Title
Real-time Medical Emergency Response System: Exploiting IoT and Big Data for Public Health.
Abstract
Healthy people are important for any nation's development. Use of the Internet of Things (IoT)-based body area networks (BANs) is increasing for continuous monitoring and medical healthcare in order to perform real-time actions in case of emergencies. However, in the case of monitoring the health of all citizens or people in a country, the millions of sensors attached to human bodies generate massive volume of heterogeneous data, called "Big Data." Processing Big Data and performing real-time actions in critical situations is a challenging task. Therefore, in order to address such issues, we propose a Real-time Medical Emergency Response System that involves IoT-based medical sensors deployed on the human body. Moreover, the proposed system consists of the data analysis building, called "Intelligent Building," depicted by the proposed layered architecture and implementation model, and it is responsible for analysis and decision-making. The data collected from millions of body-attached sensors is forwarded to Intelligent Building for processing and for performing necessary actions using various units such as collection, Hadoop Processing (HPU), and analysis and decision. The feasibility and efficiency of the proposed system are evaluated by implementing the system on Hadoop using an UBUNTU 14.04 LTS coreTMi5 machine. Various medical sensory datasets and real-time network traffic are considered for evaluating the efficiency of the system. The results show that the proposed system has the capability of efficiently processing WBAN sensory data from millions of users in order to perform real-time responses in case of emergencies.
Year
DOI
Venue
2016
10.1007/s10916-016-0647-6
Journal of Medical Systems
Keywords
Field
DocType
Big data,Hadoop ecosystem,Healthcare,Intelligent building,IoT
Health care,Public health,Data mining,Computer security,Internet of Things,Continuous monitoring,Building automation,Medical emergency,Medicine,Big data,Multitier architecture
Journal
Volume
Issue
ISSN
40
12
1573-689X
Citations 
PageRank 
References 
4
0.39
3
Authors
5
Name
Order
Citations
PageRank
muhammad mazhar ullah rathore130121.15
Awais Ahmad237945.85
Anand Paul352746.32
Jiafu Wan41866100.02
Daqiang Zhang522017.76