Service-Oriented Big Data Analytics for Improving Buildings Energy Management in Smart Cities

This paper proposes a service-oriented architecture to support big data analytics for buildings energy management in smart cities. This architecture allows for seamlessly integrating different technologies such as fog and cloud computing to support different types of analytics and decision-making operations. These operations are needed to effectively utilize available big data for optimizing energy consumption for residential, industrial, and commercial buildings in smart cities. The paper also recognizes the different kinds of decision making processes required by a smart city to effectively manage energy efficiency for its buildings. These decision-making processes can be implemented and deployed as services in the proposed architecture.