Information and communication technologies (ICT) offer immense potential to improve the energetic performance of buildings. Additionally, common building control systems are typically based on simple decision-making tools, which possess the ability to obtain controllable parameters for indoor temperatures. Nevertheless, the accuracy of such common building control systems is improvable with the integration of advanced decision-making techniques embedded into software and energy management tools. This paper presents the design of a building energy management system (BEMS), which is currently under development, and that makes use of artificial intelligence for the automated decision-making process required for optimal comfort of occupants and utilization of renewables for achieving energy-efficiency in buildings. The research falls under the scope of the H2020 project BREASER which implements fuzzy logic with the aim of governing the energy resources of a school in Turkey, which has been renovated with a ventilated façade with integrated renewable energy sources (RES). The BRESAER BEMS includes prediction techniques that increase the accuracy of common BEMS tools, and subsequent energy savings, while ensuring the indoor thermal comfort of the building occupants. In particular, weather forecast and simulation strategies are integrated into the functionalities of the overall system. By collecting the aforementioned information, the BEMS makes decisions according to a well-established selection of key performance indicators (KPIs) with the objective of providing a quantitative comparable value to determine new actuation parameters.

Current climate change threats and increasing CO₂ emissions, especially from the building stock, represent a context where action is required. It is necessary to provide efficient manners to manage energy demand in buildings and contribute to a decarbonised future. By combining new technologies, such as artificial intelligence, Internet of things, blockchain, and the exploitation of big data towards solving real life problems, the way could be paved towards smart and energy-aware buildings. In this context, the aim of this paper is to present a critical review and an in-detail definition of the big data value chain for the built environment in Europe, covering multiple needs and perspectives: “policy”, “technology” and “business”, in order to explore the main challenges and opportunities in this area.