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| data science for construction architecture and engineering: Artificial Intelligence in Construction Engineering and Management Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski, 2021-06-18 This book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in construction but also enhancing the competitiveness globally. |
| data science for construction architecture and engineering: Computer Aided Design Guide for Architecture, Engineering and Construction Ghassan Aouad, Song Wu, Angela Lee, Timothy Onyenobi, 2013-06-17 Recent years have seen major changes in the approach to Computer Aided Design (CAD) in the architectural, engineering and construction (AEC) sector. CAD is increasingly becoming a standard design tool, facilitating lower development costs and a reduced design cycle. Not only does it allow a designer to model designs in two and three dimensions but also to model other dimensions, such as time and cost into designs. Computer Aided Design Guide for Architecture, Engineering and Construction provides an in-depth explanation of all the common CAD terms and tools used in the AEC sector. It describes each approach to CAD with detailed analysis and practical examples. Analysis is provided of the strength and weaknesses of each application for all members of the project team, followed by review questions and further tasks. Coverage includes: 2D CAD 3D CAD 4D CAD nD modelling Building Information Modelling parametric design, virtual reality and other areas of future expansion. With practical examples and step-by step guides, this book is essential reading for students of design and construction, from undergraduate level onwards. |
| data science for construction architecture and engineering: Materials for Construction and Civil Engineering M. Clara Gonçalves, Fernanda Margarido, 2015-03-03 This expansive volume presents the essential topics related to construction materials composition and their practical application in structures and civil installations. The book's diverse slate of expert authors assemble invaluable case examples and performance data on the most important groups of materials used in construction, highlighting aspects such as nomenclature, the properties, the manufacturing processes, the selection criteria, the products/applications, the life cycle and recyclability, and the normalization. Civil Engineering Materials: Science, Processing, and Design is ideal for practicing architects; civil, construction, and structural engineers, and serves as a comprehensive reference for students of these disciplines. This book also: · Provides a substantial and detailed overview of traditional materials used in structures and civil infrastructure · Discusses properties of natural and synthetic materials in construction and materials' manufacturing processes · Addresses topics important to professionals working with structural materials, such as corrosion, nanomaterials, materials life cycle, not often covered outside of journal literature · Diverse author team presents expect perspective from civil engineering, construction, and architecture · Features a detailed glossary of terms and over 400 illustrations |
| data science for construction architecture and engineering: Digital Fabrication in Architecture, Engineering and Construction Luca Caneparo, 2013-10-02 Digital technologies are changing the relationship between design and construction: with computer models, CAD/CAM, and prototyping, designers can gain direct control of building and construction processes. The ability to digitally model designs, and thus to use those models directly in the context of production, creates a synthesis between design and construction in keeping with the tradition of the close relationship between design and craftsmanship, between the quality of the design and the rules of the craft. The evolution of the culture of design and construction is the underlying theme of this book. The aim is to discuss the direction that innovation is now taking, with a particular focus on today’s cutting-edge architectures. The method addresses the ways in which different societies have dealt with the issues of their age regarding design and construction, the different contributions provided by various techniques, and with them the meanings expressed by the architecture. As building design using digital tools requires specific skills in the fabrication processes and in the languages used by information technology, the book also offers a practical guide to new methods and techniques of managing and controlling fabrication for AEC. A systematic analysis of new skills used in the design process presents an overview of opportunities for architects and engineers. By collecting information on significant projects and analyzing them, the book explores the technical and artistic potential of digital technology. The cases studied are the outcomes of groundbreaking projects which were able to give form and significance to technological research. They show that digital tools are not the exclusive prerogative of large firms but can also be adopted by teams working across small and medium-sized firms – firms which have been able to use informed research to link innovative design with the possibilities offered by digital fabrication in architecture. |
