1st Edition
Buildings and Semantics Data Models and Web Technologies for the Built Environment
The built environment has been digitizing rapidly and is now transforming into a physical world that is at all times supplemented by a fully web-supported and interconnected digital version, often referred to as Digital Twin. This book shows how diverse data models and web technologies can be created and used for the built environment. Key features of this book are its technical nature and technical detail. The first part of the book highlights a large diversity of IT techniques and their use in the AEC domain, from JSON to XML to EXPRESS to RDF/OWL, for modelling geometry, products, properties, sensor and energy data. The second part of the book focuses on diverse software solutions and approaches, including digital twins, federated data storage on the web, IoT, cloud computing, and smart cities. Key research and strategic development opportunities are comprehensively discussed for distributed web-based building data management, IoT integration and cloud computing. This book aims to serve as a guide and reference for experts and professionals in AEC computing and digital construction including Master's students, PhD researchers, and junior to senior IT-oriented AEC professionals.
1. Building Product Models, Terminologies, and Object Type Libraries
Aaron Costin, Jeffrey W. Ouellette, Jakob Beetz
2. Property Modelling in the AECO Industry
Mathias Bonduel, Pieter Pauwels, Ralf Klein
3. Web Technologies for Sensor and Energy Data Models
Goncal Costa, Alvaro Sicilia
4. Geometry and Geospatial Data on the Web
Anna Wagner, Mathias Bonduel, Jeroen Werbrouck, Kris McGlinn
5. Open Data Standards and BIM on the Cloud
Pieter Pauwels, Dennis Shelden, Jan Brouwer, Devon Sparks, Saha Nirvik, Tim Pat McGinley
6. Federated Data Storage for the AEC Industry
Jeroen Werbrouck, Madhumitha Senthilvel, Mads Holten Rasmussen
7. Web-based Computing for the AEC industry: Overview and Applications
Mohamed Elagiry, Rubèn Alonso, Eva Coscia, Diego Reforgiato
8. Digital Twins for the Built Environment
Calin Boje, Sylvain Kubicki, Annie Guerriero, Yacine Rezgui, Alain Zarli
9. The Building as a Platform: Predictive Digital Twinning
Tamer El-Diraby, Soroush Sobhkhiz
10. IoT and Edge Computing in the Construction Site
Aaron Costin, Janise McNair
11. Smart Cities and Buildings
Hendro Wicaksono, Baris Yuce, Kris McGlinn, Ozum Calli
Biography
Pieter Pauwels works as an Associate Professor at the Eindhoven University of Technology (TUe), the Department of the Built Environment. He previously worked at the Department of Architecture and Urban Planning at Ghent University (2008–2019). His work and interests are in information system support for the building life-cycle (architectural design, construction, building operation). With a lot of experience and knowledge in computer science and software development, he is involved in a number of industry-oriented research projects on topics affiliated to AI in construction, design thinking, Building Information Modelling (BIM), Linked Building Data (LBD), Linked Data in Architecture and Construction (LDAC), and Semantic Web technologies.
Kris McGlinn, Ph.D., is a Research Fellow and Computer Scientist in the ADAPT Centre, Trinity College Dublin. His research focus is knowledge engineering, in particular the application of Web of Data technologies for managing data from heterogeneous data sources. He has extensive experience working within the building domain, having worked on several EU and Irish national projects which explored topics ranging from smart building application development and evaluation, energy management in buildings, and the integration of building data with geospatial data. He was Principal Investigator for the H2020 SWIMing project, a Coordination and Support Action which explored the use of Semantic Web technologies for information modelling across EU projects and industry, and he was a founding chair of the W3C Linked Building Data community group, with the stated goal of developing ontologies for managing building data.
