Machine Learning-Based Big Data Analytics for IoT-Enabled Smart Healthcare Systems

Abstract

Machine learning (ML) and big data analytics (BDA) have emerged as powerful technologies for extracting valuable information from the large amount of data generated by IoT-enabled smart healthcare systems. This chapter provides an overview of the application of ML and BDA in the context of IoT-enabled smart healthcare systems. IoT-enabled smart healthcare systems consider interconnected medical devices, wearables, and sensors to collect real-time data, including patient records, medical imaging data, and sensor data. In the near future, ML algorithms can be applied to this data to perform tasks such as predictive modeling, anomaly detection, classification, and clustering. ML algorithms enable healthcare providers to make informed decisions, improve patient outcomes, and optimize resource allocation. On other side, BDA platforms are important for handling and processing the large amount of data generated by IoT devices.