An Adaptive e-Health Solution System for Disaster Management

E-Health monitoring systems provide very good means for progressive monitoring and referential analysis based on historic data measurement & as well as general reference data of the individuals & patients, stored in the system. With the advent of Internet of Things (IOT) [1] and increased research and advances in sensor networks for intrusive and nonintrusive health monitoring systems, this will result in an explosion of information across the verticals of e-health to be processed and acted-upon and as IOT matures and with advent of smart environments (smart CARs, smart Homes, smart Hospitals, smart Cities, etc. ) this is only going to increase resulting into humongous data being made available to process and analyze imagine billions of people connected to the network constantly being monitored, their health inputs received & processed by the systems serviced by few hundred thousands of doctors and every critical alert monitored, tracked & advised upon. The world average of doctor to patient ratio being 1.6 per 1000 people [3] ( varies per country but this is the average calculated for across the globe), this would mean a lot of information & patients for doctors to act-on simultaneously during a major catastrophic event or disaster impacting multiple individuals, ultimately resulting in a very promising & a convenient solution having too many practical limitations either increased over-head due to continuous information would result in medical community becoming less sensitive to patients alerts over-the-time or patients becoming over-caring & overly-worried or patients losing faith in the e-Health solution & monitoring system where the technology is seen more of a burden and a cost over-head. In near future, the sensor network are going to play major role in monitoring of the individuals this will be influenced by rising health costs and healthcare spending which may result into multiple health insurance companies into exploring options like involving smart sensors (intrusive and nonintrusive) to monitor individuals health, habits and habitat. In this paper we attempt to explore the possible architecture that can be considered for adaptive & early processing of information during a major catastrophic event such natural calamities & disasters, terrorist attacks, etc. causing impact to multiple human beings. We should be able to successfully identify impacted individuals, direct the critical and fatally wounded/impacted individuals to relevant centers where they can be immediately treated and make this solution have practical approach, result in reduced over-head of information for medical practitioners and help increase the quality of human life.