Improving Real-Time Analytics through the Internet of Things and Data Processing at the Network Edge
DOI:
https://doi.org/10.63282/3050-922X.IJERET-V5I2P105Keywords:
Internet of Things (IoT), IoT devices, edge computing, real-time analytics, network edge, data processing, latency reduction, decision-making, smart systems, connected devices, big data, machine learning, artificial intelligence (AI), edge analytics, sensor data, distributed computing, cloud computing, data streams, automation, predictive analytics, scalability, low-latency, bandwidth optimization, IoT networks, smart cities, industrial IoT, autonomous systems, data sovereignty, fog computing, real-time decision-making, resource optimization, remote monitoring, network efficiencyAbstract
The Internet of Things (IoT) has had an exponential impact on the world in a very short span of time. It has reshaped the industries completely by providing them with a network of devices that can communicate with each other without any barriers. A major benefit of IoT is its capability of gathering a huge amount of live data, which is like oil for information regarding all kinds of processes, from industry to healthcare. On the other hand, the traditional means of sending this large amount of data to central servers for processing commonly result in delays, congestion of bandwidth, and inefficiency. These issues present obstacles to the success of IoT's numerous applications that are based on timely and precise information. Solving this dual is certainly edge computing. Thus, by processing data at or near the source rather than sending it to distant data centers, edge computing not only significantly reduces the distance data needs to travel but also minimizes the number of times data is transmitted, thus decreasing latency and enabling faster decision-making and consequently improving the overall performance of IoT systems. Such a decentralized approach also allows real-time analytics so that a business or an organization can act instantly on any detected event without facing the issue of delays that come from central processing. Besides that, edge computing makes the IoT system more reliable by cutting down on the times that it needs to rely on the cloud infrastructure, as the latter may have some instances when it is not available or faces some problems of connectivity
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