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The service providers are facilitated by edge computing to reach the deepest data, analytics are performed, knowledge is gathered and better decisions can be made [44]. Edge computing solves challenges (such as, security, latency, monitor and governance) extensively that are faced in various application services. The healthcare sector relies deeply on services that are fast-paced. Even a minimum latency would not be acceptable since it could stop access to vital services by patients. It has been proved that one of the pervasive challenges in the world is to ensure responsive healthcare. Edge computing can be used to achieve this as in the edge computing process the data is nearer to the source of data, thus eliminating unwanted latency. Some of the applications of edge computing [12] in healthcare applications are shown in Figure 4.2.

Self-Care by Patients: Wearable sensors, heartbeat monitoring, glucose monitoring in blood and various healthcare applications have grown common over the last decade. These sensors collect a huge amount of patient data which can be used by healthcare providers to diagnose the problem better. Also, the health of the patient can be monitored for a long time, creating an improved outcome. The problem here is to secure and handle such a huge amount of unstructured data. If these data are sent to the cloud, where it is sorted and analyzed, it would be highly difficult at the time of an emergency to provide an instant response to the patient. Thus edge computing is preferred to solve such problems [14, 40].

Rural Medicine: In rural and isolated areas it is difficult to provide quality healthcare even after the innovation of telemedicine. Since rural regions have poor internet connectivity or limited access to the internet, it is highly difficult to provide quality healthcare, and quick delivery of medicines is not possible. This can be made easier by the IoT devices combined with edge computing. IoT healthcare devices, which are small and portable, can be used to acquire data, process, and store and analyze a patient’s critical data, eliminating the need of internet connectivity. The patients using an IoT wearable can be quickly diagnosed and required measures can be taken immediately at the time of an emergency, and later the feedback or report is sent to the healthcare provider [11].

Figure 4.2 Some of the applications of edge computing.

Supply Chain: There are lots of medical equipment and medical components, from the smallest bandage to expensive surgery tools assisted by robots to save lives. They are maintained properly in the supply chain; if any disruption arises then significant risk is created in patient health outcomes. Thus edge devices are equipped with sensors for managing their inventories in a potential way. The data acquired from the equipment are analyzed to predict when the hardware will fail and RFID smart tags are used for efficient inventory management. This eliminates lots of paperwork, saves time and eliminates manual ordering [17].