Cloud-Based Internet of Things in Healthcare Applications: A Systematic Literature Review

Abstract

Introduction: The Internet of Things (IoT) and Cloud computing are two recent technological advances whose potential have not been realized in a range of industries. These technologies have been used in healthcare systems to improve their performance. In this regard, the IoT generates a large amount of data; also, cloud computing is a viable option for data storage and complex computing. The purpose of this study is to identify and categorize various aspects of CIoT-based healthcare in terms of main application domains, sensors, wireless communication technologies, messaging protocols, cloud platforms, and artificial intelligence (AI) algorithms.Material and Methods: We conducted a literature systematic review and reported according to the PRISMA guideline. PubMed, IEEE, Scopus, and Web of Science were searched using the related keywords and their synonyms. Two independent authors reviewed the papers' eligibility according to the defined inclusion and exclusion criteria.Results: Of the 2,118 papers retrieved, 61 were eventually selected in the study. Results of the present study revealed that the majority of CIoT research works were applied to patient monitoring systems and cardiovascular patient monitoring systems using Amazon and IBM dominating Cloud platforms. In addition, the most widely used communication technologies for CIoT in healthcare are cellular networks (3G and 4G), Wi-Fi, and Bluetooth. Cardiovascular, environmental, and position sensors are also the most common types of sensors used in healthcare CIoT applications. Among the Cloud platform providers, Amazon and IBM have the highest utility in healthcare systems. The majority of the included studies used Cloud-based AI algorithms to diagnose, classify, and predict diseases.Conclusion: The integration of the Cloud into the IoT can support healthcare systems in terms of processing power, storage capacity, security, privacy, performance, reliability, and scalability. We suggest researchers conduct experimental studies to evaluate the effectiveness of the CIoT approach in healthcare applications.

Real-Time Remote Patient Monitoring: A Review of Biosensors Integrated with Multi-Hop IoT Systems via Cloud Connectivity

“…Real-time analytics empowers healthcare professionals with timely insights, particularly in emergencies or when monitoring rapidly changing health conditions. • Predictive analytics and ML: Cloud-based platforms leverage advanced analytics, including predictive analytics and ML algorithms, to derive meaningful insights from healthcare data [119]. These technologies enable the identification of patterns, trends, and potential health risks, supporting proactive interventions and personalized treatment plans.…”