| data science for construction architecture and engineering: Automation and Robotics in the Architecture, Engineering, and Construction Industry Houtan Jebelli, Mahmoud Habibnezhad, Shayan Shayesteh, Somayeh Asadi, SangHyun Lee, 2022-01-03 Automation and Robotics in the Architecture, Engineering, and Construction Industry provides distinct and unified insight into current and future construction robotics, offering readers a comprehensive perspective for constructing a road map and illuminating improvements for a successful transition towards construction robotization. The book covers the fundamentals and applications of robotics, autonomous vehicles, and human-perceptive machines at construction sites. Through theoretical and experimental analyses, it examines the potential of robotics and automated systems for current and future fieldwork operations and identifies the factors that determine their implementation pace, adoption scale, and ubiquity throughout the industry. The book evaluates the technical, societal, and economic aspects of adopting robots in construction, both as standalone and collaborative systems, which in return can afford the opportunity to investigate these AI-enabled machines more systematically. |
| data science for construction architecture and engineering: Biomimetic Research for Architecture and Building Construction Jan Knippers, Klaus G. Nickel, Thomas Speck, 2016-12-19 This book comprises a first survey of the Collaborative Research Center SFB-TRR 141 ‘Biological Design and Integrative Structures – Analysis, Simulation and Implementation in Architecture’, funded by the Deutsche Forschungsgemeinschaft since October 2014. The SFB-TRR 141 provides a collaborative framework for architects and engineers from the University of Stuttgart, biologists and physicists from the University of Freiburg and geoscientists and evolutionary biologists from the University of Tübingen. The programm is conceptualized as a dialogue between the disciplines and is based on the belief that that biomimetic research has the potential to lead everyone involved to new findings far beyond his individual reach. During the last few decades, computational methods have been introduced into all fields of science and technology. In architecture, they enable the geometric differentiation of building components and allow the fabrication of porous or fibre-based materials with locally adjusted physical and chemical properties. Recent developments in simulation technologies focus on multi-scale models and the interplay of mechanical phenomena at various hierarchical levels. In the natural sciences, a multitude of quantitative methods covering diverse hierarchical levels have been introduced. These advances in computational methods have opened a new era in biomimetics: local differentiation at various scales, the main feature of natural constructions, can for the first time not only be analysed, but to a certain extent also be transferred to building construction. Computational methodologies enable the direct exchange of information between fields of science that, until now, have been widely separated. As a result they lead to a new approach to biomimetic research, which, hopefully, contributes to a more sustainable development in architecture and building construction. |
| data science for construction architecture and engineering: Foundations of Data Science Avrim Blum, John Hopcroft, Ravindran Kannan, 2020-01-23 This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data. |
| data science for construction architecture and engineering: ECPPM 2022 - eWork and eBusiness in Architecture, Engineering and Construction 2022 Eilif Hjelseth, Sujesh F. Sujan, Raimar J Scherer, 2023-03-29 ECPPM 2022 - eWork and eBusiness in Architecture, Engineering and Construction contains the papers presented at the 14th European Conference on Product & Process Modelling (ECPPM 2022, Trondheim, Norway, 14-16 September 2022), and builds on a long-standing history of excellence in product and process modelling in the construction industry, which is currently known as Building Information Modelling (BIM). The following topics and applications are given special attention: Sustainable and Circular Driven Digitalisation: Data Driven Design and/or Decision Support Assessment and Documentation of Sustainability Information lifecycle Data Management: Collection, Processing and Presentation of Environmental Product Documentation (EPD) and Product Data Templates (PDT) Digital Enabled Collaboration: Integrated and Multi-Disciplinary Processes Virtual Design and Construction (VDC): Production Metrics, Integrated Concurrent Engineering, Lean Construction and Information Integration Automation of Processes: Automation of Design and Engineering Processes, Parametric Modelling and Robotic Process Automation Expert Systems: BIM based model and compliance checking Enabling Technologies: Machine Learning, Big Data, Artificial and Augmented Intelligence, Digital Twins, Semantic Technology Sensors and IoT Production with Autonomous Machinery, Robotics and Combinations of Existing and New Technical Solutions Frameworks for Implementation: International Information Management Series (ISO 19650), and Other International Standards (ISO), European (CEN) and National Standards, Digital Platforms and Ecosystems Human Factors in Digital Application: Digital Innovation, Economy of Digitalisation, Client, Organisational, Team and/or Individual Perspectives Over the past 25 years, the biennial ECPPM conference proceedings series has provided researchers and practitioners with a unique platform to present and discuss the latest developments regarding emerging BIM technologies and complementary issues for their adoption in the AEC/FM industry. |
