Authors : Tarandeep Kaur; Jasmine; Sandeep Sood

Volume/Issue : Volume 10 - 2025, Issue 4 - April

Google Scholar : https://tinyurl.com/bdyc7f57

Scribd : https://tinyurl.com/dy2btk66

DOI : https://doi.org/10.38124/ijisrt/25apr1169

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Abstract : Predictive maintenance (PdM) in Industrial Internet of Things (IIoT) is revolutionizing the way industries manage equipment health and operational efficiency. By leveraging real-time sensor data, machine learning algorithms, and advanced analytics, PdM enables proactive identification of potential failures before they occur. This approach minimizes unplanned downtime, optimizes maintenance schedules, and reduces operational costs. IIoT-based predictive maintenance integrates edge computing, cloud platforms, and artificial intelligence to process large-scale industrial data, facilitating intelligent decision-making. Key challenges include data security, scalability, and integration with legacy systems. This paper examines the architecture, methodologies, and benefits of predictive maintenance in Industrial Internet of Things (IIoT), highlighting its transformative impact on industrial automation and reliability.

Keywords : Industrial IoT, Predictive Maintenance, Industry 4.0, IIoT.

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