Buch, Englisch, 280 Seiten, Format (B × H): 156 mm x 234 mm
Optimization, Control, and Innovation
Buch, Englisch, 280 Seiten, Format (B × H): 156 mm x 234 mm
ISBN: 978-1-041-07655-1
Verlag: Taylor & Francis Ltd
Artificial Intelligence is no longer just a futuristic concept—it is transforming the way we design, build, and manage electrical machines and intelligent systems today. This groundbreaking volume showcases the convergence of AI, machine learning, and modern engineering, offering a window into the technologies shaping tomorrow’s mobility, energy, and digital ecosystems.
From intelligent safety in electric vehicles and predictive maintenance of machines to additive manufacturing, smart disaster management, and Industry 5.0 integration, each chapter presents state-of-the-art research with practical applications. Readers will discover how advanced algorithms enhance machine design, optimize charging station placement, secure cloud pipelines, and redefine data-driven decision-making. The book not only delivers technical depth but also addresses ethical and societal questions, ensuring a holistic understanding of AI’s role in the modern world.
Ideal for engineers, researchers, and technology leaders, this book provides both inspiration and actionable insights. Academics and graduate students will find it a rich resource for advancing research, while professionals in mobility, energy, and IoT industries can directly apply its ideas to real-world innovation. For anyone eager to harness the power of AI in engineering and beyond, this volume is an indispensable guide.
Zielgruppe
Academic, Postgraduate, and Undergraduate Advanced
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
1. Integration of Intelligent Safety Systems in Electric Vehicle Drive Machines 2. Deep Learning Architectures for Optimization of Electrical Machine Design 3. AI Techniques for Predictive Maintenance 4. Artificial Intelligence in Additive Manufacturing: A Comprehensive Review of Applications, Challenges, and Future Directions5. Enhanced Frilled Lizard Optimization (EFLO) Algorithm for Optimizing Decision Variables in Electric Vehicle Charging Station Placement 6. AI-Driven Optimization for Data-based Decision-Making and AR in Disaster Management 7. Conceptualizing the Access and Usage of AI as a Fundamental Right for Netizens 8. Industrial IoT: Transforming Connectivity and Response in the Digital Age 9. Harnessing Data Analytics for Intelligent Electrical Machine Design 10. AI/ML-Based Security in Cloud DevOps Pipelines: Predicting and Preventing Vulnerabilities 11. Design Considerations for Electric Machines in IoT-Based Parking Infrastructure 12. Integrating Industry 5.0 Principles into Electrical Machine Design: Exploring Opportunities and Challenges 13. Simulation and Analysis of Battery State of Charge (SOC) Using MATLAB for Energy Management Systems