TUTORIAL - MAY 29, 2023
Structural Health Monitoring of historic buildings via Artificial Intelligence
Eugenio Vocaturo
CNR - Nanotec
DIMES - University of Calabria, Italy
ABSTRACT
Structural health monitoring (SHM) is a scientific discipline that concentrates on assessing and keeping track of a structure's integrity. Despite SHM systems are not a recent area of study, computational breakthroughs in sensing hardware and the computational capability of embedded devices drive the generation of trustworthy data for constructing robust models for classification and predictive tasks. Due to the effectiveness of emerging technologies real time and on-line inspection in SHM is gradually replacing conventional damage detection techniques. Artificial Intelligence (AI) algorithms are offering the required tools to boost SHM systems' capabilities and provide smart answers to identify damage in structures. Several interesting and effective AI models have been provided in the state of the art literature for various predictive applications, including crack detection, predicting the compressive strength of masonry or repair mortars, potential damage scenarios in heritage buildings, seismic vulnerability assessment, determining the mechanical properties of materials, and identifying superficial damages on the monument's surface caused by weathering effects, material loss, efflorescence, seepage, algae growth, moss an dust deposition. This talk will review the various AI techniques applied to assess the health of heritage buildings and highlights challenges and future research directions in applying AI techniques to heritage buildings, including explainability and cross-modality.
SPEAKER BIOGRAPHY
Eugenio Vocaturo received a Laurea Degree in Management Engineering, a Master Degree in Design and Development of Web and Mobile Applications and a PhD Degree in Information and Communication Technologies at the University of Calabria, Italy. He also received a Master Degree in Industrial Process Management and a Master Degree in Finance issued by SDA Bocconi.
He has decades of experience as company director, being head of editorial production of important IT publishing houses and co-founding partner of the start-up BigTech. He is currently researcher at CNR-Nanotec and contract professor of Informatics, Process Mining, Data Mining and Information Systems and DataBase at University of Calabria.
His current research interests include Machine Learning, Deep Learning, Optimization, Health Informatics, Process Mining, Cultural Heritage. He is member of Topical Advisory Panel and Editor Reviewer of several international journals and permanent member of the program committee of international conferences, being author of several papers in international journals, conferences and books.
He is a member of SIBIM (Italian Scientific Society of Biomedical Informatics) and of HL7 Italy (formed in 2003 as part of HL7 International), company responsible for the localization of health standards aiming at promoting the modernization of Italian health IT.