Artificial Intelligence in Construction Engineering and Management
Artificial Intelligence in Construction Engineering and Management

Author: Limao Zhang

Publisher: Springer Nature

Published: 2021-06-18

Total Pages: 271

ISBN-13: 9811628424

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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.

AI-Based Services for Smart Cities and Urban Infrastructure
AI-Based Services for Smart Cities and Urban Infrastructure

Author: Lyu, Kangjuan

Publisher: IGI Global

Published: 2020-09-04

Total Pages: 353

ISBN-13: 1799850250

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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.

Artificial Intelligence in Structural Engineering
Artificial Intelligence in Structural Engineering

Author: Ian Smith

Publisher: Springer Science & Business Media

Published: 1998-07-15

Total Pages: 518

ISBN-13: 9783540648062

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This book presents the state of the art of artificial intelligence techniques applied to structural engineering. The 28 revised full papers by leading scientists were solicited for presentation at a meeting held in Ascona, Switzerland, in July 1998. The recent advances in information technology, in particular decreasing hardware cost, Internet communication, faster computation, increased bandwidth, etc., allow for the application of new AI techniques to structural engineering. The papers presented deal with new aspects of information technology support for the design, analysis, monitoring, control and diagnosis of various structural engineering systems.

A Primer on Machine Learning Applications in Civil Engineering
A Primer on Machine Learning Applications in Civil Engineering

Author: Paresh Chandra Deka

Publisher: CRC Press

Published: 2019-10-28

Total Pages: 211

ISBN-13: 0429836651

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Machine learning has undergone rapid growth in diversification and practicality, and the repertoire of techniques has evolved and expanded. The aim of this book is to provide a broad overview of the available machine-learning techniques that can be utilized for solving civil engineering problems. The fundamentals of both theoretical and practical aspects are discussed in the domains of water resources/hydrological modeling, geotechnical engineering, construction engineering and management, and coastal/marine engineering. Complex civil engineering problems such as drought forecasting, river flow forecasting, modeling evaporation, estimation of dew point temperature, modeling compressive strength of concrete, ground water level forecasting, and significant wave height forecasting are also included. Features Exclusive information on machine learning and data analytics applications with respect to civil engineering Includes many machine learning techniques in numerous civil engineering disciplines Provides ideas on how and where to apply machine learning techniques for problem solving Covers water resources and hydrological modeling, geotechnical engineering, construction engineering and management, coastal and marine engineering, and geographical information systems Includes MATLAB® exercises

Digital Transformation of the Design, Construction and Management Processes of the Built Environment
Digital Transformation of the Design, Construction and Management Processes of the Built Environment

Author: Bruno Daniotti

Publisher: Springer Nature

Published: 2019-12-30

Total Pages: 391

ISBN-13: 3030335704

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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.

Construction Project Management
Construction Project Management

Author: Peter Fewings

Publisher: Routledge

Published: 2013-05-07

Total Pages: 567

ISBN-13: 1136827617

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The role of the project manager continues to evolve, presenting new challenges to established practitioners and those entering the field for the first time. This second edition of Peter Fewings' groundbreaking textbook has been thoroughly revised to recognise the increasing importance of sustainability and lean construction in the construction industry. It also tackles the significance of design management, changing health and safety regulation, leadership and quality for continuous improvement of the service and the product. Using an integrated project management approach, emphasis is placed on the importance of effectively handling external factors in order to best achieve an on-schedule, on-budget result, as well as good negotiation with clients and skilled team leadership. Its holistic approach provides readers with a thorough guide in how to increase efficiency and communication at all stages while reducing costs, time and risk. Short case studies are used throughout the book to illustrate different tools and techniques. Combining the theories underpinning best practice in construction project management, with a wealth of practical examples, this book is uniquely valuable for practitioners and clients as well as undergraduate and graduate students for construction project management.

Applications of Machine Learning
Applications of Machine Learning

Author: Prashant Johri

Publisher: Springer Nature

Published: 2020-05-04

Total Pages: 404

ISBN-13: 9811533571

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This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.

Applications of Artificial Intelligence in Process Systems Engineering
Applications of Artificial Intelligence in Process Systems Engineering

Author: Jingzheng Ren

Publisher: Elsevier

Published: 2021-06-05

Total Pages: 542

ISBN-13: 012821743X

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Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. - Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms - Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis - Gives direction to future development trends of AI technologies in chemical and process engineering

Data Science in Engineering and Management
Data Science in Engineering and Management

Author: Zdzislaw Polkowski

Publisher: CRC Press

Published: 2021-12-31

Total Pages: 159

ISBN-13: 1000520846

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This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis. Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively. This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.

Strategic Safety Management in Construction and Engineering
Strategic Safety Management in Construction and Engineering

Author: Patrick X. W. Zou

Publisher: John Wiley & Sons

Published: 2015-03-26

Total Pages: 261

ISBN-13: 1118839358

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Although the construction and engineering sector makes important contributions to the economic, social, and environmental objectives of a nation, it has a notorious reputation for being an unsafe industry in which to work. Despite the fact that safety performance in the industry has improved, injuries and fatalities still occur frequently. To address this, the industry needs to evolve further by integrating safety into all decision making processes. Strategic Safety Management in Construction and Engineering takes a broad view of safety from a strategic decision making and management perspective with a particular focus on the need to balance and integrate ‘science’ and ‘art’ when implementing safety management. The principles covered here include the economics of safety, safety climate and culture, skills for safety, safety training and learning, safety in design, risk management, building information modelling, and safety research methods and the research-practice nexus. They are integrated into a strategic safety management framework which comprises strategy development, implementation, and evaluation. Practical techniques are included to apply the principles in the context of the construction and engineering industry and projects. Case studies are also provided to demonstrate the localised context and applications of the principles and techniques in practice.