Ai Enabled Iot For Electrification And Connected Transportation
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AI Enabled IoT for Electrification and Connected Transportation
Author: Naveenkumar Marati
language: en
Publisher: Springer Nature
Release Date: 2022-06-04
This book presents an overview of artificial intelligence (AI) in the automotive section, especially in the modern era of green energy-based electrification of vehicles and smart transportation systems. The book also discusses different Internet of Things aspects involved in the automotive domain with AI. The book presents autonomous driving systems, advanced driver assistance systems (ADAS), autonomy, AI involvement, and machine learning techniques with challenges in electrification, prognostics, and diagnostics. AI and IoT are two emerging technologies, and their importance in other modern technology electrification on transportation, connected vehicle segment are discussed thoroughly in this book with different topologies. It also presents AI applications in the charging profile prediction, state of charge, state of health, battery lifetime, and battery temperature detection in dynamic conditions. Different algorithms are also given in the book to discuss the nearest point charging station for electric vehicle users. The book also discusses cybersecurity issues and challenges in the real-time environment for AI implementation, IoT in transportation, and autonomous driving. The other aspects of telematics, smart sensors for the implementation of the IoT, and AI are also discussed, especially in guidance and control aspects. The book will be useful for the researchers, practitioners, and industry people working in AI, IoT in the electrification and transportation segment.
Nature-inspired Metaheuristic Algorithms
This comprehensive text provides practical guidance for implementing nature-inspired algorithms and metaheuristics in real-life scenarios to solve complex optimization problems. It further demonstrates how nature inspired metaheuristic algorithms have the potential to contribute to multiple United Nations sustainable development goals such as climate action, clean energy, and sustainable cities. This book: Discusses load balancing and demand response using nature-inspired optimization techniques Presents energy-efficient routing and scheduling, energy management, and optimization using metaheuristic algorithms Covers disease diagnosis, and prognosis using metaheuristic algorithms, drug discovery, and development using nature-inspired optimization techniques Explains waste reduction and recycling, image processing, and computer vision using nature-inspired optimization techniques Illustrates medical image analysis and segmentation using Ant Colony optimization, and Particle Swarm optimization techniques Nature-inspired Metaheuristic Algorithms is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
Computational Intelligence in Bioprinting
COMPUTATIONAL INTELLIGENCE IN BIOPRINTING The book provides a comprehensive exploration of the evolving field of bioprinting in regenerative medicine and is an essential guide for professionals seeking a thorough understanding of the field. Computational Intelligence in Bioprinting provides a comprehensive overview of the evolving field of bioprinting in reformative medicine, defining the process of printing structures using viable cells, biomaterials, and living molecules. The primary goal is to provide substitutes for tissue implants, which might lead to eliminating the requirement for organ donors, as well as to transform animal testing for the learning and analysis of disease and the growth of treatments. The book offers a comprehensive overview of bioprinting technologies and their applications, emphasizing the integration of computation intelligence, artificial intelligence, and other computer science advancements in the field. By harnessing the power of computational intelligence techniques such as AI, machine learning, optimization algorithms, and data analytics, existing hurdles can be overcome and the full potential of bioprinting can be unlocked. The book covers an extensive range of topics, including bio-ink formulation and characterization, bioprinter hardware and software design, tissue and organ modeling, image analysis, process optimization, and quality control. Audience The book is aimed at professionals, practitioners and researchers in the fields of bioprinting, tissue engineering, and computational intelligence in medicine.