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ISSN 2063-5346
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ANALYZING FAULT DETECTION FOR BIG DATA ANALYTICS BASED ON INDUSTRIAL INTERNET OF THINGS

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P.Jothi , Mona Dwivedi
» doi: 10.48047/ecb/2023.12. 4.139

Abstract

Recently, Fault detection is a subfield of control engineering monitoring systems, identifying a fault that has occurred and its location. Identifying problems with a system before they cause downtime or other damage is crucial for keeping industrial systems safe and reliable. Big Data Analytics (BDA) describes the method used to find relationships and trends in massive volumes of data to aid in making informed judgments.Improved wireless connection for real-time industrial data gathering is made possible by the Industrial Internet of Things (IIoT). Conventional Neural Network (CNN) is created for big data analytics with different recognition, potential mechanisms, and performance detection. Built-in tests and other fault-detection strategies often record the moment an issue occurs, alert humans to act, or launch an automated recovery process

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