Towards a service-oriented architecture for the energy efficiency of buildings: a systematic review
AuthorsCastillo Sequera, José Luis; Gómez Pulido, José Manuel; Mendoza Pittí, Luis; Calderón Gómez, Huriviades; Vargas Lombardo, Miguel
IdentifiersPermanent link (URI): http://hdl.handle.net/10017/46830
L. Mendoza-Pitti, H. Calderón-Gómez, M. Vargas-Lombardo, J. M. Gómez-Pulido and J. L. Castillo-Sequera. 2021, "Towards a service-oriented architecture for the energy efficiency of buildings: a systematic review", IEEE Access, vol. 9, pp. 26119-26137.
Big data applications
Management information systems
Service-oriented systems engineering
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Currently, smart buildings generate large amounts of data due to the many devices and equipment available. Hence, buildings implement building management systems (BMSs), which monitor, control, manage and analyze each of these components. However, current BMSs are incapable of managing a massive amount of data (big data) and therefore cannot extract knowledge or make intelligent decisions in quasi real time. In addition, there are serious limitations to integrating BMSs with other services since they generally use proprietary software. In this sense, service-oriented architecture (SOA) is an architectural style that allows one to build distributed systems and provide functionalities such as services to end users or other types of services. Therefore, an SOA has the great advantage of allowing the expansion of the functionalities of BMSs. In fact, there are several studies that address SOAs for building management. However, we have not found any description or systematic analysis in the literature that allows the development of a versatile and interoperable SOA focused on the energy efficiency of buildings and that can integrate massive data analysis features. For these reasons, this study seeks to fill this knowledge gap and, more specifically, to identify and analyze the various software requirements proposed in the literature and the characteristics of big data that allow for improving the energy efficiency of buildings. To this end, we performed an in-depth review of the literature according to the methodology proposed by Kitchenham. As a result of this review, we provide researchers with a specific vision of the requirements and characteristics to consider for software development aimed at the energy efficiency of unique or historic buildings.
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