| data science for construction architecture and engineering: Legal Aspects of Architecture, Engineering and the Construction Process Justin Sweet, Marc M. Schneier, 2012-01-01 The primary focus of this text is to provide a bridge for students between the academic world and the real world. This bridge is built through an understanding of what is law, how law is created, how law affects almost every activity of human conduct, and how legal institutions operate. Intended mainly for architectural and engineering students, but increasingly for those in business schools and law schools, this text features a clear, concise, and jargon-free presentation. It probes beneath the surface of legal rules and uncovers why these rules developed as they did, outlines arguments for and against these rules, and examines how they work in practice. Updated with the most recent developments in the legal aspects of architectural, engineering, and the construction processes, this text is also a valuable reference for practitioners and has been cited in over twenty-five court decisions. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version. |
| data science for construction architecture and engineering: Creative Solutions for a Sustainable Development Yuri Borgianni, Stelian Brad, Denis Cavallucci, Pavel Livotov, 2021-09-15 This book constitutes the refereed proceedings of the 21st International TRIZ Future Conference on Automated Invention for Smart Industries, TFC 2021, held virtually in September 2021 and sponsored by IFIP WG 5.4. The 28 full papers and 8 short papers presented were carefully reviewed and selected from 48 submissions. They are organized in the following thematic sections: inventiveness and TRIZ for sustainable development; TRIZ, intellectual property and smart technologies; TRIZ: expansion in breadth and depth; TRIZ, data processing and artificial intelligence; and TRIZ use and divulgation for engineering design and beyond. Chapter ‘Domain Analysis with TRIZ to Define an Effective “Design for Excellence’ is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. |
| data science for construction architecture and engineering: eWork and eBusiness in Architecture, Engineering and Construction Jan Karlshoj, Raimar Scherer, 2018-09-03 eWork and eBusiness in Architecture, Engineering and Construction 2018 collects the papers presented at the 12th European Conference on Product and Process Modelling (ECPPM 2018, Copenhagen, 12-14 September 2018). The contributions cover complementary thematic areas that hold great promise towards the advancement of research and technological development in the modelling of complex engineering systems, encompassing a substantial number of high quality contributions on a large spectrum of topics pertaining to ICT deployment instances in AEC/FM, including: • Information and Knowledge Management • Construction Management • Description Logics and Ontology Application in AEC • Risk Management • 5D/nD Modelling, Simulation and Augmented Reality • Infrastructure Condition Assessment • Standardization of Data Structures • Regulatory and Legal Aspects • Multi-Model and distributed Data Management • System Identification • Industrilized Production, Smart Products and Services • Interoperability • Smart Cities • Sustainable Buildings and Urban Environments • Collaboration and Teamwork • BIM Implementation and Deployment • Building Performance Simulation • Intelligent Catalogues and Services eWork and eBusiness in Architecture, Engineering and Construction 2018 represents a rich and comprehensive resource for academics and researchers working in the interdisciplinary areas of information technology applications in architecture, engineering and construction. In the last two decades, the biennial ECPPM (European Conference on Product and Process Modelling) conference series, as the oldest BIM conference, has provided a unique platform for the presentation and discussion of the most recent advances with regard to the ICT (Information and Communication Technology) applications in the AEC/FM (Architecture, Engineering, Construction and Facilities Management) domains. |
