Real time sensor grid based secured health care monitoring
Goldie Gabrani, Sunil Gupta · 2017 Computing Conference · 2017
Every healthcare provider today uses the latest technologies in order to improve the quality of its patient care. Use of Wireless sensor node is one such popular technology as it helps to constantly monitor the patient's health by measuring his biological parameters. For example the biological parameters such as blood pressure, body temperature, heart rate etc. tell the status of the health condition of a patient. This paper presents a monitoring system that has the capability to monitor and gather biological parameters from multiple patients residing in multiple departments of a multispecialty hospital. The data is collected continuously at regular intervals and it results into a generation of enormous amount of data. This data should be effectively stored and processed by the physicians to manage the health of the patients. But the sensor nodes have serious limitation on both these fronts: storing large amounts of data as well as computational resources required for analyzing this data. Hence this led us to use grid infrastructure that provides high data storage as well as high computing power. In this paper, a patient health monitoring system is proposed that utilizes the merits of both Wireless sensor nodes and Grid infrastructure. The grid has multiple heterogeneous resources and it allocates its resources in such a manner so that data of maximum number of patients is catered to in a given period of time so as to reduce the patient's time to get medical attention. This system is capable to detect the abnormal conditions and issue an alarm to the patient's family/physician via SMS/E-mail. The proposed system gives higher priority to the critical and also to the VIP patients. Moreover, as the patient's data is highly confidential, the system allows only authenticated users to have an access to the data. The main advantage of this system in comparison to the previous systems is to maximize the number of patients whose health records can be analyzed in parallel on different resources, prioritized care to socially important, critical and emergency patients, secured access to patient health records and privacy of data.