The Integration of IoT and Acoustic Analysis in Predictive Maintenance for Industrial Equipment

Karthikeyan Rajamani

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025, vol. 11, issue 1, 3080-3088

Abstract: This article explores the transformative impact of Internet of Things (IoT) technology and acoustic analysis on predictive maintenance in industrial settings. It examines how the integration of IoT sensors, real-time data collection, and advanced analytics is revolutionizing equipment maintenance across various industries, including manufacturing, energy, and logistics. The article delves into the innovative approach of microphone-based acoustic monitoring, highlighting its non-invasive nature and its synergy with traditional IoT sensor data. The benefits of this integrated approach, such as early failure detection, reduced downtime, cost savings, and extended equipment lifespan, are thoroughly discussed. The article also addresses the challenges in implementing these technologies and considers future directions, including the potential of AI and machine learning in further enhancing predictive maintenance capabilities. By providing a comprehensive overview of current practices and future trends, this article underscores the significant role of IoT and acoustic analysis in shaping the future of industrial maintenance and operational efficiency.

Keywords: Predictive Maintenance; Internet of Things (IoT); Acoustic Monitoring; Industrial Equipment; Machine Learning (search for similar items in EconPapers)
Date: 2025
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT251112325
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v11:y2025:i1:id:982

DOI: 10.32628/CSEIT251112325

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