ACTIVITIY PREDICTION FOR DIFFERENTLY-ABLED PEOPLE USING DBSCAN AND GAUSSIAN DISTRIBUTION

The main objective of this paper is to train systems such that the systems itself will guide the differently abled people to perform their activities(tea, coffee, lunch & etc…). This paper provides a way in which system will remind the person to perform the activity which is adaptive to the behavior changes by combining classification and clustering techniques. By using DBSCAN algorithm the data is clustered. DBSCAN is a density based spatial clustering of applications with noise in which it finds a number of clusters starting from the estimated density distribution of corresponding nodes. After grouping the data, the Gaussian distribution algorithm is used to find the routine performed by the differently-abled people at a maximum extent. Gaussian distribution is a very commonly occurring continuous probability distribution ?a function that tells the probability that any real observation will fall between any two real limits or real numbers as the curve approaches zero on either side.