Management of energy configuration using data mining algorithm

Abstract

newline Today s world completely relies on corporate function. It may be a house flat structure or newlinethe business corporate function premises; it urges the need of smart technologies to be newlineinbuilt in the infrastructure. A typical corporate function premises need to handle newlineinformation on security alarm, energy consumption, health care, air conditioning, newlineventilation, lighting, heating, etc. In handing this huge volume of data, it is very difficult newlineto do a manual process, as it takes time to predict the nature of fault and take necessary newlineaction. And so data mining technologies have been used in this invention, where it can newlinepredict the behavior of a system and predict the outcome of the operation. And also, in newlineorder to handle the history of records and handle a number of parameters in premises, this newlinetechnology is efficient. By retrieving information from all the sensors, the energy newlineconsumption is predicted by regression based method. In this method, data retrieved is newlineconverted to the required format and the desired feature is selected. Then the model newlineparameters are optimized and the machine learning algorithm is trained with model to newlinemake predictions. The pattern is also recognized by K-means clustering method. Once the newlineprediction and the identification done, the fault can be diagnosed and necessary steps newlinecarried out to overcome the fault. newlineKeywords Energy Conservation, Data Mining, K-Means Clustering, R Programming