During the last few years, several approaches have been proposed to improve early warning systems for managing geological risk due to landslides, where important infrastructures (such as railways, highways, pipelines, and aqueducts) are exposed elements. In this regard, an Artificial intelligence Camera Prototype (AiCP) for real-time monitoring has been integrated in a multisensor monitoring system devoted to rock fall detection. An abandoned limestone quarry was chosen at Acuto (central Italy) as test-site for verifying the reliability of the integratedmonitoring system. A portion of jointed rockmass, with dimensions suitable for optical monitoring, was instrumented by extensometers. One meter of railway track was used as a target for fallen blocks and a weather station was installed nearby. Main goals of the test were (i) evaluating the reliability of the AiCP and (ii) detecting rock blocks that reach the railway track by the AiCP. At this aim, several experiments were carried out by throwing rock blocks over the railway track. During these experiments, the AiCP detected the blocks and automatically transmitted an alarm signal.

Rock falls impacting railway tracks. Detection analysis through an artificial intelligence camera prototype / Fantini, Andrea; Fiorucci, Matteo; Martino, Salvatore. - In: WIRELESS COMMUNICATIONS AND MOBILE COMPUTING. - ISSN 1530-8669. - STAMPA. - 2017:(2017), pp. 1-11. [10.1155/2017/9386928]

Rock falls impacting railway tracks. Detection analysis through an artificial intelligence camera prototype

Fantini, Andrea;Fiorucci, Matteo
;
Martino, Salvatore
2017

Abstract

During the last few years, several approaches have been proposed to improve early warning systems for managing geological risk due to landslides, where important infrastructures (such as railways, highways, pipelines, and aqueducts) are exposed elements. In this regard, an Artificial intelligence Camera Prototype (AiCP) for real-time monitoring has been integrated in a multisensor monitoring system devoted to rock fall detection. An abandoned limestone quarry was chosen at Acuto (central Italy) as test-site for verifying the reliability of the integratedmonitoring system. A portion of jointed rockmass, with dimensions suitable for optical monitoring, was instrumented by extensometers. One meter of railway track was used as a target for fallen blocks and a weather station was installed nearby. Main goals of the test were (i) evaluating the reliability of the AiCP and (ii) detecting rock blocks that reach the railway track by the AiCP. At this aim, several experiments were carried out by throwing rock blocks over the railway track. During these experiments, the AiCP detected the blocks and automatically transmitted an alarm signal.
2017
landslide monitoring; rock-falls; optical device
01 Pubblicazione su rivista::01a Articolo in rivista
Rock falls impacting railway tracks. Detection analysis through an artificial intelligence camera prototype / Fantini, Andrea; Fiorucci, Matteo; Martino, Salvatore. - In: WIRELESS COMMUNICATIONS AND MOBILE COMPUTING. - ISSN 1530-8669. - STAMPA. - 2017:(2017), pp. 1-11. [10.1155/2017/9386928]
File allegati a questo prodotto
File Dimensione Formato  
Fantini_Rock_2017.pdf

accesso aperto

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Creative commons
Dimensione 10.07 MB
Formato Adobe PDF
10.07 MB Adobe PDF

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1084981
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 15
  • ???jsp.display-item.citation.isi??? 11
social impact