measurable properties of the precast concrete modules to the requirements, thus enabling an automated quality check. The presented approach is validated based on a virtual precast concrete wall for which a chain of linked requirements is described and automatically checked within the scope of a case study. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Precast concrete

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DigiPark - Digitization in parking garage maintenance 8th

DigiPark - Digitization in parking garage maintenance

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8th International Symposium on Reliability engineering and Risk Management, ISRERM 2022

作者： Blut, C. Blankenbach, J. Geodetic Institute Chair for Computing in Civil Engineering and GIS RWTH Aachen University Aachen Germany

ISBN: (纸本)9789811851841

Maintenance is a central task for ensuring the permanent functionality of buildings and the documentation of maintenance work is an essential aspect of quality assurance. In parking garages, there are often several thousand damaged areas, which are traditionally documented by hand in paper plans. However, this is error-prone and impractical, especially since parking garages frequently change owners, with the paper plans (partly) regularly being lost. Within the research project "DigiPark", a digital process was developed based on Building Information Modeling (BIM) to optimize the documentation and management of damage in buildings, using parking garages as an example. In the first step, the process involves creating a digital twin, i.e., capturing the physical building in a digital 3D model as a basis for documenting damage. For this, methods for capturing geometric-semantic properties of buildings were investigated and a concept for an efficient implementation was developed. In the second step, a user-friendly mobile system for the semi-automatic georeferenced documentation of damaged areas was realized which is capable of estimating its position and orientation (pose) in realtime in buildings without external infrastructure. This was solved by incorporating a visual-inertial Simultaneous Localization and Mapping (VI-SLAM) approach. Finally, an interface for integrating the captured damage in the BIM model was implemented based on the Industry Foundation Classes (IFC)-conforming standard BIM Collaboration Format (BCF). The result enables an efficient BIMbased management of damage to optimize tasks such as planning of maintenance work. © 2022 ISRERM Organizers. Published by Research Publishing, Singapore.

关键词： Garages (parking)

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Enhancing Information Extraction from Building Standards with ChatGPT-4: A Multimodal Approach 20th

Enhancing Information Extraction from Building Standards wit...

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20th International Conference on computing in Civil and Building engineering, ICCCBE 2024

作者： Zentgraf, Sven König, Markus Chair of Computing in Engineering Ruhr-Universität Bochum Universitätsstraße 150 Bochum44801 Germany

ISBN: (纸本)9783031842078

The AECO (Architectural, engineering, Construction, and Operations) industry is increasingly benefiting from the advantages of advanced information management, particularly through the use of Building Information Modeling (BIM) methods. BIM integrates geometric and alphanumeric data, such as dimensions and spatial relationships, into digital building models. These elements are subject to specific constraints defined by industry standards and guidelines. The issue with these constraints embedded in regulatory documents is that they are mostly only available in non-machine readable formats which hinders the exchange and usage of data within the building’s lifecycle. Currently, the required rules and requirements are extracted manually by experts from the regulatory documents and integrated manually and labor-intensively into corresponding BIM processes. Thus, many research projects are currently addressing the issue of how the textual components of regulatory documents can be automatically analyzed to extract rules and requirements using Natural Language Processing or other approaches. In addition to this textual information, many standards also contain figures and illustrations that explain the information described in the text in more detail or contain additional knowledge. Converting this graphical content into machine-readable information is just as challenging as analyzing the textual components. This paper aims to develop an approach for extracting information related to building information requirements from figures contained in standards using the two state-of-the-art MLLMs Kosmos 2 and Chat GPT-4. An MLLM is an AI system that can process text, images, audio, and video, unlike traditional models that are limited to text. MLLMs trained on large data sets recognize complex patterns in different types of data. With the help of the two MLLMs, the images, and their corresponding texts and captions from the standards will first be analyzed, and then the information

关键词： Concretes

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BIM-Based Organization of Inspection Data Using Semantic Web Technology for Infrastructure Asset Management 1st

BIM-Based Organization of Inspection Data Using Semantic Web...

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1st Conference of the European Association on Quality Control of Bridges and Structures, EUROSTRUCT 2021

作者： Liu, Liu Hagedorn, Philipp König, Markus Chair of Computing in Engineering Faculty of Civil and Environmental Engineering Ruhr University Bochum Bochum Germany

ISBN: (纸本)9783030918767

The use of Building Information Modeling (BIM) for the planning and construction of infrastructures has increased significantly in recent years. However, there is currently a lack of flexible concepts for the management and use of BIM models for asset management, considering existing systems and processes. A major challenge is how the BIM models can be continuously enriched with information on the most current condition. In this paper, a concept for applying BIM models for bridge inspection and the subsequent integration of the results into existing asset management systems is presented. The information for inspection and condition assessment is provided as an information container according to ISO 21597. Semantic Web technologies are used to describe the information for the structural components, the structural conditions, and the detected damages of a bridge using existing ontologies. An illustrative example demonstrates how BIM models are enriched in the context of inspection and how the data can be transferred into existing asset management systems. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Ontology

