Metrological issues in the integration of heterogeneous lot devices for energy efficiency in cognitive buildings

Architecture, Engineering and Construction (AEC) industry is today strongly related to technologies for the gathering, storing and mining of big data. The use of data is paramount in today management and design is also interpreting this dictat as a new and crucial paradigm. A building is no longer a static body of material but a dynamic flow of data driving the new concept of the building as a service provider to users. The evolution of automated and smart building is cognitive, which means a learning building adaptable to users' needs and preferences and to changing conditions (i.e. weather, energy cost, occupancy profile, activities, etc.). The information is collected by sensors and referred to indoor conditions and settings, power consumption, user' flows and preferences to extend the user experience and to save energy. Such information should be machine readable and real-timed analyzed by artificial intelligence. Thus, the performance of the cognitive system relies on the quality and the reliability of the information collected by sensors. The information system should be made conscious of metrological issues through the use of proper metadata. This approach has been used to manage the sensors data in the case study of a building of University of Brescia.