Real-Time Stream Analytics and Edge/Iot-Based Data Processing For Modern Intelligent Systems

Abstract

The rapid proliferation of Internet of Things (IoT) devices and the emergence of real-time data generation have transformed the landscape of data analytics. Traditional cloud-centric analytics solutions face significant challenges in handling high-velocity, heterogeneous, and voluminous IoT data streams. Realtime stream analytics coupled with edge computing provides an efficient framework for processing and analyzing data closer to the source, reducing latency, improving response time, and optimizing network bandwidth. This paper explores the architecture, methodologies, challenges, and scope of realtime stream analytics integrated with edge/IoT-based data processing, highlighting the potential benefits for applications such as smart cities, industrial automation, healthcare monitoring, and intelligent transportation systems.

KEYWORDS: Real-time analytics, Stream processing, Edge computing, Internet of Things (IoT), Data processing, Low-latency computation, Intelligent systems