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Creating influential nodes in a smart building social network

Smart buildings are an important development in energy efficient technology. Through the use of smart meters, integrated electric vehicles, and other technologies, the energy efficiency of a home or office can be improved significantly. The use of user incentives and influences are key to the successful operation of a smart building. Many of the relevant technologies are tools that require effort on the part of the occupant to reach their full potential. In this paper, we study the effects of influencing the social network of a smart apartment building's occupants in order to raise a building's energy efficiency to a socially desirable state. We study a novel inversion of the concept of influential nodes; we influence the network so as to make the best users highly influential within the network. We find that this method is able to produce reasonably good results in our simulations. Our results indicate that such a setup does increase the efficiency and help to produce a smoother load curve and a closer-to-optimal global energy usage state. Additionally, the results show that societal values can greatly impact the final result, and that the number of best users chosen has a significant effect on the scalability of the algorithm.