AI and Machine Learning for Mechatronic Systems

Energy, Predictive Maintenance and Autonomous Applications
Erscheinungsjahr 2027
ISBN: 978-981-9272-18-1
Verlag: Springer Nature Singapore

Buch, Englisch, 226 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Emerging Trends in Mechatronics

This book gathers applied artificial intelligence and machine learning methods that supply exactly that layer, across autonomous vehicles, renewable-energy operations, and the condition monitoring of rotating machinery. Mechatronic systems increasingly depend on a layer of intelligence that turns sensor measurements into decisions and actions. It shows how learning-based models, from neural networks and ensemble regressors to reinforcement learning agents, are used to perceive, predict, and act within real mechatronic and energy systems.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Azizi, Aydin

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik

Inhaltsverzeichnis

Artificial intelligence in autonomous driving vehicles.-AI Based Predictive Cleaning Scheduler for Photovoltaic Panels in Arid Environments A Physics Informed Hybrid Machine Learning Approach.- Predictive Maintenance Of Wind Turbine Blades Using Vibration Analysis And Machine Learning.- Predictive Maintenance Using Vibration Analysis for Water Pumps.

Über Autor(innen)

Dr. Aydin Azizi holds a Ph.D. in mechanical engineering–mechatronics, a M.Sc. in mechatronics, and a B.Sc. in mechanical engineering. He is a as Fellow of the Higher Education Academy, Official Instructor for the Siemens Mechatronic Certification Program (SMSCP), and Editor-in-Chief of the book series Emerging Trends in Mechatronics published by Springer Nature Group. He currently serves as Senior Lecturer and Academic Partnership Liaison Manager at Oxford Brookes University. His current research focuses on investigating and developing novel techniques to model, control, and optimize complex systems, with expertise in control and automation, AI, and simulation techniques.