AN IN-DEPTH STUDY OF MACHINE LEARNING AND AI APPLICATIONS IN EDGE COMPUTING

In recent years, the integration of machine learning and artificial intelligence with edge computing has brought about a significant transformation across industries worldwide. By shifting
computational intelligence closer to the source of data, this convergence enables faster insights, real-time decision-making, and improved operational efficiency. Traditionally, data processing has been handled through centralized cloud computing systems. However, with the rapid expansion of IoT devices and the increasing demand for low-latency performance, edge computing has emerged as a vital solution. It facilitates local data processing, thereby reducing delays, enhancing reliability, and minimizing dependence on distant cloud servers.
The combination of AI and edge computing has unlocked new opportunities in sectors such as healthcare, transportation, industrial automation, smart cities, and retail. This powerful synergy supports real-time analytics, autonomous decision-making, and intelligent operations directly at the network edge.
This book, Artificial Intelligence and Machine Learning for Edge Computing, is designed as a comprehensive resource for researchers, engineers, students, and industry professionals. It presents both foundational principles and advanced topics, including AI system architecture, development tools, 5G technologies, edge analytics, fog computing, and microservices architecture. The fusion of AI and edge computing represents a major technological shift, driving innovation, operational excellence, and digital transformation on a global scale. This work also acknowledges the valuable contributions of researchers and industry experts whose knowledge and insights have supported the development of this book.-Authors