Smart Infrastructure Management.

Format:

Book

Author/Creator:

Qiu, Shi.

Contributor:

Zaheer, Qasim.

Wang, Jin.

Ai, Chengbo.

Language:

English

Physical Description:

1 online resource (438 pages)

Edition:

1st ed.

Place of Publication:

Chantilly : Elsevier, 2025.

Summary:

People and businesses rely on transportation networks every day, but what happens when critical assets fail unexpectedly or pollute our environment?Smart Infrastructure Management provides an interdisciplinary exploration of this intricate and dynamic landscape, enriching the theoretical and practical understanding of state-of-the-art.

Contents:

Front Cover

Front Matter

Copyright

Dedication

Contents

Contributors

About the authors

Preface

Acknowledgments

Abbreviations

Abstract

Chapter 1 Introduction to infrastructure management

1.1 Introduction

1.1.1 Historical background

1.1.2 Modern infrastructure

1.2 Understanding infrastructure management

1.2.1 Definition and key components of infrastructure management

1.2.2 From traditional to smart infrastructure management

1.2.3 Why infrastructure management is crucial?

1.2.4 Efficient infrastructure management

1.3 Technological advancements in infrastructure management

1.3.1 Role of technology in infrastructure management

1.3.2 Techniques in infrastructure management

1.4 Challenges in infrastructure management

1.5 Objectives

1.6 Book structure

1.7 Summary

References

Chapter 2 Fundamentals of computer science for infrastructure management

2.1 Historical overview of computer technologies

2.2 Fundamentals of computer science

2.3 Computer programming languages

2.3.1 Exploring programming languages for infrastructure management

2.3.2 Case studies on the application of programming languages in IM

2.4 Data structures and algorithms

2.4.1 Importance of data structures in handling infrastructure data

2.4.2 Algorithms used in infrastructure management

2.4.3 Real-world applications

2.5 Integration of computer science with infrastructure management

2.6 The future of infrastructure management: Emerging technologies

2.6.1 Internet of things

2.6.2 Cloud-edge-device integration

2.6.3 Artificial intelligence

2.6.4 Digital twins

2.6.5 Quantum computing.

2.7 Challenges and opportunities in computer science for IM

2.7.1 Current limitations and challenges

2.7.2 Opportunities for innovation and growth in the field

2.8 Summary

Chapter 3 Data collection and preprocessing

3.1 Data collection and processing in infrastructure management

3.2 Traditional data collection techniques

3.2.1 Overview

3.2.2 Limitations

3.3 Modern data collection techniques

3.3.1 Overview

3.3.2 Types of data collection techniques

3.3.3 Artificial intelligence for data collection optimization

3.3.4 Data collection: Real-World use cases

3.3.5 Limitations

3.4 Data integration and preprocessing

3.4.1 Data integration from multiple sources

3.4.2 Handling data inconsistencies

3.4.3 Data cleaning

3.4.4 Feature engineering

3.5 Challenges in data collection and preprocessing

3.5.1 Ensuring data accuracy and integrity

3.5.2 Managing large volumes of data

3.5.3 Handling data from diverse sources

3.5.4 Addressing privacy and security concerns

3.6 Case studies and methods

3.6.1 Case study 3.1

3.6.2 Method 3.1

3.6.3 Case study 3.2

3.7 Summary

Chapter 4 Infrastructure modeling and simulation

4.1 Introduction to modeling and simulation

4.2 Infrastructure modeling

4.3 Geographic information systems

4.3.1 GIS applications in infrastructure management

4.3.2 Case studies on gis in infrastructure management

4.4 Building information modeling

4.4.1 Overview

4.4.2 Method 4.1

4.4.3 Case studies

4.5 Digital twins

4.5.1 Overview

4.5.2 Method 4.2

4.5.3 Case study 4.3

4.6 Infrastructure simulation

4.7 Simulation tools and techniques

4.8 Challenges and solutions

4.9 Summary

Chapter 5 Asset management and maintenance

5.1 Introduction to asset management.

5.1.1 Overview and importance

5.1.2 Key objectives in infrastructure

5.2 Modern techniques for asset management

5.2.1 Digital transformation in asset management

5.2.2 Data analytics and predictive maintenance

5.2.3 Automation and internet of things integration

