Intelligent Technical Systems 1st edition by Natividad Mart´ınez Madrid, Ralf Seepold ISBN 1402098227 ‎ 978-1402098222
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Authors:Natividad Mart´ınez Madrid · Ralf E.D. Seepold , Series:Electrical Engineering [24] , Tags:Technology & Engineering; Industrial Design; Product; Mechanical; Engineering (General); General; Manufacturing; Language Arts & Disciplines; Library & Information Science , Author sort:Seepold, Natividad Mart´ınez Madrid · Ralf E.D. , Ids:Google; 9783642454356 , Languages:Languages:eng , Published:Published:Jan 2014 , Publisher:Springer Science & Business Media , Comments:Comments:Intelligent technical systems, which combine mechanical, electrical and software engineering with control engineering and advanced mathematics, go far beyond the state of the art in mechatronics and open up fascinating perspectives. Among these systems are so-called self-optimizing systems, which are able to adapt their behavior autonomously and flexibly to changing operating conditions. Self-optimizing systems create high value for example in terms of energy and resource efficiency as well as reliability. The Collaborative Research Center 614 “Self-optimizing Concepts and Structures in Mechanical Engineering” pursued the long-term aim to open up the active paradigm of self-optimization for mechanical engineering and to enable others to develop self-optimizing systems. This book is directed to researchers and practitioners alike. It provides a design methodology for the development of self-optimizing systems consisting of a reference process, methods, and tools. The reference process is divided into two phases the domain-spanning conceptual design and the domain-specific design and development. For the conceptual design a holistic approach is provided. Domain-specific methods and tools developed especially for the design and development of self-optimizing systems are described and illustrated by application examples. This book will enable the reader to identify the potential for self-optimization and to develop self-optimizing systems independently.
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ISBN 10: 1402098227
ISBN 13: 978-1402098222
Author: Natividad Mart´ınez Madrid, Ralf Seepold
Intelligent technical systems are networked, embedded systems incorporating real-time capacities that are able to interact with and adapt to their environments. These systems need innovative approaches in order to meet requirements like cost, size, power and memory consumption, as well as real-time compliance and security.
Intelligent Technical Systems covers different levels like multimedia systems, embedded programming, middleware platforms, sensor networks and autonomous systems and applications for intelligent engineering.
Each level is discussed by a set of original articles summarizing the state of the art and presenting a concrete application; they include a deep discussion of their model and explain all design decisions relevant to obtain a mature solution.
Intelligent Technical Systems 1st Table of contents:
Preface
- Introduction to Intelligent Technical Systems
- Scope and Objectives of the Book
- Who Should Read This Book
- How to Use the Book
Chapter 1: Introduction to Intelligent Systems
1.1. Defining Intelligent Systems
1.2. The Role of Intelligence in Technical Systems
1.3. Key Concepts in Intelligent Systems
1.4. Evolution and History of Intelligent Systems
1.5. Types of Intelligent Systems
1.6. Challenges in Designing Intelligent Technical Systems
Chapter 2: Fundamentals of Artificial Intelligence
2.1. Artificial Intelligence Overview
2.2. Machine Learning and Deep Learning
2.3. Expert Systems
2.4. Fuzzy Logic Systems
2.5. Neural Networks
2.6. Genetic Algorithms and Evolutionary Computation
2.7. Reinforcement Learning and Optimization
Chapter 3: Sensor Systems for Intelligent Technologies
3.1. Overview of Sensors in Technical Systems
3.2. Types of Sensors: Analog and Digital
3.3. Sensor Networks and IoT (Internet of Things)
3.4. Data Acquisition and Processing Techniques
3.5. Integration of Sensors in Intelligent Systems
3.6. Sensor Fusion and Multimodal Sensing
Chapter 4: Embedded Systems and Microcontrollers
4.1. Overview of Embedded Systems
4.2. Microcontroller Architecture and Design
4.3. Real-Time Operating Systems
4.4. Embedded System Development Tools
4.5. Interfacing Sensors and Actuators
4.6. Power Management in Embedded Systems
4.7. Communication Protocols for Embedded Systems
Chapter 5: Control Systems and Automation
5.1. Basics of Control Systems
5.2. Classical Control Techniques: PID Controllers
5.3. Modern Control Techniques: State-Space and Optimal Control
5.4. Intelligent Control Systems
5.5. Robotics and Automation in Industry
5.6. Motion Control and Actuators
5.7. Distributed Control Systems (DCS)
Chapter 6: Communication Systems in Intelligent Technical Systems
6.1. Fundamentals of Communication Systems
6.2. Wired vs. Wireless Communication
6.3. Network Protocols and Topologies
6.4. Data Transmission and Error Control
6.5. Real-Time Communication in Embedded Systems
6.6. Internet of Things (IoT) in Intelligent Systems
6.7. Security Challenges in Intelligent Systems
Chapter 7: Machine Vision and Image Processing
7.1. Introduction to Machine Vision
7.2. Components of a Vision System
7.3. Image Acquisition and Preprocessing
7.4. Object Recognition and Tracking
7.5. Applications of Machine Vision
7.6. Deep Learning in Image Processing
7.7. Challenges in Vision Systems Integration
Chapter 8: Intelligent Robotics and Autonomous Systems
8.1. Overview of Robotics
8.2. Robotic Actuators and Sensors
8.3. Path Planning and Navigation
8.4. Autonomous Vehicles and Drones
8.5. Collaborative Robots (Cobots)
8.6. Multi-Robot Systems and Coordination
8.7. AI for Robot Control and Decision Making
Chapter 9: Artificial Intelligence in Industrial Applications
9.1. AI in Manufacturing and Production Systems
9.2. Predictive Maintenance and Fault Diagnosis
9.3. Smart Factories and Industry 4.0
9.4. AI in Supply Chain Management
9.5. Quality Control and Process Optimization
9.6. Energy Management and Efficiency with AI
9.7. AI for Environmental Monitoring
Chapter 10: Future Trends in Intelligent Systems
10.1. Evolution of Intelligent Technical Systems
10.2. Integration of AI with Big Data and Cloud Computing
10.3. Quantum Computing and Its Impact on Intelligent Systems
10.4. The Role of 5G in Intelligent Systems Communication
10.5. Ethical Issues and Social Implications of Intelligent Systems
10.6. Human-Machine Interaction and Collaboration
10.7. Towards Fully Autonomous Systems and Smart Cities
Appendices
A.1. Glossary of Terms
A.2. Key Tools and Technologies for Intelligent Systems
A.3. References for Further Reading
A.4. Index
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