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This book focuses on the techniques of Artificial Intelligence that are mainly used in the power electronics field for the optimization of lost vehicle power. With the intention of optimizing the powerful energy of the vehicles and producing reliable energy, the most efficient methods, algorithms, and strategies of Ethical Artificial Intelligence (AI) are being applied. By employing machine learning methods, the optimization of power energy in vehicles can be quickly recovered and managed efficiently. In today’s bustling world, power energy is indispensable for progress, yet in congested Vehicular Ad-hoc Networks (VANETs), vehicles often face power depletion and decreased efficiency. This book explores these challenges, encompassing not only power but also other critical power electronics within vehicles. We aim to introduce innovative approaches, leveraging ethical AI methods, to optimize energy performance in the face of these difficulties. Through this exploration, we seek to provide practical insights into navigating congested VANET environments while upholding ethical principles in technological advancements. Our book will discuss the current power energy concerns faced by vehicles and also contribute a novel strategy to overcome those concerns. The employment of ethical AI in vehicular power energy will undoubtedly improve the effectiveness and production of vehicles.
This book is a detailed guide for researchers on ethical AI in powersystems, smart girds, blockchain, and IoT-​based electrical appliances. It is organized as follows:
• Chapter 1 sheds light on the integration of ethical machine learning with IoT. Recognizing the pivotal role of AI in societal advancement, this chapter emphasizes data-​centric decision-​making as a catalyst for improving our daily lives.
• Chapter 2 presents the applications of ethical machine learning in shaping industries, with a particular focus on its transformative impact on healthcare and transportation. The resulting technological integration is poised to usher in a new era of smart cities.
• Chapter 3 shifts its focus to the merger of IoT with ethical machine learning, unraveling basic concepts, addressing challenges, and presenting real-​time applications. This chapter serves as a guide, providing a nuanced understanding of the synergistic potential inherent in the integration of IoT and ethical machine learning, particularly in shaping the future landscape of communication systems.
• Chapter 4 provides a full overview of “Machine Learning in Wireless Communication Networks”, including AI techniques that are applied to develop a smartphone application for various advancements in the upcoming years.
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• Chapter 9 extends its reach to the IoT, exploring how AI can be harnessed to assess and mitigate risks in the intricate web of interconnected devices and systems.