Advances in Integrated Intelligent Systems Engineering
To be published by John Wiley & Sons, New York
Edited by: Waldemar Karwowski Vincent G. Duffy and Gavriel Salvendy
BOOK DESCRIPTION
Over the last five years, the field of systems engineering has undergone a significant transformation, driven by the integration of digital technologies, the need for transdisciplinary treatment of the subject matter, the impact of artificial intelligence, including deep learning and large language models, and the ever-increasing complexity of engineering projects globally.
Intelligent systems engineering is critical in today's complex and interconnected world. As technology advances and societal challenges become increasingly intricate, the need for intelligent approaches to designing, managing, and optimizing large-scale systems has never been more critical.
This edited book is designed to ensure a comprehensive coverage of the emerging field of integrated intelligent systems engineering by providing comprehensive knowledge, from the foundational principles through advanced methodologies and into practical applications and future directions.
Advances in Integrated Intelligent Systems Engineering will comprehensively cover principles, methodologies, tools, and case studies. The book will serve as both an authoritative guide for professionals and a foundational text for academics, by focusing on utilizing intelligent systems engineering to enhance efficiency, creativity, and collaboration, leading to the development and use of complex engineered systems.
EXPRESSION OF INTEREST
Prospective authors should carefully examine the Table of Contents provided below and send an expression of interest to contribute a chapter to this book directly to Dr. Waldemar Karwowski by email:
wkarwowski@gmail.com . YOUR PROPOSAL SHOULD INCLUDE:
- Proposed chapter title
- Co-authors' names and contact information (affiliation, address and email)
- A short description of the intended contribution (max 250 words)
- Proposed (tentative) Table of Contents (please refer to text below).
TENTATIVE TABLE OF CONTENTS
I: Foundations of Systems Engineering
1.1. Fundamental Concepts and Definitions
1.2. The Evolution of Systems Engineering
1.3. Systems Thinking: Principles and Practices
1.4. The Systems Engineering Process
1.5. Life Cycle Models and Methodologies
1.6. Requirements Engineering
II: Evolution of Systems Engineering
2.1. System Architecting and Design
2.2. Model-Based Systems Engineering (MBSE)
2.3. MBSE Implementation: Examples
2.4. Systems of Systems (SoS) Engineering
2.5. Integration and Management Techniques
2.6. Transdisciplinary Systems Engineering
III: Machine Learning in Systems Engineering
3.1. Machine Learning Foundations
3.2. Machine Learning Approach to Systems Engineering
3.3. Machine Learning Applications in Systems Engineering
3.4. Data Analytics for Systems Engineering
3.5. Machine Learning-Based Optimization and Decision-Making in Systems Engineering
3.6. Emerging Machine Learning Models for Systems Engineering
IV: Artificial Intelligence in Systems Engineering
4.1. Artificial Intelligence Approach to Systems Engineering
4.2. Large Language Models (LLM) in Systems Engineering
4.3. Data Analytics for Intelligent Systems Engineering
4.4. AI-driven Optimization and Decision-Making
4.5. Sustainable Intelligent Systems Engineering
4.6. Emerging AI-Based Intelligent Systems Engineering Tools
V: Managing Trust and Explainability in Integrated Intelligent Systems
Engineering
5.1. Trust in Intelligent Systems Engineering
5.2. Explainability Management in Intelligent Systems Engineering
5.3. Bias and Intelligent Systems Engineering
5.4. Ethical Concerns In Intelligent Systems Engineering
5.5. Integrated Design Perspective of Intelligent Systems Engineering
5.6. Regulatory Issues in Intelligent Systems Engineering
VI. Stakeholder Engagement in Integrated Intelligent Systems Engineering
6.1. Stakeholder Engagement: Industry and Government
6.2. AI-based Systems Engineering Regulations
6.3. Social Relevance and Ethical Considerations
6.4. International Relations Perspective
6.5. Integrating Diverse Disciplinary Perspectives
VII. Design and Operation of Integrated Intelligent Systems Engineering
7.1. Requirements for Design of Integrated Intelligent Systems Engineering
7.2. Human Factors In Design And Operation of Intelligent Systems Engineering
7.3. Human Centered Design, Usability, and User Experience
7.4. Requirements for Operation of Integrated Intelligent Systems Engineering
7.5. Integrating Design and Operation of Intelligent Systems Engineering
7.6. Future Implementation Challenges
VIII: Integrated Intelligent Systems Engineering: Applications
8.1. Applications in Healthcare
8.2. Applications in Transportation
8.3. Applications in Software Security
8.4. Applications in Aerospace and Space Exploration
8.5. Applications Infrastructure and Urban Systems
8.6. Applications in Military and Defense Systems
IX: Integrated Intelligent Systems Engineering: Case Studies
9.1. Case Studies in Healthcare
9.2. Case Studies in Transportation
9.3. Case Studies in Software Security
9.4. Case Studies in Aerospace and Space Exploration
9.5. Case Studies Infrastructure and Urban Systems
9.6. Case Studies in Military and Defense Systems
X: Future Directions in Integrated Intelligent Systems Engineering
10.1. New AI Technologies and Their Impact on Intelligent Systems Engineering
10.2. Emerging Intelligent Systems Engineering Principles
10.3. VR/AR Applications in Intelligent Systems Engineering
10.4. The Future of Intelligent Systems Engineering Education and Practice
10.5. Interdisciplinary Training and Skills Development
10.6. Future Trends, Challenges, and Opportunities.