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Abstract
An intelligent Body Area Routing (BAN) routing mechanism for remote patient monitoring has been proposed in this paper. In case of remote patient monitoring different level of care and attentions have to be provided to the patient depending upon their criticality level. So in this proposed model patients are being categorized as Extremely Critical, Most Critical, Critical, Moderate and Low Risk using the machine learning technique- K means clustering. At the same time most competent route has to be selected according to the patient level of criticality. The nodes taking part in the routing are also being categorized as Extremely Competent, Most Competent, Competent, Moderate and Least Competent considering Hop Count, Congestion Level, Energy Level and Priority using K means clustering as well. Then mapping from patient cluster to node cluster to route the data following that the extremely critical patient data would be routed through extremely competent nodes. The proposed model can be an effective approach for monitoring remote patient in an optimal way.
Published Version
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