Analysing e-Healthcare Data from Internet of Things Devices and Cloud Computing

This chapter examines the opportunities and challenges posed by handling large-scale electronic healthcare (e-healthcare) data from edge/fog/Internet of Things (IoT) medical devices and cloud computing. With the increasing use of computing devices in healthcare, there is a need for efficient methods to process and analyze vast amounts of data for real-time processing, data security, privacy, and sharing. The chapter conducts a comprehensive review of existing research on integrating IoT medical devices and cloud computing environments using various machine learning models. It evaluates these models’ performance across domains such as wearable devices, electronic health records, and medical imaging systems, highlighting their potential for real-time data processing and secure data sharing to enhance healthcare outcomes. The study’s four main components include data acquisition, processing, analysis, and visualization, with data collected from wearable devices, electronic health records, and medical imaging systems. The findings have implications for healthcare providers, policymakers, and researchers seeking to leverage e-healthcare data to improve patient care and outcomes while potentially revolutionizing the healthcare industry and reducing costs through data visualization techniques.