The past few years have demonstrated how civil infrastructure continues to experience an unprecedented scale of extreme loading conditions (i.e. hurricanes, wildfires and earthquakes). Despite recent advancements in various civil engineering disciplines, specific to the analysis, design and assessment of structures, it is unfortunate that it is common nowadays to witness large scale damage in buildings, bridges and other infrastructure. The analysis, design and assessment of infrastructure comprises of a multitude of dimensions spanning a highly complex paradigm across material sciences, structural engineering, construction and planning among others. While traditional methods fall short of adequately accounting for such complexity, fortunately, computational intelligence presents novel solutions that can effectively tackle growing demands of intense extreme events and modern designs of infrastructure – especially in this era where infrastructure is reaching new heights and serving larger populations with high social awareness and expectations. Computational Intelligence for Analysis, Design and Assessment of Civil Infrastructure highlights the growing trend of fostering the use of CI to realize contemporary, smart and safe infrastructure. This is an emerging area that has not fully matured yet and hence the book will draw considerable interest and attention. In a sense, the book presents results of innovative efforts supplemented with case studies from leading researchers that can be used as benchmarks to carryout future experiments and/or facilitate development of future experiments and advanced numerical models. The book is written with the intention to serve as a guide for a wide audience including senior postgraduate students, academic and industrial researchers, materials scientists and practicing engineers working in civil, structural and mechanical engineering.

Showcases the state-of-the-art research in the area of AI with specific consideration to engineering, management and safety of civil construction. Offers detailed insights towards applying AI into design, construction and maintenance of infrastructure Leverages the various sub-disciplines of AI to arrive at modern, smart, and safe infrastructure as well as achieve a synergy between users/commuters and such structures. Covers practical case studies of primary interest to students, researchers, engineers, social scientists and government officials.

This handbook aims at modernizing the current state of civil engineering and firefighting, especially in this era where infrastructures are reaching new heights, serving diverse populations, and being challenged by unique threats. Its aim is to set the stage toward realizing contemporary, smart, and resilient infrastructure. The Handbook of Cognitive and Autonomous Systems for Fire Resilient Infrastructures draws convergence between civil engineering and firefighting to the modern realm of interdisciplinary sciences (i.e., artificial intelligence, IoT, robotics, sensing, and human psychology). As such, this work aims to revolutionize the current philosophy of design for one of the most notorious extreme events: fire. Unlike other publications, which are narrowed to one specific research area, this handbook cultivates a paradigm in which critical aspects of structural design, technology, and human behavior are studied and examined through chapters written by leaders in their fields. This handbook can also serve as a textbook for graduate and senior undergraduate students in Civil, Mechanical, and Fire Protection engineering programs as well as for students in Architectural and social science disciplines. Students, engineers, academics, professionals, scientists, firefighters, and government officials involved in national and international societies such as the American Society of Civil Engineers (ASCE), Society of Fire Protection Engineers (SFPE), National Fire Protection Association (NFPA), and Institute of Electrical and Electronics Engineers (IEEE), among others, will benefit from this handbook.

This book examines whether a global consensus is emerging on climate change and human mobility and presents evidence of a slow-moving but dynamic, step-by-step process of international policy development on climate-related mobility. Naser reviews the range of solutions offered to address climate-related mobility problems, such as extending the 1951 UN Refugee Convention, adopting an additional protocol to the UNFCCC or creating a new international treaty to support those facing climate-related migration and displacement problems. He examines the accumulating stock of international policies and initiatives relevant to climate-related mobility using a framework of six policy areas: human rights, refugees, climate change, disaster risk reduction, migration,and sustainable development. He uses this framework to define and summarise the main UN actions and milestones on climate-related mobility. Despite the difficult context affecting the global community of worsening climate change impacts and human rights under threat, Naser asserts that the foundations of global consensus on climate-related mobility have been built, particularly in the last decade. This book will be of great relevance to students, scholars and policy-makers with an interest in the increasing interface between climate change and human mobility policy issues.

