Association Rules for Electrical Activity Detection in Smart Home to Reduce Electricity Wastage

Abstract

Currently the use of big-data is on a large scale and is increasing day-by-day. So to handle the massive data is very important. In our research we have used Association Rules to generate rules from the best patterns which are generated by the Feature Selection. We have used Apriori Algorithm to generated Association Rules for finding best patterns to reduce electricity wastage. As it is a big-data means lots of data in high volume and also we have to provide high dimensionality as we are using feature selection so we have to be very carefully manipulate this all operations. In our research feature selection selects the features which are more dominating and it skips which are less dominating to get the better throughput using Best-Fit Linear Regression. As a result we can let the manufacturers know about the appliances usage at which time they are in use and in parallel or at at which time they are not in used. Our work is to find out the better patterns for electricity consumption in smart homes.