Название: Artificial Intelligence for Intelligent Systems: Fundamentals, Challenges, and Applications
Автор: Ullah Khan, Mariya Ouaissa, Mariyam Ouaissa, Muhammad Fayaz
Издательство: CRC Press
Серия: Intelligent Data-Driven Systems and Artificial Intelligence
Год: 2025
Страниц: 375
Язык: английский
Формат: pdf (true)
Размер: 26.3 MB
The aim of this book is to highlight the most promising lines of research, using new enabling technologies and methods based on AI/ML techniques to solve issues and challenges related to intelligent and computing systems. Intelligent computing easily collects data using smart technological applications like IoT-based wireless networks, digital healthcare, transportation, blockchain, 5.0 industry and deep learning for better decision making. AI enabled networks will be integrated in smart cities' concept for interconnectivity. Wireless networks will play an important role. The digital era of computational intelligence will change the dynamics and lifestyle of human beings. Future networks will be introduced with the help of AI technology to implement cognition in real-world applications. Cyber threats are dangerous to encode information from network. Therefore, AI-Intrusion detection systems need to be designed for identification of unwanted data traffic. Chapter 1 examines the interdisciplinary uses of AI and how it is revolutionizing several sectors, by introducing the concept of AI and the significance of a multidisciplinary approach in harnessing its potential. Chapter 2 introduces deep neural networks and their structures, methodologies, properties, and limits. Also discussed are the significant distinctions between deep neural networks and standard ML, as well as the big obstacles ahead. Chapter 3 focuses on providing a comprehensive comparative analysis of AI, Deep Learning (DL), and ML. It briefly overviews the state-of-the-art developments in these fields, highlighting key trends, challenges, and applications. Chapter 4 sheds light on the challenges and possibilities offered by these technologies by addressing the fundamental principles of Big Data mining and distributed processing.
