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.

<p>B<span>UILDSPACE aims to couple terrestrial data from buildings (collected by IoT platforms, BIM solutions and other) with aerial imaging from drones equipped with thermal cameras and location annotated data from satellite services (i.e., EGNSS and Copernicus) to deliver innovative services for the building and urban stakeholders and support informed decision making towards energy-efficient buildings and climate resilient cities. The platform will allow integration of these heterogeneous data and will offer services at building scale, enabling the generation of high fidelity multi-modal digital twins and at city scale providing decision support services for energy demand prediction, urban heat and urban flood analysis. The services will enable the identification of environmental hotspots that increase pressure to local city ecosystems and raise probability for natural disasters (such as flooding) and will issue alerts and recommendations for action to local governments and regions (such as the support of policies for building renovation in specific vulnerable areas). </span><span>BUILDSPACE services will be validated and assessed in four European cities with different climate profiles. The digital twin services at building level will be tested during the construction of a new building in Poland, and the city services validating the link to digital twin of buildings will be tested in 3 cities (Piraeus, Riga, Ljubljana) across EU. BUILDSPACE will create a set of replication guidelines and blueprints for the adoption of the proposed applications in building resilient cities at large.</span> </p>

The EU strategies to reduce carbon dioxide emissions highlight the importance of renovating the existing building stock. It is one of the most contributing sectors to these undesired emissions to the atmosphere. The business-as-usual practices for designing energy-efficient retrofitting projects are still too time consuming and imprecise, and their supporting tools are not interconnected, provoking a lack of trust within the sector, particularly from investors. There is a need to improve these practices by reducing the errors and the time required to evaluate retrofitting alternatives to select the most appropriate according to the stakeholders’ priorities. To address this gap, the Optimised Energy Efficient Design Platform for Refurbishment at District Level (OptEEmAL) solution enables the automatic generation of scenarios of energy conservation measures and their simulation and optimisation, based on data provided by the users. This solution automatically launches and connects the processes that the different stakeholders usually carry out in a long period of time. This allows testing a more varied set of solutions and engages stakeholders along the process supported by the integrated project delivery approach. As a result, time is reduced, as well as errors and, therefore, costs, which will lead to increase in efficiency and confidence among stakeholders.

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Climate change will have a strong impact on urban settings, which will also represent one of the major challenges (world’s urban population is expected to double by 2050, EU buildings consume 40% final energy and generate 36% CO2 emissions). A plethora of initiatives address this challenge by stressing the underlying necessity of thinking globally but acting locally. This entails the inclusion of a varied set of decision-makers acting at different scales and needing robust, comprehensive and comparable information that can support them in their energy planning process. To this end, this paper presents the GIS4ENER tool to support energy planners at different scales by proposing a bottom-up approach towards the calculation of energy demand and consumption at local scale that can be aggregated to support other decision-making scales. It is based on three main pillars: the exploitation of publicly available data (such as Open Street Maps, Building Stock Observatory or TABULA), the implementation of standardised methods to calculate energy (in particular the ISO52000 family) and the use of Geographic Information Systems to represent and facilitate the understanding of results, and their aggregation. The paper presents the context, main differences with other approaches and results of the tool in Osimo (IT).