An Approach to Integrate Wireless Sensor Networks with Cloud Computing Technology in Medical Context

الموضوعات : Majlesi Journal of Telecommunication Devices

Mohsen Norouzi ¹ (Faculty of Computer, Imam Hossein University, Tehran, Iran)
Ali Arshaghi ² (Faculty of Computer, Imam Hossein University, Tehran, Iran.)
Mohsen Ashourian ³ (Department of Electrical Engineering, Majlesi Branch, Islamic Azad University, Isfahan, Iran)

تاريخ الإرسال : 12 الثلاثاء , جمادى الأولى, 1444 تاريخ التأكيد : 28 الأحد , رجب, 1444 تاريخ الإصدار : 12 الخميس , ذو القعدة, 1444

الکلمات المفتاحية: Wireless Sensor Networks, the military health care system, cloud computing,

ملخص المقالة :

Recently, with the advent of cloud computing technology and the growth of cell phone applications, the technology has been introduced as a solution for use in smart phones. Combining cloud computing and smart phones copes with such obstacles as performance including battery life time, storage capacity and bandwidth, environment as scalability and availability, and security like reliability and accessibility. Today, patient information collection processes require extensive analysis on the collected input data. In addition, this process has lots of errors, it is affordable and increases the time needed for access to the data. These conditions constrain effective monitoring and diagnostic capabilities by the hospitals. Unlike previous methods, data can be collected by devices such as Bluetooth and stored on a server in hospital. In this paper, a comprehensive research involves collecting data from patients and sending this data to a smart phone. Therefore, two algorithms were proposed for a list of physicians with the highest priority. Priority parameters are received by the hospitals server. These priorities include the initial weight, the weight indicating how busy the physician is, and the relationship between physician and patient's disease. Android application was simulated by Eclipse software. The application includes a diagnostic system that receives patient data and compared it with the reference table. If the patient's condition is not good, a short message is sent using two mentioned algorithms.

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