Research Precision livestock farming

Precision livestock farming consists in the application of information and communication technologies to continuously monitor each animal in a farm, in a fully automatic way. Retrieved information helps in management to fulfil the basic health and welfare requirements of livestock, to early detect problems, and to improve the efficiency of production systems. Many physical variables can be monitored using sensors like microphones, thermometer, accelerometers, inertial measurement units, among others. Data provided by the sensors need to be analyzed by ad-hoc algorithms to process data and retrieve the information to help in the management decisions.
The aim of this research line is to design, develop and implement algorithms based on signal processing and pattern recognition techniques for: i) animal foraging monitoring and ii) heat detection.

Team members

Leonardo Giovanini
Leonardo Rufiner
Diego Milone
Sebastián Vanrell
Leandro Bugnon
José Cheloti
Constanza Quaglia
Juan Carrique
Luciano Martinez Rau
Leandro Vignolo
Mariano Ferrero

Collaborators

Web demos

BUFAR: An online algorithm to extract detailed information of foraging behavior in grazing cattle.
RAFAR: A regularity-based algorithm designed for long-term analysis of foraging behavior in grazing cattle.
Chewbite web: Foraging activity recognizers BUFAR and RAFAR for grazing cattle.

Selected publications

A full end-to-end deep approach for detecting and classifying jaw movements from acoustic signals in grazing cattle    

M. Ferrero, L. D. Vignolo, S. R. Vanrell, L. Rau, J. O. Chelotti, J. Galli, L. Giovanini, H. L. Rufiner

Engineering Applications of Artificial Intelligence, Volume 121 – 2023

A robust computational approach for jaw movement detection and classification in grazing cattle using acoustic signals    

Rau, J. O. Chelotti, S. R. Vanrell, J. Galli, S.A Utsumi, A. M. Planisich, H. L. Rufiner, L. Giovanini

Computers and Electronics in Agriculture, Elsevier, Volume 192 – 2022

An online method for estimating grazing and rumination bouts using acoustic signals in grazing cattle    

J. O. Chelotti, S. R. Vanrell, L. Rau, J. Galli, A. M. Planisich, S.A Utsumi, D. H. Milone, L. Giovanini, H. L. Rufiner

Computers and Electronics in Agriculture, Volume 173 – 2020

Discriminative power of acoustic features for jaw movement classification in cattle and sheep    

J. Galli, D. H. Milone, C. Cangiano, C. E. Martínez, E. Laca, J. O. Chelotti, H. L. Rufiner

Bioacoustics, Volume 29, Number 5, page 602–616 – 2020

A pattern recognition approach for detecting and classifying jaw movements in grazing cattle.    

J. O. Chelotti, S. R. Vanrell, J. Galli, L. Giovanini, H. L. Rufiner

Computers and Electronics in Agriculture, Volume 145, page 83–91 – 2018

A regularity-based algorithm for identifying grazing and rumination bouts from acoustic signals in grazing cattle    

S. R. Vanrell, J. O. Chelotti, J. Galli, S.A Utsumi, L. Giovanini, H. L. Rufiner, D. H. Milone

Computers and Electronics in Agriculture, Volume 151, page 392–402 – 2018

Embedded system for real-time monitoring of foraging behavior of grazing cattle using acoustic signals    

Nestor N. Deniz, J. O. Chelotti, J. Galli, A. M. Planisich, M. Larripa, H. L. Rufiner, L. Giovanini

Computers and Electronics in Agriculture, Volume 138, page 167–174 – 2017

Automatic recognition of ingestive sounds of cattle based on hidden Markov models.    

D. H. Milone, J. Galli, C. Cangiano, H. L. Rufiner, E. Laca

Computers and Electronics in Agriculture, Volume 87, page 51–55 – sep 2012

Computational Method for Segmentation and Classification of Ingestive Sounds in Sheep    

D. H. Milone, H. L. Rufiner, J. Galli, E. Laca, C. Cangiano

Computers and Electronics in Agriculture, Volume 65, Number 2, page 228–237 – 2009