5.3 Asset inventory and assessment

5.3.1 Asset inventory methods

5.3.2 Condition and performance assessment

5.3.3 Risk-based asset prioritization

5.4 Understanding asset maintenance

5.4.1 Overview

5.4.2 Condition-based maintenance

5.4.3 Predictive maintenance techniques

5.4.4 Reliability-centered maintenance

5.4.5 Integration of digital technologies

5.5 Optimization of maintenance strategies

5.5.1 Strategy formulation for enhanced efficiency

5.5.2 Tools and techniques for optimized maintenance

5.5.3 Examples of optimized maintenance

5.6 Case study and method

5.6.1 Method 5.1

5.6.2 Case study 5.1

5.7 Challenges in asset management and maintenance

5.8 Summary

Chapter 6 Computational techniques

6.1 Overview of computational techniques

6.2 Traditional optimization techniques

6.3 Artificial intelligence

6.3.1 Machine learning

6.3.2 Deep learning

6.4 Applications of artificial intelligence

6.4.1 Computer vision

6.4.2 Image processing techniques

6.5 Methods

6.5.1 Method 6.1

6.5.2 Method 6.2

6.5.3 Method 6.3

6.6 Case studies

6.6.1 Case study 6.1

6.6.2 Case study 6.2

6.6.3 Case study 6.3

6.7 Future innovations

6.8 Summary

Chapter 7 Cybersecurity in infrastructure management

7.1 Overview

7.2 Importance of cybersecurity

7.3 Evolving cyber threat landscape in infrastructure systems

7.3.1 Types of cyber threats

7.3.2 Targeted systems and vulnerabilities

7.4 Security measures and best practices.

7.5 Regulatory compliance and cybersecurity policies

7.6 Cybersecurity technologies for infrastructure protection

7.6.1 AI and machine learning in cybersecurity

7.6.2 Blockchain for securing infrastructure data

7.7 Case studies on infrastructure cybersecurity

7.8 Summary

Chapter 8 Decision support systems

8.1 Foundations of decision support systems

8.1.1 Overview of decision support systems

8.1.2 Role in infrastructure management

8.2 Data-driven decision-making

8.2.1 Big data integration in infrastructure

8.2.2 Analytics and predictive modeling

8.3 Artificial intelligence and machine learning for decision support

8.4 Internet of things-enabled decision support

8.5 Real-time data processing frameworks

8.6 Visualization and immersive technologies for decision support systems

8.7 Methods and case study

8.7.1 Method 8.1

8.7.2 Method 8.2

8.7.3 Case study

8.8 Summary

Chapter 9 Smart cities and infrastructure management

9.1 The concept of smart infrastructure

9.1.1 Definition and characteristics

9.1.2 Components of smart infrastructure

9.2 Internet of things and sensor networks in smart cities

9.3 Smart cities and infrastructure interconnectivity

9.3.1 Interconnected systems for disaster response

9.3.2 Adaptive infrastructure planning for resilience

9.4 Sustainability and energy efficiency

9.4.1 Green infrastructure monitoring for sustainable urban development

9.4.2 Internet of things-enabled environmental impact assessments (EIA)

9.5 Ethical considerations in smart infrastructure

9.6 Challenges in implementing smart infrastructure

9.7 Summary

Chapter 10 Future trends and challenges

10.1 Emerging technologies in infrastructure management

10.2 Anticipated future trends.

10.2.1 Innovations in data acquisition

10.2.2 Advancements in computational techniques

10.3 Strategies for addressing future challenges

10.4 Environmental and regulatory challenges

10.5 Predictions for the future of infrastructure management

10.6 Summary

Chapter 11 Case studies

11.1 Overview

11.2 Challenges faced and lessons learned

11.3 Case studies

11.3.1 Case study 1: Interpretable cracks segmentation for structural health monitoring and maintenance

11.3.2 Case study 2: Interpretable fasteners fault detection using distillation vision transformer

11.3.3 Case study 3: Self-supervised contrastive anomaly detection in railway fasteners using point cloud data

11.4 Summary

Chapter 12 Conclusion and future directions

12.1 Recap of key points

12.2 The evolving role of computer science in infrastructure management

12.3 Future directions and research opportunities

12.4 Summary

Index

Back Cover.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

0-443-34018-8

OCLC:

1524045453