Abstract
New study results on artificial intelligence have been published. According to news reporting originating from Ancona, Italy, by NewsRx correspondents, research stated, “In a seismic context, it is fundamental to deploy distributed sensor networks for Structural Health Monitoring (SHM).” Funders for this research include Recity. Our news editors obtained a quote from the research from Marche Polytechnic University: “Indeed, regularly gathering data from a structure/infrastructure gives insight on the structural health status, and Artificial Intelligence (AI) technologies can help in exploiting this information to generate early warnings useful for decision-making purposes. With a perspective of developing a remote monitoring platform for the built environment in a seismic context, the authors tested self-sensing concrete beams in loading tests, focusing on the measured electrical impedance. The formed cracks were objectively assessed through a vision-based system. Also, a comparative analysis of AI-based and statistical prediction methods, including Prophet, ARIMA, and SARIMAX, was conducted for predicting electrical impedance. Results show that the real part of electrical impedance is highly correlated with the applied load (Pearson’s correlation coefficient >0.9); hence, the piezoresistive ability of the manufactured specimens has been confirmed.”
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