Advances in Artificial Intelligence, Electronic Instruments and Information Systems
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Advances in Artificial Intelligence, Electronic Instruments and Information Systems

Advances in Artificial Intelligence, Electronic Instruments and Information Systems


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About the Book

This book is a compilation of high-quality scientific papers presented at International Conference on Artificial Intelligence, Electronic Instruments and Information Systems (AIEIIS 2025). This book addresses the integration challenge: AI is rapidly evolving, but practical deployment requires seamless interaction with physical devices, embedded systems, and secure information infrastructures. This book emphasizes end to end solutions, showing how advanced algorithms can be embedded into real world sensing, measurement, and control platforms. Contributors highlight how AI methods adapt under hardware constraints, achieve energy efficiency, handle uncertainty, and meet requirements of robustness, explainability, and regulatory compliance. This book is structured to balance theoretical advances with case studies and system prototypes. Part I covers foundations and methods for intelligent sensing, representation, and optimization. Part II presents platforms and architectures, including edge AI, distributed systems, and digital twin frameworks. Part III focuses on security, privacy, and reliability, reflecting the pressing demand for trustworthy AI in sensitive domains. Part IV illustrates application domains such as healthcare instrumentation, intelligent transportation, robotics, industrial inspection, environmental monitoring, and urban computing.



Table of Contents:

Binary classification CNN for Abnormal event detection.- Electroencephalography power spectrum estimation based on the AR model with Butterworth filter.- Optimization of Hazardous Material Detection Algorithm for Border Defense Vehicle Undercarriage Based on Improved YOLOv 5.- Emotional Agent Modeling and Application in Artificial Stock Market.- Deep Reinforcement Learning based Market Making in Limit Order Books.- Modeling and Simulation about Noise Trader Based on Prospect Theory.



About the Author :

Dr. Chien-Ming Chen is a professor in the School of Artificial Intelligence at Nanjing University of Information Science and Technology, China. He received his Ph.D. in Computer Science from National Tsing Hua University, Taiwan, in 2010, and previously held academic appointments at Harbin Institute of Technology (Shenzhen), China. His research interests include security and privacy, IoT systems, federated learning, and blockchain-based secure computing. He has published more than 150 SCI-indexed journal papers, including over 50 papers in IEEE and ACM journals, with several ESI Highly Cited Papers. His work has accumulated nearly 10,000 citations with an H-index of 56, and he holds 20 patents in China and the United States. Dr. Chen is a senior member of IEEE and a recipient of Shenzhen’s Overseas High-Level Talent Program. He serves as an executive editor of the International Journal of Information and Computer Security and as Associate Editor for several international journals.

 
Dr. Milan Simic holds a Ph.D., master’s, and bachelor’s degrees in Electronics Engineering, as well as a Graduate Diploma in Education. He is currently affiliated with the School of Engineering at RMIT University, Australia, and serves as a professor at MB University in Belgrade, Serbia, and an adjunct professor at the Kalinga Institute of Industrial Technology (KIIT), India. He was general editor and now is an honorary editor of the KES Journal. Dr. Simic has extensive international experience across industry and academia, including appointments at Honeywell Information Systems, CISCO Networking Academy and research institute. His multidisciplinary research spans biomedical engineering, such as gait monitoring using Deep Learning and brain computer interfaces, electrical and autonomous vehicles, intelligent transportation systems, physical systems modelling, management and engineering education.
 
Dr. Jia Hu is an associate professor in the Department of Computer Science at the University of Exeter, U.K. He received his Ph.D. in Computing Science from the University of Bradford in 2010 and previously held academic positions at Liverpool Hope University and the University of Exeter. His research focuses on distributed computing, communication networks, edge and cloud intelligence, federated learning, and AI-driven networking systems. He has published more than 200 research papers, including articles in leading journals such as IEEE Transactions on Computers, IEEE Transactions on Mobile Computing, IEEE Transactions on Parallel and Distributed Systems, and IEEE Journal on Selected Areas in Communications. His work has received multiple ESI Highly Cited Papers and numerous awards, including the IEEE Outstanding Paper Award and several IEEE Best Paper Awards.
 
Dr. Por Lip Yee is a full professor in the Faculty of Computer Science and Information Technology at Universiti Malaya, Malaysia. He is a senior member of IEEE and an internationally recognized researcher in security, cryptography, machine learning, computer vision, IoT authentication, steganography, watermarking, and blockchain technologies. He has authored more than 120 SCI/SCIE/SSCI-indexed journal papers and has secured over RM 7 million in competitive research funding as Principal Investigator. His research achievements have been recognized through numerous national and international awards, including multiple gold, silver, and bronze medals in innovation exhibitions. Prof. Por also has extensive editorial experience, serving as an associate editor for Frontiers in Public Health, Frontiers in Computer Science, and the Malaysian Journal of Computer Science, and as an editorial board member for CMC–Computers, Materials & Continua and TCRT (SAGE).


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Product Details
  • ISBN-13: 9783032237071
  • Publisher: Springer Nature Switzerland AG
  • Publisher Imprint: Springer Nature Switzerland AG
  • ISBN-10: 3032237076
  • Publisher Date: 18 May 2026


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