Knowledge based smart health care system: A survey

Life is the most precious gift to man and safeguarding this gift is of utmost importance.With increasing number of diseases and fast paced lives, people have less time to look after themselves and their family members or to even visit the doctor for regular check-ups.Our E-Health patient monitoring system can remotely monitor the health of the patients and intimate the doctor of critical conditions without human intervention. Some of the existing E-Health systems include telemedicine network for Francophone African countries (RAFT) and LOBIN. RAFT is implemented in java and uses asymmetric public – private key encryption, however it is expensive, does not support mobility and is not a context aware system. LOBIN is a hardware/software platform to locate and monitor a set of physiological parameters and context parameters of several patients within hospital facilities. Although it is a context aware system it cannot handle high and concurrent data traffic load. To overcome the above flaws, our proposed system puts forward an idea of patient monitoring using various knowledge based techniques like K-means clustering, Gaussian kernel function, ANN and Fuzzy inference engine. In our project we intend to do remote patient health monitoring in which we will be using three-four machines which will send various sensed health parameters to the centralised server that will make clusters of the sensed health parameters based on criticality of the health condition. Then depending upon clusters formed and on comparison with the threshold values appropriate reports will be generated and send to the doctors and caretakers.