Smart Mechatronics

IoT, Sensors and Intelligent Automation
Erscheinungsjahr 2027
ISBN: 978-981-9287-81-9
Verlag: Springer

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

Reihe: Emerging Trends in Mechatronics

This book covers emerging topics, including AIoT-based vehicle safety, intelligent surveillance and tiny object detection, adaptive deep learning optimization, IoT-enabled smart farming, energy-efficient wireless sensor networks, edge computing for smart cities, reinforcement learning for blockchain consensus in IoT networks, AI-driven energy optimization for next-generation IoT devices, and intelligent driving analytics. This book demonstrates how machine learning, deep learning, reinforcement learning, edge intelligence, blockchain, and intelligent optimization can be integrated with mechatronic sensing and communication systems to address complex engineering challenges.

By combining theoretical foundations with practical implementations and application-oriented case studies, this book provides a comprehensive perspective on intelligent mechatronic systems and connected sensing technologies.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Agrawal, Akshat

Azizi, Aydin

Fachgebiete

• Technische Wissenschaften Bauingenieurwesen Verkehrsingenieurwesen, Verkehrsplanung
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

A Hybrid Cognitive AIoT Framework for Real Time Vehicle Collision Avoidance and Driver Drowsiness Detection Mechatronic Multi Sensor Techniques under Indian Road Conditions.- SurveilNet X Context Aware Deep Learning for Tiny Object Detection in Mechatronic Smart Surveillance Networks.- Self Adaptive Hyperparameter Optimization for Multi Scale Deep Surveillance Networks Towards Resilient Mechatronic Camera Systems.- An Energy Efficient Sleep Awake Multi Hop Clustering Protocol for Prolonging NetworkLifetime in Mechatronic Wireless Sensor Networks.- Key Challenges in Edge Computing for Smart Cities Coordinating Mechatronic Sensors and Actuators at Urban Scale.

Über Autor(innen)

Dr. Akshat Agrawal obtained his Ph.D. from GGSIPU, Delhi. He is currently working as an associate professor at Computer Science & Engineering, JK Lakshmipat University, Jaipur. Previously he served as a cluster lead at the School of Computer Science & Engineering, IILM University, Gurugram and served as an assistant professor (Senior Scale) Assistant Professor-III at Amity University Haryana, Amity School of Engineering and Technology. Dr. Agrawal has over 17 years of teaching and research experience. His primary research interests include Artificial Intelligence, Deep Learning, Artificial Neural Networks, Speech Processing, and Image Processing.

Dr. Aydin Azizi holds a Ph.D. in Mechanical Engineering with a specialization in Mechatronics, an M.Sc. in Mechatronics, and a B.Sc. in Mechanical Engineering. He is a fellow of the Higher Education Academy, an official instructor for the Siemens Mechatronic Systems Certification Program (SMSCP), and an editor-in-chief of the Emerging Trends in Mechatronics book series published by Springer Nature. He currently serves as a senior lecturer and the 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, artificial intelligence, and simulation techniques.