Author: Sonal Patel
Abstract: The integration of Internet of Things (IoT) with real-time data analytics has revolutionized various industries, particularly in predictive maintenance. By leveraging sensors and smart devices, IoT systems collect vast amounts of data that can be analyzed in real time to predict equipment failures and maintenance needs. This paper explores the frameworks and technologies that enable predictive maintenance in IoT applications, focusing on manufacturing, healthcare, and smart home devices. We analyze key components such as data collection, processing, machine learning algorithms, and visualization techniques, as well as the challenges and benefits associated with implementing real-time predictive maintenance solutions.
Keywords: Real-Time Data Analytics, Internet of Things (IoT), Predictive Maintenance, Machine Learning, Smart Devices, Manufacturing, Healthcare, Smart Homes, Data Processing, Fault Detection.
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