| data science for construction architecture and engineering: Advancements in Architectural, Engineering, and Construction Research and Practice AbdulLateef Olanrewaju, Silvana Bruno, 2024-06-30 This book offers a captivating discussion into the cutting-edge developments at the intersection of architecture, engineering, construction, and technology. With a focus on the power of big data analytics and computational design, this book delves into the transformative potential of these domains in shaping the built environment and business. This book discovers the fusion of architectural and engineering innovations with the capabilities of big data analytics, machine learning, and AI and explores how this parallelism is revolutionizing the design process, enhancing efficiency, and opening new horizons for creativity. This book steps into a world where predictive models, statistical algorithms, and what-if scenarios drive advancements in architectural and engineering practices and witnesses the seamless integration of technology in design generation, data visualization, task automation, and performance testing. It is an essential read for researchers and professionals seeking to leverage the potential of big data analytics to transform the built environment, maintaining the central role of humans. |
| data science for construction architecture and engineering: Data Science And Knowledge Engineering For Sensing Decision Support - Proceedings Of The 13th International Flins Conference Jun Liu, Jie Lu, Yang Xu, Luis Martinez, Etienne E Kerre, 2018-07-30 FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to include Computational Intelligence for applied research. The contributions of the FLINS conference cover state-of-the-art research, development, and technology for computational intelligence systems, with special focuses on data science and knowledge engineering for sensing decision support, both from the foundations and the applications points-of-view. |
| data science for construction architecture and engineering: The Complete Book of Colleges 2021 The Princeton Review, 2020-07 The mega-guide to 1,349 colleges and universities by the staff of the Princeton Review ... [including] detailed information on admissions, financial aid, cost, and more--Cover. |
| data science for construction architecture and engineering: ECPPM 2021 - eWork and eBusiness in Architecture, Engineering and Construction Vitaly Semenov, Raimar J Scherer, 2021-04-28 eWork and eBusiness in Architecture, Engineering and Construction 2021 collects the papers presented at the 13th European Conference on Product and Process Modelling (ECPPM 2021, Moscow, 5-7 May 2021). The contributions cover a wide spectrum of thematic areas that hold great promise towards the advancement of research and technological development targeted at the digitalization of the AEC/FM (Architecture, Engineering, Construction and Facilities Management) domains. High quality contributions are devoted to critically important problems that arise, including: Information and Knowledge Management Semantic Web and Linked Data Communication and Collaboration Technologies Software Interoperability BIM Servers and Product Lifecycle Management Systems Digital Twins and Cyber-Physical Systems Sensors and Internet of Things Big Data Artificial and Augmented Intelligence in AEC Construction Management 5D/nD Modelling and Planning Building Performance Simulation Contract, Cost and Risk Management Safety and Quality Sustainable Buildings and Urban Environments Smart Buildings and Cities BIM Standardization, Implementation and Adoption Regulatory and Legal Aspects BIM Education and Training Industrialized Production, Smart Products and Services Over the past quarter century, the biennial ECPPM conference series, as the oldest BIM conference, has provided researchers and practitioners with a unique platform to present and discuss the latest developments regarding emerging BIM technologies and complementary issues for their adoption in the AEC/FM industry. |
| data science for construction architecture and engineering: The Data Science Design Manual Steven S. Skiena, 2017-07-01 This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com) |
| data science for construction architecture and engineering: AI-Based Services for Smart Cities and Urban Infrastructure Lyu, Kangjuan, Hu, Min, Du, Juan, Sugumaran, Vijayan, 2020-09-04 Cities are the next frontier for artificial intelligence to permeate. As smart urban environments become possible, probable, and even preferred, artificial intelligence offers the chance for even further advancement through infrastructure and industry boosting. Opportunity overflows, but without thorough research to guide a complicated development and implementation process, urban environments can become disorganized and outright dangerous for citizens. AI-Based Services for Smart Cities and Urban Infrastructure is a collection of innovative research that explores artificial intelligence (AI) applications in urban planning. In addition, the book looks at how the internet of things and AI can work together to enable a real smart city and discusses state-of-the-art techniques in urban infrastructure design, construction, operation, maintenance, and management. While highlighting a broad range of topics including construction management, public transportation, and smart agriculture, this book is ideally designed for engineers, entrepreneurs, urban planners, architects, policymakers, researchers, academicians, and students. |
| data science for construction architecture and engineering: Advancements in Architectural, Engineering, and Construction Research and Practice AbdulLateef Olanrewaju, |
| data science for construction architecture and engineering: Data Science for Healthcare Sergio Consoli, Diego Reforgiato Recupero, Milan Petković, 2019-02-23 This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare. Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising. This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book. |
