N. Rajesh Kumar – författare

Artificial Intelligence and Data Science in Electric Vehicle Technology and Infrastructure offers a comprehensive exploration of how AI and data science are revolutionizing the electric vehicle (EV) industry. It guides readers through the basic concepts of EV technology and explains how machine learning and blockchain optimize battery management, predictive maintenance, and secure fault detection. The book highlights cutting-edge techniques like sensor fusion and computer vision for autonomous driving, alongside real-time analytics and edge computing for low-latency AI applications. It also covers intelligent charging infrastructure, route optimization, and renewable energy integration and shares insights into cybersecurity, business models, and demand forecasting, complemented by practical case studies.This book is a useful resource for researchers, scientists, advanced students, software engineers, data scientists, R&D professionals, and other industrial personnel working at the intersection of computer science, electrical engineering, artificial intelligence, data science, and machine learning with an interest in advancing AI and ML applications in electric vehicle technologies.Demonstrates how AI algorithms improve battery management, energy use, and vehicle performance to tackle EV reliability and efficiency issuesExplains how predictive analytics leverage data science and machine learning to prevent vehicle malfunctions, minimizing downtime and reducing maintenance costsShowcases the development of smart charging infrastructure that utilizes data analysis to optimize energy distribution and significantly cut charging timesDiscusses the role of AI and data science in advancing autonomous driving capabilities, enhancing safety and operational efficiency in transportationHighlights innovative, data-driven solutions for sustainable energy, aiding in reducing carbon emissions and promoting environmentally friendly EV technologies

Revolutionize your IoT infrastructure with this guide to mastering quantum-enhanced machine learning algorithms and theoretical frameworks that are shattering the boundaries of classical computing to deliver unprecedented network performance and security. In a world increasingly reliant on interconnected devices and data-driven insights, the limitations of classical computing become ever more apparent. The convergence of quantum computing, machine learning, and the Internet of Things (IoT) heralds a new era of technological advancement, one where the boundaries of computational possibility are continually redefined. This book offers an in-depth examination of how quantum algorithms are utilized to improve the performance, security, and efficiency of IoT devices and networks. It connects theoretical concepts with practical applications, providing a comprehensive look at fundamental principles and advanced techniques in this rapidly growing field. Using case studies and real-world insights, this book gives readers the latest developments in quantum machine learning, artificial intelligence, and the smart Internet of Things, and their potential to create an accessible pathway to the future. Readers will find the volume: Demonstrates how to seamlessly integrate quantum computing and machine learning for next-gen IoT solutions;Explores the emerging field of quantum machine learning and its various applications for the AI-driven Internet of Things;Provides real-world examples and case studies demonstrating the power of quantum machine learning in smart IoT environments;Comprehensively covers a wide range of topics.Audience Researchers and engineers in machine learning, quantum computing, data science, the Internet of Things.

Revolutionize your IoT infrastructure with this guide to mastering quantum-enhanced machine learning algorithms and theoretical frameworks that are shattering the boundaries of classical computing to deliver unprecedented network performance and security.

In a world increasingly reliant on interconnected devices and data-driven insights, the limitations of classical computing become ever more apparent. The convergence of quantum computing, machine learning, and the Internet of Things (IoT) heralds a new era of technological advancement, one where the boundaries of computational possibility are continually redefined. This book offers an in-depth examination of how quantum algorithms are utilized to improve the performance, security, and efficiency of IoT devices and networks. It connects theoretical concepts with practical applications, providing a comprehensive look at fundamental principles and advanced techniques in this rapidly growing field. Using case studies and real-world insights, this book gives readers the latest developments in quantum machine learning, artificial intelligence, and the smart Internet of Things, and their potential to create an accessible pathway to the future.

Readers will find the volume:

Demonstrates how to seamlessly integrate quantum computing and machine learning for next-gen IoT solutions; Explores the emerging field of quantum machine learning and its various applications for the AI-driven Internet of Things; Provides real-world examples and case studies demonstrating the power of quantum machine learning in smart IoT environments; Comprehensively covers a wide range of topics.

Audience

Researchers and engineers in machine learning, quantum computing, data science, the Internet of Things.