Edge Computing For Real-Time Iot App
Abstract
The exponential growth of the Internet of Things (IoT) has led to an unprecedented surge in data generation, creating challenges for traditional cloud-centric models in terms of latency, bandwidth consumption, and real-time responsiveness. Edge computing has emerged as a paradigm that processes data closer to the source, enabling faster decision-making, enhanced privacy, and improved system reliability. This paper explores the role of edge computing in real-time IoT applications, highlighting its layered architecture, key domains of application, and associated challenges. Case studies from healthcare, autonomous vehicles, industrial IoT, smart cities, and agriculture demonstrate its transformative potential. Furthermore, future directions such as AI integration, 5G-enabled edge deployments, federated learning, and sustainable energy-efficient designs are discussed. The findings emphasize that edge computing is not only an extension of cloud capabilities but also a critical enabler for next-generation real-time IoT ecosystems.
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