| data science for construction architecture and engineering: Architecture and Design: Breakthroughs in Research and Practice Management Association, Information Resources, 2018-11-02 Technological evolutions have changed the field of architecture exponentially, leading to more stable and energy-efficient building structures. Architects and engineers must be prepared to further enhance their knowledge in the field in order to effectively meet new and advancing standards. Architecture and Design: Breakthroughs in Research and Practice is an authoritative resource for the latest research on the application of new technologies and digital tools that revolutionize the work of architects globally, aiding in architectural design, planning, implementation, and restoration. Highlighting a range of pertinent topics such as design anthropology, digital preservation, and 3D modeling, this publication is an ideal reference source for researchers, scholars, IT professionals, engineers, architects, contractors, and academicians seeking current research on the development and creation of architectural design. |
| data science for construction architecture and engineering: Building Smart and Secure Environments Through the Fusion of Virtual Reality, Augmented Reality, and the IoT Nadesh RK, Shynu PG, Chiranji Lal Chowdhary, 2020 This book provides research on integrating a digital environment in professional settings through IoT design and virtual reality. It also explores developing methods of smart security as well as protocol support in IoT devices-- |
| data science for construction architecture and engineering: Human-Centered Data Science Cecilia Aragon, Shion Guha, Marina Kogan, Michael Muller, Gina Neff, 2022-03-01 Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets. Human-centered data science is a new interdisciplinary field that draws from human-computer interaction, social science, statistics, and computational techniques. This book, written by founders of the field, introduces best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of very large datasets. It offers a brief and accessible overview of many common statistical and algorithmic data science techniques, explains human-centered approaches to data science problems, and presents practical guidelines and real-world case studies to help readers apply these methods. The authors explain how data scientists’ choices are involved at every stage of the data science workflow—and show how a human-centered approach can enhance each one, by making the process more transparent, asking questions, and considering the social context of the data. They describe how tools from social science might be incorporated into data science practices, discuss different types of collaboration, and consider data storytelling through visualization. The book shows that data science practitioners can build rigorous and ethical algorithms and design projects that use cutting-edge computational tools and address social concerns. |
| data science for construction architecture and engineering: Digital Transformation of the Design, Construction and Management Processes of the Built Environment Bruno Daniotti, Marco Gianinetto, Stefano Della Torre, 2019-12-30 This open access book focuses on the development of methods, interoperable and integrated ICT tools, and survey techniques for optimal management of the building process. The construction sector is facing an increasing demand for major innovations in terms of digital dematerialization and technologies such as the Internet of Things, big data, advanced manufacturing, robotics, 3D printing, blockchain technologies and artificial intelligence. The demand for simplification and transparency in information management and for the rationalization and optimization of very fragmented and splintered processes is a key driver for digitization. The book describes the contribution of the ABC Department of the Polytechnic University of Milan (Politecnico di Milano) to R&D activities regarding methods and ICT tools for the interoperable management of the different phases of the building process, including design, construction, and management. Informative case studies complement the theoretical discussion. The book will be of interest to all stakeholders in the building process – owners, designers, constructors, and faculty managers – as well as the research sector. |
