Automation and Computational Intelligence for Road Maintenance and Management

Advances and Applications
1. Auflage 2022
ISBN: 978-1-119-80064-4
Verlag: Wiley

Buch, Englisch, 544 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 1212 g

Automation and Computational Intelligence for Road Maintenance and Management

A comprehensive computational intelligence toolbox for solving problems in infrastructure management

In Automation and Computational Intelligence for Road Maintenance and Management, a team of accomplished researchers delivers an incisive reference that covers the latest developments in computer technology infrastructure management. The book contains an overview of foundational and emerging technologies and methods in both automation and computational intelligence, as well as detailed presentations of specific methodologies.

The distinguished authors emphasize the most recent advances in the maintenance and management of infrastructure robotics, automated inspection, remote sensing, and the applications of new and emerging computing technologies, including artificial intelligence, evolutionary computing, fuzzy logic, genetic algorithms, knowledge discovery and engineering, and more.

Automation and Computational Intelligence for Road Maintenance and Management explores a universal synthesis of the cutting edge in parameters and indices to evaluate models. It also includes: - Thorough introductions to management science and the latest methods of automation and the structure and framework of automation and computing intelligence
- Comprehensive explorations of advanced image processing techniques, recent advances in fuzzy, and diagnosis automation
- Practical discussions of segmentation and fragmentation and different types of features and feature extraction methods
- In-depth examinations of methods of classification along with various developed methodologies and models of quantification, evaluation, and indexing in automation

Perfect for postgraduate students in road and transportation engineering, evaluation, and assessment, Automation and Computational Intelligence for Road Maintenance and Management will also earn a place in the libraries of researchers interested in or working with the evaluation and assessment of infrastructure.

Autoren/Hrsg.

Zakeri, Hamzeh

Nejad, Fereidoon Moghadas

Gandomi, Amir H

Fachgebiete

• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Chemische Verfahrenstechnik

Inhaltsverzeichnis

Dedication xiii

Preface xv

Author Biography xvii

1 Concepts and Foundations Automation and Emerging Technologies 1

1.1 Introduction 1

1.2 Structure and Framework of Automation and Key Performance Indexes (KPIs) 3

1.3 Advanced Image Processing Techniques 4

1.4 Fuzzy and Its Recent Advances 6

1.5 Automatic Detection and Its Applications in Infrastructure 6

1.6 Feature Extraction and Fragmentation Methods 8

1.7 Feature Prioritization and Selection Methods 8

1.8 Classification Methods and Its Applications in Infrastructure Management 10

1.9 Models of Performance Measures and Quantification in Automation 11

1.10 Nature-Inspired Optimization Algorithms (NIOAS) 12

1.11 Summary and Conclusion 14

1.12 Questions and Exercise 14

2 The Structure and Framework of Automation and Key Performance Indices (KPIs) 15

2.1 Introduction 15

2.2 Macro Plan and Architecture of Automation 16

2.2.1 Infrastructure Automation 16

2.2.2 Importance of Infrastructure Automation Evaluation 16

2.3 A General Framework and Design of Automation 17

2.4 Infrastructure Condition Index and Its Relationship with Cracking 20

2.4.1 Road Condition Index 20

2.4.2 Bridge Condition Index 28

2.4.3 Tunnel Condition Index 31

2.5 Automation, Emerging Technologies, and Futures Studies 31

2.6 Summary and Conclusion 32

2.7 Questions 32

Further Reading 32

3 Advanced Images Processing Techniques 35

Introduction 35

3.1 Preprocessing (PPS) 36

3.1.1 Edge Preservation Index (EPI) 39

3.1.2 Edge-Strength Similarity-Based Image Quality Metric (ESSIM) 39

3.1.3 QILV Index 40

3.1.4 Structural Content Index (SCI) 40

3.1.5 Signal-To-Noise Ratio Index (PSNR) 41

3.1.6 Computational time index (CTI) 41

3.2 Preprocessing Using Single-Level Methods 41

3.2.1 Single-Level Methods 42

Über Autor(innen)

Hamzeh Zakeri, PhD, is Adjunct Research Professor for the Department of Civil and Environment Engineering, Amirkabir University of Technology. His research interests include Automation, and Fuzzy type 2, Image Processing, Remote sensing, Machine Learning, Knowledge extraction, Hybrid Meta-heuristic Application in the field of pavement engineering.

Fereidoon Moghadas Nejad, PhD, is Professor and Head of Transportation Group at Amirkabir University of Technology. His research interests include Materials, and Testing, Image Processing, Automation, Fuzzy and Numerical Methods in Pavement and Railway Engineering.

Amir H. Gandomi, PhD, is Professor of Data Science and an ARC DECRA Fellow for the Faculty of Engineering and Information Technology at the University of Technology, Sydney. His research interests include Global Optimisation and (Big) Data Analytics using Machine Learning and Evolutionary Computations in particular.