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Neural Evolutionary Architecture Search for Compact Printed Analog Neuromorphic Circuits

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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2024年

作者： Zhao, Haibin Pal, Priyanjana Hefenbrock, Michael Wang, Yuhong Beigl, Michael Tahoori, Mehdi B. Chair for Pervasive Computing Systems Institute of Telematics Germany Chair of Dependable Nano Computing Institute of Computer Engineering Department of Informatics Germany RevoAI GmbH Germany

Printed electronics (PE) is an additive fabrication technology for manufacturing electronic circuits which not only allows for a highly flexible printing of arbitrary circuit patterns, but also produce soft, non-Toxic, and degradable electronics at an extremely low cost. These properties are unmatched by silicon based electronics, making PE an enabler of new application domains, e.g., fast moving consumer goods, wearables, and disposable healthcare devices. A particularly promising class of circuits in this technology is the printed analog neuromorphic circuits, offering efficient and highly tailored computational functionalities. In this work, we leverage the highly flexible fabrication process of PE to address the bottleneck of PE, i.e., the large feature sizes and low device counts. This issue is crucial, as it impairs the integration of printed circuits into target applications with limited footprint, such as smart band aids. We also propose an evolutionary algorithm (EA) to improve the circuit compactness through circuit architecture optimization. As baseline, we compare the proposed EA method with a state-of-The-Art pruning method and a modified area-Aware pruning method. All of them are able to optimize circuit architecture alongside the component values of printed neuromorphic circuits. Experimental simulation reveals that the proposed EA approach can effectively achieve compact circuits and outperform the pruning method by 3.1× lower area with no loss of accuracy. As a byproduct, the power is reduced by 3.0×, paving the way to energy-harvested printed systems. © 1982-2012 IEEE.

关键词： Flexible electronics

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Training Underserved Communities in Construction Trades for Social Mobility and Job Equity

Training Underserved Communities in Construction Trades for ...

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Construction Research Congress 2024, CRC 2024

作者： Calle Müller, Claudia Rivera, Erika Gallego, Emily Tomas, Victoria Faria, Jose Elzomor, Mohamed Dept. of Civil and Environmental Engineering Florida International Univ United States Moss School of Construction Infrastructure and Sustainability College of Engineering and Computing Florida International Univ United States Moss Endowed Chair Moss School of Construction Infrastructure and Sustainability College of Engineering and Computing Florida International Univ United States Moss School of Construction Infrastructure and Sustainability College of Engineering and Computing Florida International Univ MiamiFL United States

ISBN: (数字)9780784485293

ISBN: (纸本)9780784485293

To promote social mobility and job equity in low-income communities, this research demonstrates a successful pedagogy that educates, trains, and certifies lower-income and underserved individuals, including unemployed, veterans, women, individuals aging out of foster care, and the homeless to join the construction industry, thus filling the critical shortage of skilled craft workers in construction. The goals of this research are to (1) identify gaps in construction trade knowledge of low-income individuals, (2) evaluate if individuals found better job opportunities after completing a construction trades program (CTP), and (3) identify pedagogy including course delivery and instructional technologies to effectively educate and train particularly the low-income workforce on basic construction knowledge and offer them the needed skills to find better job opportunities in this well-paid industry. To achieve these goals, this research surveyed 65 students, alumni, and faculty of a CTP that serves low-income and underserved communities. The results of this study showed that students of a CTP obtained better job opportunities and highlighted the importance of training low-income individuals in construction trades for social mobility. This study provides strategies for low-income communities to join the construction workforce, thus leading to a diverse workforce and filling in the construction workforce gap. © CRC 2024. All rights reserved.

关键词： Construction industry

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TwinGen: Advanced technologies to automatically generate digital twins for operation and maintenance of existing bridges 14th

TwinGen: Advanced technologies to automatically generate dig...

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14th European Conference on Product and Process Modelling, ECPPM 2022

作者： Vilgertshofer, S. Mafipour, M.S. Borrmann, A. Martens, J. Blut, T. Becker, R. Blankenbach, J. Göbels, A. Beetz, J. Celik, F. Faltin, B. König, M. Computational Modeling and Simulation Technical University of Munich Germany Geodetic Institute and Chair for Computing in Civil Engineering & Geo Information Systems RWTH Aachen University Germany Design Computation RWTH Aachen University Germany Computing in Engineering Ruhr University Bochum Germany

ISBN: (纸本)9781032406732

The high effort of operating and maintaining existing infrastructure facilities resulted in a large stock of structurally deficient bridges in most industrialized countries. Today, the condition assessment of bridges is conducted mostly manually. To relieve effort and costs, the digitization and automation of conventional manual, labour-intensive methods is necessary. We interpret the ambiguously used term "digital twin" (DT) in this study as a semantic-geometric model of an existing asset (here, a bridge) that contains all information required for assessing its current condition. This paper proposes an approach to automatically generate the DT of existing bridges from point cloud data (PCD) and images captured from the structure. The PCD of the bridge is semantically segmented by means of ML techniques, and a digital model is created using parametric modeling. Subsequently, detected damages and data from existing bridge maintenance systems are linked to the model to create a full DT. This paper reports the main results of the TwinGen research project: The digital twinning process of bridges can be automated to a large extent, in order to efficiently support the maintenance process of bridges. © 2023 the Author(s).

