AI APPLICATIONS IN THE BUILDING PROCESS
The study on the functioning of HVAC systems and hydraulic circuits in buildings has highlighted the energy limits of a static management of the parameters that regulate them. The main recurring problems regard inadequate maintenance, failures, losses and malfunctions. With the development of new digital methodologies on the management of data flows (BIM and IoT) it has been demonstrated how the dynamic analysis of the sys-tems functioning parameters can lead to wide margins of improvement in terms of ener-gy use and containment of energy costs. The application of machine learning and artifi-cial intelligence (AI) methodologies to monitoring data has led the construction industry to introduce practices such as predictive maintenance and fault detection and diagnostics. In this way it is possible to develop preventive maintenance interventions that prevent discomfort and emergency situations; at the same time, it is possible to evaluate potential improvements and correct malfunctions that cause an improper use of energy and high operating costs. After introducing the issues of digitalization and building sustainability, we will show a possible application of AI and Big Data in the energy field, using the methodology of recurrent neural networks that can be used inside a Dynamo environment.