The amalgamation of artificial intelligence (AI), optimization techniques, and blockchain is revolutionizing how to conceptualize, design, and operate aerospace systems. While optimization techniques are pivotal in streamlining aerospace processes, security challenges have recently surfaced. AI and Blockchain Optimization Techniques in Aerospace Engineering delves into the transformative impact of technologies on various facets of the aerospace industry, offering a multidimensional solution to overcome security concerns and enhance the overall efficiency of aerospace systems

The book explores how machine learning reshapes aerospace systems by automating complex tasks through self/reinforced learning methods. From air traffic data analysis to flight scheduling, geographical information, and navigation, machine learning has become an indispensable tool, offering valuable insights that enhance aerospace operations. Simultaneously, blockchain technology, with its inherent characteristics of decentralization and tamper-proof ledgers, ensures transparency, accountability, and security in transactions, providing an innovative approach to data integrity and system resilience.

Designed for technology development professionals, academicians, data scientists, industrial experts, researchers, and students, the book offers a panoramic view of the latest innovations in the field. The content spans various critical areas, including aerodynamics, flight mechanics, gas dynamic medical imaging, analytics and diagnostics, image segmentation, deep learning-based computer-aided diagnosis systems, natural language processing, robotics-assisted systems, and bio-inspired algorithms for aerospace applications.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

Aeronautical Innovations
Aerospace Engineering
Analytics and Diagnostics
Artificial Intelligence Applications and Benefits
Autonomous Systems
Blockchain Optimization
Concepts and Technologies Aerodynamics
Control System Modeling
Data Integrity in Aerospace Engineering
Deep Learning-Based Computer-Aided Diagnosis System
Flight Mechanics
Flight Path Optimization
Gas Dynamic Medical Imaging
Image Segmentation
Machine Learning in Aerospace Engineering
Multidisciplinary Applications in Aerospace Engineering
Natural Language Processing
Optimization Techniques
Predictive Analytics
Predictive Fault Detection
Security Challenges in Aerospace Engineering
Speech Recognition Text Conversation
Tamper-Proof Ledger

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Editor/Author Biographies

U. Vignesh is currently an Assistant Professor Senior Grade 2 in School of Computer Science and Engineering, Vellore Institute of Technology (VIT) - Chennai. Prior to his recent appointment at the VIT, he was a Post-Doctoral Fellow in National Institute of Technology (NIT), Trichy – India. Dr. Vignesh received his undergraduate degree in B.Tech (IT) as well as his M.Tech (IT) degree from Anna University - Chennai, and his PhD in Computer Science and Engineering from VIT University - Chennai. Dr. Vignesh published several papers in preferred Journals, patents and chapters in books, and participated in a range of forums on computer science, social science, etc. He also presented various academic as well as research-based papers at several national and international conferences. His research activities are currently twofold: while the first research activity is set to explore the developmental role that society needs with technology such as, Artificial Intelligence; the second major research theme that he is pursuing is focused on the bioinformatics and data mining.

Rahul Ratnakumar received his Bachelor’s degree from College of Engineering Trivandrum, University of Kerala in Electrical and Electronics Engineering in 2009. He obtained Master of Engineering degree from Birla Institute of Technology and Science (BITS), Pilani with a specialization in Microelectronics in 2012. He worked on the project- Interface circuit design for a MEMS Vibratory Gyroscope, with the Analog and Mixed Signal Design group of CSIR-CEERI Pilani, India. He is completed his doctoral work in Malaviya National Institute of Technology (MNIT), Jaipur, India in the topic of VLSI implementation of Clustering Algorithms. He has a post-doctoral fellowship from the Department of Systems and Computer Engineering at Carleton University, Canada in the field of Autonomous Vehicles from Jan to June 2021. He is currently working as an Assistant Professor in the Department of Electronics and Communication Engg., Manipal Institute of Technology (MIT), Manipal Academy of Higher Education (MAHE), Manipal, Karnataka, India. His field of Interest are Digital VLSI architecture, Bio-inspired systems, Image Processing, System on Chip Design, Soft computing, Machine and Deep Learning.

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