Efforts of electrical utilities to respond to climate change require the development of increasingly sophisticated, integrated electrical grids referred to as the “smart grids”. Much of the smart grid effort focuses on integration of renewable generation into the electricity grid and on increased monitoring and automation of electrical transmission functions. However, a key component of smart grid development is the introduction of the smart electrical meter for all residential electrical customers. Smart meter (SM) deployment is the corner stone of the smart grid. In addition to adding new functionality to support system reliability, SMs provide the technological means for utilities to institute new programs to allow their customers to better manage and reduce their electricity use and to support increased renewable generation to reduce greenhouse emissions from electricity use. As such, this paper presents our research towards the study of a smart home environment and how the data produced is used to profile energy usage in homes. The validity of the data is justified through analysis of the profiles generated while consumers use energy during off peak and peak periods. By learning, understanding and feeding patterns of home behaviour, it is possible to educate the consumer regarding their energy usage, helping them to reduce costs but also the emissions from their home.