%0 Journal Article %1 pandey_behavioral_2021 %A Pandey, Santosh %A Kalwa, Upender %A Kong, Taejoon %A Guo, Baoqing %A Gauger, Phillip C. %A Peters, David J. %A Yoon, Kyoung-Jin %D 2021 %J Animals %K adoption behavioral ear farming health industry intelligence machine microfluidics monitoring myown phenotype pig precision producer sensor swine tag technology %N 9 %P 2665 %R 10.3390/ani11092665 %T Behavioral Monitoring Tool for Pig Farmers: Ear Tag Sensors, Machine Intelligence, and Technology Adoption Roadmap %U https://www.mdpi.com/2076-2615/11/9/2665 %V 11 %X Precision swine production can benefit from autonomous, noninvasive, and affordable devices that conduct frequent checks on the well-being status of pigs. Here, we present a remote monitoring tool for the objective measurement of some behavioral indicators that may help in assessing the health and welfare status—namely, posture, gait, vocalization, and external temperature. The multiparameter electronic sensor board is characterized by laboratory measurements and by animal tests. Relevant behavioral health indicators are discussed for implementing machine learning algorithms and decision support tools to detect animal lameness, lethargy, pain, injury, and distress. The roadmap for technology adoption is also discussed, along with challenges and the path forward. The presented technology can potentially lead to efficient management of farm animals, targeted focus on sick animals, medical cost savings, and less use of antibiotics.

@article{pandey_behavioral_2021, abstract = {Precision swine production can benefit from autonomous, noninvasive, and affordable devices that conduct frequent checks on the well-being status of pigs. Here, we present a remote monitoring tool for the objective measurement of some behavioral indicators that may help in assessing the health and welfare status—namely, posture, gait, vocalization, and external temperature. The multiparameter electronic sensor board is characterized by laboratory measurements and by animal tests. Relevant behavioral health indicators are discussed for implementing machine learning algorithms and decision support tools to detect animal lameness, lethargy, pain, injury, and distress. The roadmap for technology adoption is also discussed, along with challenges and the path forward. The presented technology can potentially lead to efficient management of farm animals, targeted focus on sick animals, medical cost savings, and less use of antibiotics.}, added-at = {2022-07-12T23:17:28.000+0200}, author = {Pandey, Santosh and Kalwa, Upender and Kong, Taejoon and Guo, Baoqing and Gauger, Phillip C. and Peters, David J. and Yoon, Kyoung-Jin}, biburl = {https://www.bibsonomy.org/bibtex/22517bcfbf816154043256084a4ac6f44/spandey50}, copyright = {http://creativecommons.org/licenses/by/3.0/}, doi = {10.3390/ani11092665}, interhash = {ed5ccb398fe36cf76f45d843d40571d4}, intrahash = {2517bcfbf816154043256084a4ac6f44}, issn = {2076-2615}, journal = {Animals}, keywords = {adoption behavioral ear farming health industry intelligence machine microfluidics monitoring myown phenotype pig precision producer sensor swine tag technology}, language = {en}, month = sep, number = 9, pages = 2665, shorttitle = {Behavioral {Monitoring} {Tool} for {Pig} {Farmers}}, timestamp = {2023-02-23T22:47:30.000+0100}, title = {Behavioral Monitoring Tool for Pig Farmers: Ear Tag Sensors, Machine Intelligence, and Technology Adoption Roadmap}, url = {https://www.mdpi.com/2076-2615/11/9/2665}, urldate = {2022-05-16}, volume = 11, year = 2021 }