INTEGRATING AI POWERED EDGE COMPUTING FOR SCALABLE AND EFFICIENT INTERNET OF THINGS APPLICATIONS
Abstract
The rapid expansion of the Internet of Things (IoT) has led to challenges in data processing, latency, and energy efficiency. Traditional cloud computing models struggle with real-time data processing due to network congestion and transmission delays. This paper explores the integration of Artificial Intelligence (AI) with Edge Computing to enhance scalability, efficiency, and real-time decision-making in IoT applications. AI-driven edge computing optimizes resource allocation, reduces latency, and enhances security by processing data closer to the source. The paper discusses recent advancements, challenges, and potential solutions in integrating AI with Edge Computing for IoT applications.