Real Time & Edge Analytics: Transforming Data Processing at the Source

Abstract

The rapid growth of Internet of Things (IoT), smart devices, industrial sensors and mobile applications has created a massive amount of data that needs to be processed instantly. Traditional cloud-centric data analytics models often face latency, bandwidth limitations and privacy issues when handling real-time data streams. Real Time and Edge Analytics has emerged as a powerful approach where data is processed near the source of generation rather than sending everything to centralized cloud. This paper presents a comprehensive review of Real Time & Edge Analytics, its architecture, enabling technologies, applications, advantages and challenges. It also discusses how edge intelligence is transforming sectors such as healthcare, smart cities, manufacturing and autonomous systems. The paper concludes with future research directions in this evolving field.

KEYWORDS: Edge Computing, Real Time Analytics, IoT, Stream Processing, Edge Intelligence, Low Latency