An Efficient Data reduction Technique in IoT Health Care System

Abstract

Internet of Things (IoT) is a system of interrelated devices or things that communicate among themselves
the device may be Electrical, Mechanical, Chemical or anything. IoT is used in almost all the field, one of
the important field is health care, in remote patient monitoring system patient health data are needed to be
monitored continuously, so it is unavoidable in such systems to generate unprecedented data, all the data
acquired are processed in cloud, consequently it overloads the cloud and hence latency, congestion and
memory requirement increases , In the Proposed system all the data are validated at the edge or fog node
itself rather than the cloud, and also only the data which are more important are uploaded to the cloud for
further broadcast here the non-critical data are redundant, hence a large number of data being transmitted
to the cloud platform is averted. The data filtering method is used at fog node near the IoT gateway is used
in the proposed work. Only Unsafe Health data is filtered out from the raw data used at Fog Layer, Fog
computing is an architecture that permits applications to processed on the edge device rather in IoT cloud
computing platform. Utilizing the concept of Fog computing here off load the cloud by restricting the raw
data to be uploaded in to the cloud and also increase the effectiveness of the system.