Real-Time Health Monitoring and Predictive Maintenance of Medical Devices using Big Data Analytics

Abstract

Predictive maintenance is a worthwhile innovation in industry use, manufacturing, and health care, using big data analytics, the Internet of Things (IoT), and artificial intelligence (AI) to improve operations and minimize downtime. This paper overviews some predictive maintenance models, ranging from real-time analytics, deep learning strategies, and industrial big data platforms, and their usage in healthcare services, manufacturing, and smart infrastructure. The article discussed about core techniques like sensor-based monitoring, machine learning-based fault detection, and IoT-based preventive maintenance and emphasizes their significance in enhancing equipment reliability, reducing resources, and lowering operational expenditure. Challenges like data integration up to scalability and cybersecurity issues are also discussed. The article validates how predictive maintenance has become increasingly crucial in spearheading innovation and sustainability across industries, preventing reactive maintenance of assets, and enhancing decision-making.