A review of IoT architectures in smart healthcare applications

Abstract

The Internet of Things (IoT) is revolutionizing numerous industries, including healthcare services, known as the Internet of Medical Things (IoMT). A large amount of generated data in IoMT applications need to be transmitted, analyzed, and stored. Consequently, the cloud-only architecture was proposed as being the best-fit organizational infrastructure. Indeed, cloud capabilities of processing, networking, and storage are overwhelming properties that make it outperform classical solutions for decades when it comes to healthcare applications. Nevertheless, this architecture could not keep up with the ever-growing amount of biomedical data. One of the main drawbacks of cloud architecture is the large latency, which prevents it from delivering real-time alerts to save the patient's life in critical situations. In this context, edge and fog computing become good alternatives to reduce health data management complexity and latency and therefore increase their reliability. This paper proposes a review of the most recent healthcare applications based on edge and fog computing, respectively. The selected research works of this survey are classified into four categories depending on their use case application. Furthermore, a comparison study helps extract relevant insights from several recent papers in the current literature to highlight their methodologies and purposes. The main concern is to emphasize what features and properties are to be considered most when designing a distributed healthcare system in an edge-fog architecture. Finally, we present some challenges to be addressed in healthcare applications along with the uprising of new technologies.