Main Article Content
Abstract
Today, our world is frequently facing a challenging environment everywhere. The main problem is
energy crisis. New technologies like sensor networks have been incorporated in the management of
buildings for organizations and cities. In recent years, Sensor networks have led to an exponential
increase in the volume of data available, and monetary savings. For this purpose, new approaches and
techniques are required to investigate information in big data environments .For this problem, having
a relevant system to monitor the power usage is the only solution. This paper proposes an analytical
model using energy profiles, which gives power consumption of a consumer over a period of time, to
perform quantitative analysis using smart meters that automatically acquire context information. There
are devices which are capable of measuring customer’s energy consumption for example smart meter.
In this paper, there are two modules. The first one emphasis on receiving the data from the smart meter
and also send it to the data analyst. The second module is the predictive module which uses consumption
data and information of the consumer in order to understand the behavioral patterns of the consumption
of electricity. These trends can be used to predict energy consumption and also identify irregularities
and outliers. The customer gets acknowledged about abnormal usage.