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.
|Titolo:||On Damage Monitoring in Historical Buildings via Neural Networks|
|Data di pubblicazione:||2015|
|Nome del convegno:||IEEE Workshop on Environmental, Energy and Structural Monitoring Systems, EESMS 2015|
|Digital Object Identifier (DOI):||10.1109/EESMS.2015.7175870|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|