| data science for construction architecture and engineering: Data Engineering with Google Cloud Platform Adi Wijaya, 2022-03-31 Build and deploy your own data pipelines on GCP, make key architectural decisions, and gain the confidence to boost your career as a data engineer Key Features Understand data engineering concepts, the role of a data engineer, and the benefits of using GCP for building your solution Learn how to use the various GCP products to ingest, consume, and transform data and orchestrate pipelines Discover tips to prepare for and pass the Professional Data Engineer exam Book DescriptionWith this book, you'll understand how the highly scalable Google Cloud Platform (GCP) enables data engineers to create end-to-end data pipelines right from storing and processing data and workflow orchestration to presenting data through visualization dashboards. Starting with a quick overview of the fundamental concepts of data engineering, you'll learn the various responsibilities of a data engineer and how GCP plays a vital role in fulfilling those responsibilities. As you progress through the chapters, you'll be able to leverage GCP products to build a sample data warehouse using Cloud Storage and BigQuery and a data lake using Dataproc. The book gradually takes you through operations such as data ingestion, data cleansing, transformation, and integrating data with other sources. You'll learn how to design IAM for data governance, deploy ML pipelines with the Vertex AI, leverage pre-built GCP models as a service, and visualize data with Google Data Studio to build compelling reports. Finally, you'll find tips on how to boost your career as a data engineer, take the Professional Data Engineer certification exam, and get ready to become an expert in data engineering with GCP. By the end of this data engineering book, you'll have developed the skills to perform core data engineering tasks and build efficient ETL data pipelines with GCP.What you will learn Load data into BigQuery and materialize its output for downstream consumption Build data pipeline orchestration using Cloud Composer Develop Airflow jobs to orchestrate and automate a data warehouse Build a Hadoop data lake, create ephemeral clusters, and run jobs on the Dataproc cluster Leverage Pub/Sub for messaging and ingestion for event-driven systems Use Dataflow to perform ETL on streaming data Unlock the power of your data with Data Studio Calculate the GCP cost estimation for your end-to-end data solutions Who this book is for This book is for data engineers, data analysts, and anyone looking to design and manage data processing pipelines using GCP. You'll find this book useful if you are preparing to take Google's Professional Data Engineer exam. Beginner-level understanding of data science, the Python programming language, and Linux commands is necessary. A basic understanding of data processing and cloud computing, in general, will help you make the most out of this book. |
| data science for construction architecture and engineering: Ontology in the AEC Industry Raymond Issa, Ivan Mutis, 2015-06 |
| data science for construction architecture and engineering: The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy John MacIntyre, Jinghua Zhao, Xiaomeng Ma, 2020-11-04 This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field. |
| data science for construction architecture and engineering: BIM and Big Data for Construction Cost Management Weisheng Lu, Chi Cheung Lai, Tung Tse, 2018-10-11 This book is designed to help practitioners and students in a wide range of construction project management professions to understand what building information modelling (BIM) and big data could mean for them and how they should prepare to work successfully on BIM-compliant projects and maintain their competencies in this essential and expanding area. In this book, the state-of-the-art information technologies that support high-profile BIM implementation are introduced, and case studies show how BIM has integrated core quantity surveying and cost management responsibilities and how big data can enable informed decision-making for cost control and cost planning. The authors' combined professional and academic experience demonstrates, with practical examples, the importance of using BIM and particularly the fusion of BIM and big data, to sharpen competitiveness in global and domestic markets. This book is a highly valuable guide for people in a wide range of construction project management and quantity surveying roles. In addition, implications for project management, facilities management, contract administration, and dispute resolution are also explored through the case studies, making this book essential reading for built environment and engineering professionals. |
| data science for construction architecture and engineering: Data Science Zhiwen Yu, Qilong Han, Hongzhi Wang, Bin Guo, Xiaokang Zhou, Xianhua Song, Zeguang Lu, 2023-09-14 This two-volume set (CCIS 1879 and 1880) constitutes the refereed proceedings of the 9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023 held in Harbin, China, during September 22–24, 2023. The 52 full papers and 14 short papers presented in these two volumes were carefully reviewed and selected from 244 submissions. The papers are organized in the following topical sections: Part I: Applications of Data Science, Big Data Management and Applications, Big Data Mining and Knowledge Management, Data Visualization, Data-driven Security, Infrastructure for Data Science, Machine Learning for Data Science and Multimedia Data Management and Analysis. Part II: Data-driven Healthcare, Data-driven Smart City/Planet, Social Media and Recommendation Systems and Education using big data, intelligent computing or data mining, etc. |
