This paper deals with a project for real-time monitoring of railway tracks to detect events, such as fast failures from natural risks, which may threaten the transit of trains. The paper describes a network of smart sensors for early warning of these endangering events. Three main types of fast-failure events involving railways were identified: sinkhole, rock and debris falls. A case study on a known test site and experimentation with various scenarios were carried out with a view to developing algorithms capable of spotting and localising them. Results demonstrate the good performance of the network in monitoring the investigated events.
Experimenting an embedded-sensor network for early warning of natural risks due to fast failures along railways / Fantini, Andrea; Massimo, Magrini; Martino, Salvatore; Davide, Moroni; Gabriele, Pieri; Prestininzi, Alberto; Ovidio, Salvetti. - 2015:(2015), pp. 85-91. (Intervento presentato al convegno 5th International Workshop on Image Mining. Theory and Applications, IMTA-5 2015 tenutosi a Berlin; Germany).
Experimenting an embedded-sensor network for early warning of natural risks due to fast failures along railways
Andrea Fantini;MARTINO, Salvatore;PRESTININZI, ALBERTO;
2015
Abstract
This paper deals with a project for real-time monitoring of railway tracks to detect events, such as fast failures from natural risks, which may threaten the transit of trains. The paper describes a network of smart sensors for early warning of these endangering events. Three main types of fast-failure events involving railways were identified: sinkhole, rock and debris falls. A case study on a known test site and experimentation with various scenarios were carried out with a view to developing algorithms capable of spotting and localising them. Results demonstrate the good performance of the network in monitoring the investigated events.File | Dimensione | Formato | |
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