关键词： Bridges

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SACNN-IDS: A self-attention convolutional neural network for intrusion detection in industrial internet of things

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CAAI Transactions on Intelligence Technology 2024年第6期9卷 1398-1411页

作者： Mimonah Al Qathrady Safi Ullah Mohammed S.Alshehri Jawad Ahmad Sultan Almakdi Samar M.Alqhtani Muazzam A.Khan Baraq Ghaleb Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Department of Computer Science Quaid-i-Azam UniversityIslamabadPakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia School of Computing Engineering and the Built EnvironmentEdinburgh Napier UniversityEdinburghUK ICESCO Chair Big Data Analytics and Edge Computing Quaid-i-Azam UniversityIslamabadPakistan

Industrial Internet of Things(IIoT)is a pervasive network of interlinked smart devices that provide a variety of intelligent computing services in industrial *** IIoT nodes operate confidential data(such as medical,transportation,military,etc.)which are reachable targets for hostile intruders due to their openness and varied *** Detection Systems(IDS)based on Machine Learning(ML)and Deep Learning(DL)techniques have got significant ***,existing ML and DL-based IDS still face a number of obstacles that must be *** instance,the existing DL approaches necessitate a substantial quantity of data for effective performance,which is not feasible to run on low-power and low-memory *** and fewer data potentially lead to low performance on existing *** paper proposes a self-attention convolutional neural network(SACNN)architecture for the detection of malicious activity in IIoT networks and an appropriate feature extraction method to extract the most significant *** proposed architecture has a self-attention layer to calculate the input attention and convolutional neural network(CNN)layers to process the assigned attention features for *** performance evaluation of the proposed SACNN architecture has been done with the Edge-IIoTset and X-IIoTID *** datasets encompassed the behaviours of contemporary IIoT communication protocols,the operations of state-of-the-art devices,various attack types,and diverse attack scenarios.

关键词： convolutional neural network deep learning industrial internet of things intrusion detection self-attention

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9th Linked Data in Architecture and Construction Workshop, LDAC 2021

作者： Hagedorn, Philipp König, Markus Chair of Computing in Engineering Ruhr University Bochum Germany

The information delivery in BIM-based construction projects regarding predefined exchange requirements is crucial for the quality of information. Information modeling using Linked Building Data receives increasing attention as it may overcome current interoperability issues. Hence, this information needs to satisfy requirements defined in business processes in an Information Delivery Manual. This paper examines the compatibility of business process modeling and Linked Building Data. Considering recent research progresses, the Information Delivery Processes ontology is developed and evaluated in two demonstration cases for converting XML-based business processes to RDF-based ontology data and performing requirements validation for the attached data sets. These use cases show the feasibility of the application of the developed approach for modeling information deliveries for Linked Building Data. © 2021 Copyright for this paper by its authors.

关键词： Ontology

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A Laser-based Volumetric Measurement Approach for Industrial Settings

A Laser-based Volumetric Measurement Approach for Industrial...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Jérôme Rutinowski Niklas Schrötler Simon Klüttermann Moritz Roidl Christian Janiesch Chair of Material Handling and Warehousing TU Dortmund University Chair of Data Science and Data Engineering TU Dortmund University Chair of Enterprise Computing TU Dortmund University

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

This work introduces a novel approach to the currently available automatic volumetric measurement systems used in the industry. The proposed system uses a ceiling-mounted laser in tandem with an RGB camera to generate a point cloud of the object that is to be measured, utilizing an adaptation of a structured light scanning approach. The resulting point clouds are post-processed, removing detected structural anomalies to improve the yielded results. The resulting system is then tested and validated on a set of seven objects of various sizes commonly encountered in industrial environments. For these experiments, our approach yields outlier-corrected volumes which are accurate at up to 1% volume divergence. The results differ vastly when going beyond the system’s optimal object size range. The limits of the system are tested for smaller and larger objects, showing a notably higher inaccuracy when tested on relatively small or large objects. Further experiments, exploring optimal laser line distance, lighting conditions, and (in the case of containers) filling degrees are also conducted.

关键词： Point cloud compression Industries Laser theory Computer aided software engineering Volume measurement Measurement by laser beam Lighting Containers Cameras Filling

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