| data science for construction architecture and engineering: Mechanical and Electrical Systems in Architecture, Engineering, and Construction Joseph B. Wujek, Frank R. Dagostino, 2010 Mechanical and electrical systems in architecture, engineering, and construction is intended for everyone involved in the construction industry. The book contains materials for those interested in the design of building electrical, lighting, plumbing, HVAC, fire protection, and telecommunications systems to those who must understand building mechanical and electrical materials and equipment in order to successfully envision, design, draw, construct, or operate a building or project. |
| data science for construction architecture and engineering: Construction 4.0 Anil Sawhney, Michael Riley, Javier Irizarry, 2020-02-06 Modelled on the concept of Industry 4.0, the idea of Construction 4.0 is based on a confluence of trends and technologies that promise to reshape the way built environment assets are designed, constructed, and operated. With the pervasive use of Building Information Modelling (BIM), lean principles, digital technologies, and offsite construction, the industry is at the cusp of this transformation. The critical challenge is the fragmented state of teaching, research, and professional practice in the built environment sector. This handbook aims to overcome this fragmentation by describing Construction 4.0 in the context of its current state, emerging trends and technologies, and the people and process issues that surround the coming transformation. Construction 4.0 is a framework that is a confluence and convergence of the following broad themes discussed in this book: Industrial production (prefabrication, 3D printing and assembly, offsite manufacture) Cyber-physical systems (actuators, sensors, IoT, robots, cobots, drones) Digital and computing technologies (BIM, video and laser scanning, AI and cloud computing, big data and data analytics, reality capture, Blockchain, simulation, augmented reality, data standards and interoperability, and vertical and horizontal integration) The aim of this handbook is to describe the Construction 4.0 framework and consequently highlight the resultant processes and practices that allow us to plan, design, deliver, and operate built environment assets more effectively and efficiently by focusing on the physical-to-digital transformation and then digital-to-physical transformation. This book is essential reading for all built environment and AEC stakeholders who need to get to grips with the technological transformations currently shaping their industry, research, and teaching. |
| data science for construction architecture and engineering: Structural Health Monitoring Based on Data Science Techniques Alexandre Cury, Diogo Ribeiro, Filippo Ubertini, Michael D. Todd, 2021-10-23 The modern structural health monitoring (SHM) paradigm of transforming in situ, real-time data acquisition into actionable decisions regarding structural performance, health state, maintenance, or life cycle assessment has been accelerated by the rapid growth of “big data” availability and advanced data science. Such data availability coupled with a wide variety of machine learning and data analytics techniques have led to rapid advancement of how SHM is executed, enabling increased transformation from research to practice. This book intends to present a representative collection of such data science advancements used for SHM applications, providing an important contribution for civil engineers, researchers, and practitioners around the world. |
| data science for construction architecture and engineering: Architecture | Design | Data Phillip Bernstein, 2018-09-24 A systemic transformation is underway in architectural design, engineering and construction. The discipline and profession of architecture is being reshaped in a moment where information, insight and predictions generated during the design process move into construction no longer essentially via drawings. Other, more profound digital techniques yield fundamentally different workflows, responsibilities and business models for architects. This book offers a comprehensive framework, detailed analysis and critical assessment of the challenges and opportunities inherent in those changes. The author sets out to provide direction for a new era in architectural creation that can be understood and managed by a profession which must become better equipped to direct its future. |
| data science for construction architecture and engineering: Contemporary Problems in Architecture and Construction Darja Kubečková, 2014 Selected, peer reviewed papers from the 6th International Conference on Contemporary Problems of Architecture and Construction, June 24-27, 2014, Ostrava, |
| data science for construction architecture and engineering: Readings in Information Visualization Stuart K. Card, Jock Mackinlay, Ben Shneiderman, 1999-01-25 This groundbreaking book defines the emerging field of information visualization and offers the first-ever collection of the classic papers of the discipline, with introductions and analytical discussions of each topic and paper. The authors' intention is to present papers that focus on the use of visualization to discover relationships, using interactive graphics to amplify thought. This book is intended for research professionals in academia and industry; new graduate students and professors who want to begin work in this burgeoning field; professionals involved in financial data analysis, statistics, and information design; scientific data managers; and professionals involved in medical, bioinformatics, and other areas. Features Full-color reproduction throughout Author power team - an exciting and timely collaboration between the field's pioneering, most-respected names The only book on Information Visualization with the depth necessary for use as a text or as a reference for the information professional Text includes the classic source papers as well as a collection of cutting edge work |
