TY - GEN
T1 - An Embedded System Device to Monitor Farrowing
AU - Silapachote, Piyanuch
AU - Srisuphab, Ananta
AU - Banchongthanakit, Warot
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/11/20
Y1 - 2018/11/20
N2 - Crucial for successful farrowing in swine production is the monitoring of health and welfare of pigs from insemination to farrowing and lactation. Although most are naturally farrowed, a significant number of piglets are lost due to fetal hypoxia. Common causes are ruptured umbilical cords, getting stuck in the birth canal, and exhaustion of sow. Prompt assistance offered by farmers can save lives of many piglets. Time is critical. Minutes of delay could mean another loss. Around-the-clock monitoring, at the same time, is not only labor-intensive but also a financial burden for farm management. One of the keys toward better assessment of the right timing for farmworkers to attend to a farrow with minimal wait-around time - first and foremost - is to collect and analyze the detailed timing of the farrowing process. Bringing digital technology of embedded systems to farming, we developed a monitoring device capable of continuously recording a video of a sow. Farrowing videos were collected for seven weeks. Graphical visualization and statistical analysis of the data were evaluated. Employing computer vision and machine intelligence, we proposed a methodology for extracting features and training a classifier to automatically detect the firstborn piglet. Preliminary image processing results are presented.
AB - Crucial for successful farrowing in swine production is the monitoring of health and welfare of pigs from insemination to farrowing and lactation. Although most are naturally farrowed, a significant number of piglets are lost due to fetal hypoxia. Common causes are ruptured umbilical cords, getting stuck in the birth canal, and exhaustion of sow. Prompt assistance offered by farmers can save lives of many piglets. Time is critical. Minutes of delay could mean another loss. Around-the-clock monitoring, at the same time, is not only labor-intensive but also a financial burden for farm management. One of the keys toward better assessment of the right timing for farmworkers to attend to a farrow with minimal wait-around time - first and foremost - is to collect and analyze the detailed timing of the farrowing process. Bringing digital technology of embedded systems to farming, we developed a monitoring device capable of continuously recording a video of a sow. Farrowing videos were collected for seven weeks. Graphical visualization and statistical analysis of the data were evaluated. Employing computer vision and machine intelligence, we proposed a methodology for extracting features and training a classifier to automatically detect the firstborn piglet. Preliminary image processing results are presented.
UR - https://www.scopus.com/pages/publications/85059959661
U2 - 10.1109/ICAICTA.2018.8541287
DO - 10.1109/ICAICTA.2018.8541287
M3 - Conference contribution
AN - SCOPUS:85059959661
T3 - ICAICTA 2018 - 5th International Conference on Advanced Informatics: Concepts Theory and Applications
SP - 208
EP - 213
BT - ICAICTA 2018 - 5th International Conference on Advanced Informatics
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Advanced Informatics: Concepts Theory and Applications, ICAICTA 2018
Y2 - 14 August 2018 through 17 August 2018
ER -