Scalable AI: Leveraging Cloud and Edge Computing for Real-Time Analytics (International Journal of Scientific Research and Management (IJSRM), 2024)
With the rapid advancements in artificial intelligence (AI), the demand for scalable solutions to process vast amounts of data in real time has become more critical than ever. Traditional computing infrastructures often struggle with the computational and storage requirements necessary to support AI applications, especially for real-time analytics. This paper explores how combining cloud computing with edge computing can address these challenges by offering scalable, low-latency, and highly efficient AI systems for real-time decision-making. It examines the architectural frameworks, key technologies, and potential applications of AI in cloud and edge computing environments. Additionally, the paper investigates various methodologies for enhancing AI performance, data privacy, and communication efficiency. Finally, it discusses real-world case studies where this hybrid approach has been successfully implemented.