| data science for construction architecture and engineering: Data Analytics in Reservoir Engineering Sathish Sankaran, Sebastien Matringe, Mohamed Sidahmed, 2020-10-29 Data Analytics in Reservoir Engineering describes the relevance of data analytics for the oil and gas industry, with particular emphasis on reservoir engineering. |
| data science for construction architecture and engineering: Data Science and Big Data Analytics EMC Education Services, 2014-12-19 Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today! |
| data science for construction architecture and engineering: eWork and eBusiness in Architecture, Engineering and Construction Z. Turk, R. Scherer, 2002-01-01 This is a comprehensive review of research related to construction informatics, with a particular focus on the related 5th framework EU projects on product and process technology and the implementation of the new economy technologies and business models in the construction industry. |
| data science for construction architecture and engineering: eWork and eBusiness in Architecture, Engineering and Construction. ECPPM 2006 Manuel Martinez, Raimar Scherer, 2006-08-24 The task of structuring information on built environment has presented challenges to the research community, software developers and the industry for the last 20 years. Recent work has taken advantage of Web and industry standards such as XML, OWL, IFC and STEP. Another important technology for the fragmented AEC industry is digital communication. Wired or wireless, it brings together architects, engineers and construction site workers, enabling them to exchange information, communicate and work together. Virtual enterprise organization structures, involving mobile teams over distance, are highly compatible with the needs of the construction industry. |
| data science for construction architecture and engineering: eWork and eBusiness in Architecture, Engineering and Construction Gudni Gudnason, Raimar Scherer, 2012-07-06 Since 1994, the European Conferences of Product and Process Modelling (www.ecppm.org) have provided a review of research, development and industrial implementation of product and process model technology in the Architecture, Engineering, Construction and Facilities Management (AEC/FM) industry. Product/Building Information Modelling has matured significantly in the last few years and has never been closer to having a permanent impact on the AEC/FM industry as a mainstream technology. In this context the 9th European Conference of Product and Process Modelling provided a forum for leading experts to discuss the latest achievements, emerging trends and future directions in product and process modelling technology in this dynamic and fragmented industry, focusing on integrated project working, value-based life cycle management and intelligent and sustainable buildings and construction. eWork and eBusiness in Architecture, Engineering and Construction 2012 provides a comprehensive overview of topics including BIM in all life-cycle stages, ICT for energy efficiency, smart buildings and environmental performance, energy and building simulation, knowledge and semantic modelling, visualization technologies as well as tools and methods to support innovations in design and construction processes. It further includes the proceedings of the 3rd Workshop on eeBuildings Data Models (Energy Efficiency Vocabularies), which aim to identify ICT Energy Efficiency Vocabularies and Ontologies to foster interoperability of Energy Efficiency Management Systems. eWork and eBusiness in Architecture, Engineering and Construction 2012 will be of interest to academics and professionals working in the interdisciplinary area of information technology in architecture, engineering and construction. |
| data science for construction architecture and engineering: Cooperative Design, Visualization, and Engineering Yuhua Luo, 2015-09-21 This book constitutes the refereed proceedings of the 12th International Conference on Cooperative Design, Visualization, and Engineering, CDVE 2015, held in Mallorca, Spain, in September 2015. The 30 full papers presented together with 4 short papers were carefully reviewed and selected from numerous submissions. There is a group of papers dressing the big data related to the cooperative work. It includes the information modeling, intensive task management, how to use the cloud technology to foster the cooperation etc. To deal with the social network issues is the topic of another group of papers in this volume. They range from creating programming languages to automate cooperative processes, social network information visualization, and the ranking cooperative research teams by analyzing the social network data. |
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