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Automatic solution for detection, identification and biomedical monitoring of a cow using remote sensing for optimised treatment of cattle
Year:
2014
Authors :
Beiderman, Yevgeny
;
.
Halachmi, Ilan
;
.
Volume :
45
Co-Authors:

Mark Kunin,Eli Kolberg, Binyamin Abramov, Rafael Amsalem, Zeev Zalevsky  -  Faculty of Engineering, Bar-Ilan University, Ramat-Gan, Israel.

 
Facilitators :
From page:
0
To page:
0
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Total pages:
1
)
Abstract:

In this paper we show how a novel photonic remote sensing system assembled on a robotic platform can extract vital biomedical parameters from cattle including their heart beating, breathing and chewing activity. The sensor is based upon a camera and a laser using selfinterference phenomena. The whole system intends to provide an automatic solution for detection, identification and biomedical monitoring of a cow. The detection algorithm is based upon image processing involving probability map construction. The identification algorithms involve well known image pattern recognition techniques. The sensor is used on top of an automated robotic platform in order to support animal decision making. Field tests and computer simulated results are presented.

Note:
Related Files :
cattle
Cattle - dairy
cow
Detection
monitoring
Remote-sensing
Robotics
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More details
DOI :
https://doi.org/10.4081/jae.2014.418
Article number:
0
Affiliations:
Database:
Google Scholar
Publication Type:
article
;
.
Language:
English
Editors' remarks:
ID:
43191
Last updated date:
02/03/2022 17:27
Creation date:
12/08/2019 14:53
Scientific Publication
Automatic solution for detection, identification and biomedical monitoring of a cow using remote sensing for optimised treatment of cattle
45

Mark Kunin,Eli Kolberg, Binyamin Abramov, Rafael Amsalem, Zeev Zalevsky  -  Faculty of Engineering, Bar-Ilan University, Ramat-Gan, Israel.

 
Automatic solution for detection, identification and biomedical monitoring of a cow using remote sensing for optimised treatment of cattle

In this paper we show how a novel photonic remote sensing system assembled on a robotic platform can extract vital biomedical parameters from cattle including their heart beating, breathing and chewing activity. The sensor is based upon a camera and a laser using selfinterference phenomena. The whole system intends to provide an automatic solution for detection, identification and biomedical monitoring of a cow. The detection algorithm is based upon image processing involving probability map construction. The identification algorithms involve well known image pattern recognition techniques. The sensor is used on top of an automated robotic platform in order to support animal decision making. Field tests and computer simulated results are presented.

Scientific Publication
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