Oestrus Detection in Dairy Cows using Automata Modelling and Diagnosis Techniques

Ragnar Ingi Jónsson; Fabio Caponetti; Mogens Blanke; Niels Kjølstad Poulsen

doi:10.3182/20090630-4-ES-2003.00228

Oestrus Detection in Dairy Cows using Automata Modelling and Diagnosis Techniques

Ragnar Ingi Jónsson
, Fabio Caponetti
, Mogens Blanke
, Niels Kjølstad Poulsen

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

This paper addresses detection of oestrus in dairy cows using automata-based modelling and diagnosis. Measuring lying/standing behaviour of the cows by a sensor attached to the cows hindleg, lying/standing behaviour is modelled as a stochastic automaton. The paper introduces a cow's lying-balance as a biologically inspired quantity describing how much the cow has been resting for a preceding period. A dynamic lying-balance model is identified from real data and the lying balance is used as input, together with lying/standing sensor measurements. Using different automata models for oestrus and non-oestrus conditions, with state transition probability densities identified from observations, diagnosis theory for stochastic automata is employed to obtain diagnoses of oestrus. The oestrus cases are detected using consistency based diagnosis on real data.

Original language	English
Title of host publication	Procedings of 7. IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes
Publication date	2009
Pages	1402-1407
ISBN (Print)	978-3-902661-46-3
DOIs	https://doi.org/10.3182/20090630-4-ES-2003.00228
Publication status	Published - 2009
Event	7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes - Barcelona, Spain Duration: 30 Jun 2009 → 3 Jul 2009 Conference number: 7 http://safeprocess09.upc.es/

Conference

Conference	7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes
Number	7
Country/Territory	Spain
City	Barcelona
Period	30/06/2009 → 03/07/2009
Internet address	http://safeprocess09.upc.es/

Keywords

Health monitoring
Diagnosis
Signal processing
Animal husbandry
Stochastic automata
Fault diagnosis and monitoring

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10.3182/20090630-4-ES-2003.00228

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@inproceedings{1e73d1abf5114390a424e55d9499883c,

title = "Oestrus Detection in Dairy Cows using Automata Modelling and Diagnosis Techniques",

abstract = "This paper addresses detection of oestrus in dairy cows using automata-based modelling and diagnosis. Measuring lying/standing behaviour of the cows by a sensor attached to the cows hindleg, lying/standing behaviour is modelled as a stochastic automaton. The paper introduces a cow's lying-balance as a biologically inspired quantity describing how much the cow has been resting for a preceding period. A dynamic lying-balance model is identified from real data and the lying balance is used as input, together with lying/standing sensor measurements. Using different automata models for oestrus and non-oestrus conditions, with state transition probability densities identified from observations, diagnosis theory for stochastic automata is employed to obtain diagnoses of oestrus. The oestrus cases are detected using consistency based diagnosis on real data.",

keywords = "Health monitoring, Diagnosis, Signal processing, Animal husbandry, Stochastic automata, Fault diagnosis and monitoring",

author = "J{\'o}nsson, \{Ragnar Ingi\} and Fabio Caponetti and Mogens Blanke and Poulsen, \{Niels Kj{\o}lstad\}",

year = "2009",

doi = "10.3182/20090630-4-ES-2003.00228",

language = "English",

isbn = "978-3-902661-46-3",

pages = "1402--1407",

booktitle = "Procedings of 7. IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes",

note = "7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2009 ; Conference date: 30-06-2009 Through 03-07-2009",

url = "http://safeprocess09.upc.es/",

}

Jónsson, RI, Caponetti, F, Blanke, M & Poulsen, NK 2009, Oestrus Detection in Dairy Cows using Automata Modelling and Diagnosis Techniques. in Procedings of 7. IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes. pp. 1402-1407, 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, Barcelona, Spain, 30/06/2009. https://doi.org/10.3182/20090630-4-ES-2003.00228

Oestrus Detection in Dairy Cows using Automata Modelling and Diagnosis Techniques. / Jónsson, Ragnar Ingi; Caponetti, Fabio; Blanke, Mogens et al.
Procedings of 7. IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes. 2009. p. 1402-1407.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Oestrus Detection in Dairy Cows using Automata Modelling and Diagnosis Techniques

AU - Jónsson, Ragnar Ingi

AU - Caponetti, Fabio

AU - Blanke, Mogens

AU - Poulsen, Niels Kjølstad

N1 - Conference code: 7

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N2 - This paper addresses detection of oestrus in dairy cows using automata-based modelling and diagnosis. Measuring lying/standing behaviour of the cows by a sensor attached to the cows hindleg, lying/standing behaviour is modelled as a stochastic automaton. The paper introduces a cow's lying-balance as a biologically inspired quantity describing how much the cow has been resting for a preceding period. A dynamic lying-balance model is identified from real data and the lying balance is used as input, together with lying/standing sensor measurements. Using different automata models for oestrus and non-oestrus conditions, with state transition probability densities identified from observations, diagnosis theory for stochastic automata is employed to obtain diagnoses of oestrus. The oestrus cases are detected using consistency based diagnosis on real data.

AB - This paper addresses detection of oestrus in dairy cows using automata-based modelling and diagnosis. Measuring lying/standing behaviour of the cows by a sensor attached to the cows hindleg, lying/standing behaviour is modelled as a stochastic automaton. The paper introduces a cow's lying-balance as a biologically inspired quantity describing how much the cow has been resting for a preceding period. A dynamic lying-balance model is identified from real data and the lying balance is used as input, together with lying/standing sensor measurements. Using different automata models for oestrus and non-oestrus conditions, with state transition probability densities identified from observations, diagnosis theory for stochastic automata is employed to obtain diagnoses of oestrus. The oestrus cases are detected using consistency based diagnosis on real data.

KW - Health monitoring

KW - Diagnosis

KW - Signal processing

KW - Animal husbandry

KW - Stochastic automata

KW - Fault diagnosis and monitoring

U2 - 10.3182/20090630-4-ES-2003.00228

DO - 10.3182/20090630-4-ES-2003.00228

M3 - Article in proceedings

SN - 978-3-902661-46-3

SP - 1402

EP - 1407

BT - Procedings of 7. IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes

T2 - 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes

Y2 - 30 June 2009 through 3 July 2009

ER -

Oestrus Detection in Dairy Cows using Automata Modelling and Diagnosis Techniques

Abstract

Conference

Keywords

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