It is well known that ancient buildings suffer a high vulnerability to hazards, which may induce unpredictable damages. For this purpose, a main objective to be pursued concerns with the development of techniques for monitoring historical buildings and immediately alerting in case of early vulnerability warnings. This paper proposes a noninvasive Neural Network-based (NN-based) approach for Monitoring heritage buildings providing alerts in risk events. More in detail, a neural approach is suggested with the aim of predicting early warnings of risk events by detecting time novelties in images of historical evidences.
On Damage Monitoring in Historical Buildings via Neural Networks / Carnimeo, Leonarda; Foti, Dora; Vacca, V.. - (2015), pp. 157-161. (Intervento presentato al convegno IEEE Workshop on Environmental, Energy and Structural Monitoring Systems, EESMS 2015 tenutosi a Trento, Italy nel July 9.10, 2015) [10.1109/EESMS.2015.7175870].
On Damage Monitoring in Historical Buildings via Neural Networks
CARNIMEO, Leonarda;FOTI, Dora;
2015-01-01
Abstract
It is well known that ancient buildings suffer a high vulnerability to hazards, which may induce unpredictable damages. For this purpose, a main objective to be pursued concerns with the development of techniques for monitoring historical buildings and immediately alerting in case of early vulnerability warnings. This paper proposes a noninvasive Neural Network-based (NN-based) approach for Monitoring heritage buildings providing alerts in risk events. More in detail, a neural approach is suggested with the aim of predicting early warnings of risk events by detecting time novelties in images of historical evidences.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
