ABSTRACT
Industrial automation increasingly relies on smart motor systems (SMS) that integrate Internet of Things (IoT) capabilities with real-time analytics to improve efficiency, reliability, and predictive maintenance. This paper presents an overview of IoT-enabled smart motors, data acquisition, edge analytics, and cloud-based monitoring architectures. The integration of sensors, communication networks, and machine learning algorithms allows for condition monitoring, energy optimization, and predictive maintenance in industrial environments. Tables and 2D figures are included to illustrate system architecture, performance metrics, and data flow. Challenges, such as cybersecurity and interoperability, as well as emerging trends in predictive analytics and AI-driven motor control, are also discussed.
KEYWORDS: - Smart motors, IoT, Industrial automation, Predictive analytics, Condition monitoring, Energy efficiency
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