ISSN (Print) : 2320 – 3765 ISSN (Online): 2278 – 8875 International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (An ISO 3297: 2007 Certified Organization) Website: www.ijareeie.com Vol. 6, Issue 12, December 2017 Copyright to IJAREEIE DOI:10.15662/IJAREEIE.2017.0612002 8811 The Role of Edge Computing in IOT: Enhancing Real-Time Data Processing Capabilities Mohit Mittal Dr. A.P.J. Abdul Kalam Technical University, Lucknow, Uttar Pradesh, India ABSTRACT: The quick expansion of the Internet of Things (IoT) has produced exponential data production requiring efficient processing solutions. Because of too high latency, limited bandwidth, and security concerns, real-time applications find conventional cloud-based architectures less suitable. Edge computing addresses these restrictions by processing data nearer the source, thus reducing latency, improving response times, and so raising overall system efficiency. Edge computing—by leveraging localized computation—allows real-time decision-making for significant IoT purposes like smart cities, industrial automation, healthcare, and autonomous autos. Filtering and evaluating data at the edge before passing relevant information to the cloud helps to clear network congestion as well. This study addresses the importance of edge computing in IoT, its primary benefits, challenges, and future prospects in providing intelligent, real-time, scalable IoT systems. KEYWORDS: Edge Computing, Internet of Things, Cloud computing, Real Time Data Processing I. INTRODUCTION The Internet of Things (IoT) facilitates bidirectional connection between smart devices via the use of sensors, enabling real-time data transfer [1]. The Internet of Things (IoT) is used in everyday life via "smart homes," "smart cities," and "smart healthcare." Internet of Things devices must comply with essential and standardized communication protocols, allowing enhanced identification, tracking, and administration of things. The International Telecommunication Union (ITU) defines the Internet of Things (IoT) as a worldwide framework that enhances services by connecting virtual and physical entities via communication networks. Applications developed for the Internet of Things (IoT) have issues with privacy, performance, security, and reliability because to the constrained storage and processing capabilities of IoT devices. The integration of Internet of Things (IoT) applications with cloud computing facilitates enhancements. Smart devices possess an abundance of data that may be sent across the network. This may often become an issue. Research from International Data Corporation (IDC) indicates that the quantity of Internet of Things (IoT) devices might attain 41.6 billion by 2025, generating 79.4 zettabytes of data. Issues related to volume, variety, velocity, legitimacy, and value are intrinsic to big data. Currently, the cloud oversees the management of all data generated by Internet of Things (IoT) devices. The integration of cloud computing with IoT has generated substantial expectations that the cloud alone cannot fulfil. The cloud networking architecture encounters many challenges including network utilization, data congestion, and cloud federation. The advent of IoT devices has heightened the significance of energy and resource conservation. Enhancing energy efficiency in smart devices and prolonging battery life are two issues posed by data transfer between IoT sensors and the cloud. Several issues may emerge with cloud computing: All Internet of Things sensors transmit their data to a central data center over a network. Upon processing, the data is sent to the actuators. The co-location of sensors and actuators inside the same device results in increased delay, rendering control information ineffective. Cloud computing encounters challenges in data processing and providing suitable computing services; edge computing presents a viable solution. Proximity of computing workloads to intelligent devices on an edge server significantly decreases data transmission latency and network capacity demands for cloud collaboration. The elimination of long-distance data transmission ensures guaranteed data security. Consequently, intelligent devices need to use edge computing to do activities of a flexible nature [6].