Adapting distributed stream processing technologies for the automation of modern health care systems

Abstract

In the past decade, smart healthcare systems have been on an ascendant drift, especially with the evolution of hospitals and their increasing reliance on bioinformatics and software specializing in healthcare. Doctors have become reliant on technology more than ever, something that in the past would have been looked down upon, as technology has become imperative in reducing overall costs and improving the quality of patient care. With patient-doctor interactions becoming more necessary and more complicated than ever, systems must be developed while taking into account costs, patient comfort, and patient data, among other things. Of course, with the rise in the number of patients, there is also subsequently see an increase in the amount of patient data that needs to be processed, further emphasizing the need for new systems and developments that can handle such large quantities of big data. This goal of this paper is to propose a potential solution to this problem in the form of a system prototype that can read, analyze and predict a patient’s data in real time, providing doctors and other intended healthcare personnel with an immediate report of a patient’s current situation, allowing for a quicker response time, better treatment, and the first step towards a grand realized smart hospital system in the long-term. In doing so, this system will highlight new forms of treatment that can potentially revolutionize the area of smart healthcare systems in a unique way, contrast to other previous research in this field where there is a lack of said provisions.