AI-Enabled Edge Computing: Revolutionizing IoT with Real-Time Optimization
Murali Krishna Pasupuleti · 2024
Abstract: This chapter explores how AI-enabled edge computing is revolutionizing the Internet of Things (IoT) by delivering real-time optimization and transforming data processing capabilities. By integrating AI algorithms directly into edge devices, edge computing reduces latency, enhances real-time decision-making, and enables IoT systems to operate with greater efficiency. The chapter discusses various applications, including predictive maintenance, anomaly detection, and dynamic optimization in sectors such as smart cities, healthcare, manufacturing, and autonomous vehicles. It also addresses the technical challenges of deploying AI at the edge, including hardware limitations, data security concerns, and the need for scalable infrastructure. Future trends, such as the integration of 5G and the potential impact of quantum computing, are explored as game-changers in the evolution of AI-driven edge computing for IoT optimization. Keywords: AI-enabled edge computing, IoT, real-time optimization, latency reduction, predictive maintenance, anomaly detection, smart cities, healthcare, manufacturing, autonomous vehicles, data security, 5G, quantum computing, scalable infrastructure.