This book examines whether a global consensus is emerging on climate change and human mobility and presents evidence of a slow-moving but dynamic, step-by-step process of international policy development on climate-related mobility. Naser reviews the range of solutions offered to address climate-related mobility problems, such as extending the 1951 UN Refugee Convention, adopting an additional protocol to the UNFCCC or creating a new international treaty to support those facing climate-related migration and displacement problems. He examines the accumulating stock of international policies and initiatives relevant to climate-related mobility using a framework of six policy areas: human rights, refugees, climate change, disaster risk reduction, migration,and sustainable development. He uses this framework to define and summarise the main UN actions and milestones on climate-related mobility. Despite the difficult context affecting the global community of worsening climate change impacts and human rights under threat, Naser asserts that the foundations of global consensus on climate-related mobility have been built, particularly in the last decade. This book will be of great relevance to students, scholars and policy-makers with an interest in the increasing interface between climate change and human mobility policy issues.

This handbook aims at modernizing the current state of civil engineering and firefighting, especially in this era where infrastructures are reaching new heights, serving diverse populations, and being challenged by unique threats. Its aim is to set the stage toward realizing contemporary, smart, and resilient infrastructure. The Handbook of Cognitive and Autonomous Systems for Fire Resilient Infrastructures draws convergence between civil engineering and firefighting to the modern realm of interdisciplinary sciences (i.e., artificial intelligence, IoT, robotics, sensing, and human psychology). As such, this work aims to revolutionize the current philosophy of design for one of the most notorious extreme events: fire. Unlike other publications, which are narrowed to one specific research area, this handbook cultivates a paradigm in which critical aspects of structural design, technology, and human behavior are studied and examined through chapters written by leaders in their fields. This handbook can also serve as a textbook for graduate and senior undergraduate students in Civil, Mechanical, and Fire Protection engineering programs as well as for students in Architectural and social science disciplines. Students, engineers, academics, professionals, scientists, firefighters, and government officials involved in national and international societies such as the American Society of Civil Engineers (ASCE), Society of Fire Protection Engineers (SFPE), National Fire Protection Association (NFPA), and Institute of Electrical and Electronics Engineers (IEEE), among others, will benefit from this handbook.

Accessible and practical framework for machine learning applications and solutions for civil and environmental engineers This textbook introduces engineers and engineering students to the applications of artificial intelligence (AI), machine learning (ML), and machine intelligence (MI) in relation to civil and environmental engineering projects and problems, presenting state-of-the-art methodologies and techniques to develop and implement algorithms in the engineering domain. Through real-world projects like analysis and design of structural members, optimizing concrete mixtures for site applications, examining concrete cracking via computer vision, evaluating the response of bridges to hazards, and predicating water quality and energy expenditure in buildings, this textbook offers readers in-depth case studies with solved problems that are commonly faced by civil and environmental engineers. The approaches presented range from simplified to advanced methods, incorporating coding-based and coding-free techniques. Professional engineers and engineering students will find value in the step-by-step examples that are accompanied by sample databases and codes for readers to practice with. Written by a highly qualified professional with significant experience in the field, Machine Learning includes valuable information on: The current state of machine learning and causality in civil and environmental engineering as viewed through a scientometrics analysis, plus a historical perspective Supervised vs. unsupervised learning for regression, classification, and clustering problems Explainable and causal methods for practical engineering problems Database development, outlining how an engineer can effectively collect and verify appropriate data to be used in machine intelligence analysis A framework for machine learning adoption and application, covering key questions commonly faced by practitioners This textbook is a must-have reference for undergraduate/graduate students to learn concepts on the use of machine learning, for scientists/researchers to learn how to integrate machine learning into civil and environmental engineering, and for design/engineering professionals as a reference guide for undertaking MI design, simulation, and optimization for infrastructure.