Pilot 1 – “Hospital Real” in Granada

This pilot will demonstrate the capabilities of BUILDCHAIN acting as a self-adaptive expert system for proactive maintenance of cultural heritage buildings such as the “Hospital Real”, a 16^th century hospital serving today as UGR’s Headquarters. To this end, first, the most critical deterioration processes will be identified and modelled using data from existing monitoring (accelerometers and digital photogrammetry) and new monitoring data form sensors that will monitor the physical variables responsible to degradation of stone, such as moisture, pollution, etc. Degradation processes in structural and non-structural parts such as surface recession, corrosion, etc. due to climate loads and extreme events will be considered. Then, the deterioration data will be used to create a hybrid AI model to produce updated degradation predictions according to the data. Finally, the resulting predictive deterioration model(s) will be integrated within a system representation model to simulate the impact of a particular inspection and/or maintenance action into the foreseen deterioration process, which encompasses a significant research challenge due to the heterogeneity, interdependence and non-linearity of the maintenance operations in reality. Novel methodological frameworks such as High Level Petri nets (HLPNs) will be investigated and enhanced to efficiently incorporate monitoring data, expert knowledge, and maintenance non-linearities creating a self-adaptive expert system for proactive maintenance and self-attentive sensing system management