Green revolution suggests that agriculture systems, such as farms turn into dynamic entities boosting animal production in an ecofriendly way. In this direction, we propose exploiting the acoustic modality for farm monitoring. Such information could be used in a stand-alone or complimentary mode to monitor the farm constantly and provide a great level of detail. To this end, we designed a scheme classifying the vocalizations produced by farm animals. We employed a feature set able to capture diverse characteristics of generalized sound events seen from different domain representations (time, frequency, and wavelet). These are modeled using state of the art generative and discriminative classification schemes. We performed extensive experiments on a publicly available dataset, where we report encouraging recognition rates.
On Acoustic Monitoring of Farm Environments / S. Ntalampiras (COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE). - In: Advances in Signal Processing and Intelligent Recognition Systems / [a cura di] S.M. Thampi, O. Marques, S. Krishnan, K.-C. Li, D. Ciuonzo, M.H. Kolekar. - [s.l] : Springer Singapore, 2019. - ISBN 9789811357572. - pp. 53-63 (( Intervento presentato al 4. convegno SIRS : International Symposium on Signal Processing and Intelligent Recognition Systems : 19 September 2018 through 22 September tenutosi a Bangalore (India) nel 2018.
|Titolo:||On Acoustic Monitoring of Farm Environments|
NTALAMPIRAS, STAVROS (Corresponding)
|Parole Chiave:||Acoustic farm monitoring; Intelligent farming Audio signal processing; Hidden Markov model; Echo state network Random forest; Support vector machine Multidomain acoustic parameters|
|Settore Scientifico Disciplinare:||Settore INF/01 - Informatica|
|Data di pubblicazione:||2019|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1007/978-981-13-5758-9_5|
|Tipologia:||Book Part (author)|
|Appare nelle tipologie:||03 - Contributo in volume|