Evaluation of an Intelligent Edge Computing System for the Hospital Intensive Care Unit

The evolution of medical technology along with information and communication technologies has accelerated the development and operationalization of smart hospitals recently. Traditionally, such hospitals typically rely on cloud computing platforms for data treatment and processing. However, the expansion and popularization of Internet of Medical Things (IoMT) devices and constant data monitoring have resulted in massive amounts of generated data, leading to the overload of the cloud infrastructure. This results in high power consumption and latency in data transmission, which is critical especially in a healthcare environment where data flow must be particularly responsive. Thus, we proposed and designed a Raspberry Pi-based edge computing system to computer-intensive care unit (ICU) data at the periphery of the network to offload the hospital cloud platform. ICU medical data were simulated from the PhysioNet MIMIC III database and transferred to the edge platform for computation and identification of emergency cases that were then sent to the cloud level. We further discuss the current issues and prospects of edge computing in hospitals.