Adhesive Model for Collection and Auto Storage of Colossal Health Data for Epidemiological Studies

The advent of cloud based technology has raised the data availability to its users. Consider any kind of data from medical data to inconsequential data is available categorically. However the data access rate depends on the nature, prominence of data and technology used. Based on these days scenario, the medical data can either be stored manually or automatically through embedded sensors on private clouds. This scenario leads to scattering of medical data at different locations. In order to perform research on the collective medical data is a tedious work as that would require permissions from respective hospital authorities. In the proposed work a model has been developed to gather the medical data at a unified cloud by efficiently managing the massive data. The data on the local server of hospitals need to be converted into XML web services for fast and secure communication. The data once received on the cloud is handled by the map reduce implementation, making the parallel execution of data on clusters of machine. Basically data is collected from distinct private clouds to form a unified community cloud. This may provide a coherent analysis of human health perspective with respect to vivid climatic conditions in particular demographic area.