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Handbook of Cognitive and Autonomous Systems for Fire Resilient Infrastructures

  • Book
  • © 2022

Overview

  • Presents novel concepts to realize smart, autonomous infrastructure resilient to extreme loading conditions
  • Progresses the state of structural engineering and firefighting by modern and interdisciplinary approaches
  • Documents experiments and innovative approaches supplemented with case studies as benchmarks

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Table of contents (13 chapters)

Keywords

About this book

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 writtenby 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.


Editors and Affiliations

  • Clemson University, Clemson, USA

    MZ Naser

  • John Jay College of Criminal Justice, New York, USA

    Glenn Corbett

About the editors

M.Z. Naser is a faculty member at the School of Civil and Environmental Engineering and Earth Sciences & the Artificial Intelligence Research Institute for Science and Engineering (AIRISE) at Clemson University. His research aims to create Causal & explainable machine learning methodologies to discover new knowledge hidden within systems belonging to the domains of Structural fire engineering and Materials science to help us realize functional, sustainable, and resilient infrastructure.

Glenn Corbett is an Associate Professor of Fire Science and Public Management at John Jay College of Criminal Justice in New York City. He has spent over 40 years in the fields of fire protection and firefighting. He is a registered professional fire protection engineer in the State of Texas.  His interests include building disaster investigations and modernizing fire protection test standards and design practices.   

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