Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloLocalizing tortoise nests by neural networks
Anno di pubblicazione2016
FormatoElettronico
Autore/iBarbuti R.; Chessa S.; Micheli A.; Pucci R.
Affiliazioni autoriDepartment of Computer Science, University of Pisa, Pisa, Italy and Museum of Natural History, University of Pisa, Calci, Italy; Department of Computer Science, University of Pisa, Pisa, Italy and CNR-ISTI, Pisa, Italy; Department of Computer Science, University of Pisa, Pisa, Italy; Department of Computer Science, University of Pisa, Pisa, Italy
Autori CNR e affiliazioni
  • STEFANO CHESSA
Lingua/e
  • inglese
AbstractThe goal of this research is to recognize the nest digging activity of tortoises using a device mounted atop the tortoise carapace. The device classifies tortoise movements in order to discriminate between nest digging, and non-digging activity (specifically walking and eating). Accelerometer data was collected from devices attached to the carapace of a number of tortoises during their two-month nesting period. Our system uses an accelerometer and an activity recognition system (ARS) which is modularly structured using an artificial neural network and an output filter. For the purpose of experiment and comparison, and with the aim of minimizing the computational cost, the artificial neural network has been modelled according to three different architectures based on the input delay neural network (IDNN). We show that the ARS can achieve very high accuracy on segments of data sequences, with an extremely small neural network that can be embedded in programmable low power devices. Given that digging is typically a long activity (up to two hours), the application of ARS on data segments can be repeated over time to set up a reliable and efficient system, called Tortoise@ for digging activity recognition.
Lingua abstractinglese
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RivistaPloS one
Attiva dal 2006
Editore: Public Library of Science - San Francisco, CA
Paese di pubblicazione: Stati Uniti d'America
Lingua: inglese
ISSN: 1932-6203
Titolo chiave: PloS one
Titolo proprio: PloS one
Titolo abbreviato: PLoS ONE
Titoli alternativi:
  • Public Library of Science one
  • PLoS 1
Numero volume della rivista11
Fascicolo della rivista3
DOI10.1371/journal.pone.0151168
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • Scopus (Codice:2-s2.0-85009164587)
  • ISI Web of Science (WOS) (Codice:000372580300050)
Parole chiaveAccelerometry, Animals, Equipment Design, Female, Humans, Movement, Nesting Behavior, Neural Networks (Computer), Turtles
Link (URL, URI)https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0151168#abstract0
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Strutture CNR
  • ISTI — Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"
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Localizing tortoise nests by neural networks
Descrizione: Published version - OA sito editore
Tipo documento: application/pdf