An IIoT Base Platform for Industrial Fault Detection: Implementation and Performance Analysis - A Comprehensive Review

In the contemporary industrial landscape, the integration of the Industrial Internet of Things (IIoT) has revolutionized traditional manufacturing and production paradigms. This research presents an IIoT Base Platform meticulously designed for the detection of faults within industrial settings. By amalgamating real-time data acquisition, advanced analytics, and intuitive visualization capabilities, the platform aims to proactively identify anomalies, offering a pivotal shift from reactive to predictive maintenance strategies. This study delineates the architecture of the platform, elucidates the fault detection algorithms employed, and presents a comprehensive performance analysis. Through empirical evaluations in diverse industrial environments, the platform demonstrates promising accuracy, scalability, and adaptability, underscoring its potential to augment operational efficiency and minimize downtime.