<![CDATA[This study explores the role of the Internet of Things (IoT) in machine maintenance, focusing on its integration with artificial intelligence (AI) and its impact on operational efficiency across various industries. A bibliometric analysis was conducted using data from Scopus, identifying key research trends, influential publications, and emerging technologies within the field. The findings highlight the increasing adoption of IoT for predictive maintenance in manufacturing, energy, and agriculture sectors. The study also reveals the growing intersection between IoT, machine learning, and data analytics, which enhances predictive capabilities and resource management. The results emphasize the importance of real-time monitoring and decision-making in improving industrial operations. However, challenges such as data security, interoperability, and adoption costs remain barriers to full implementation. This study provides valuable insights into the current state of research on IoT for machine maintenance, offering a foundation for future technological advancements and research directions.]]>
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