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Presentation
Infrared proximity measurement system development and validation for classifying sow posture
Agricultural and Biosystems Engineering Conference Proceedings and Presentations
  • Benjamin C. Smith, Iowa State University
  • Brett C. Ramirez, Iowa State University
  • Steven J. Hoff, Iowa State University
Document Type
Presentation
Conference
ASABE Annual International Meeting
Publication Version
Published Version
Publication Date
1-1-2019
DOI
10.13031/aim.201900327
Conference Title
ASABE Annual International Meeting
Conference Date
July 7–10, 2019
Geolocation
(42.3600825, -71.05888010000001)
Abstract

The rapidly progressing field of precision livestock farming is becoming increasingly dependent on the utilization of camera technology. Integration of camera technology involves substantial intellectual input and computational power to acquire, process, and interpret images in real-time. Further, cameras and the necessary computational power can be cost-prohibitive and subsequently, become a constraint for application in a commercial livestock and poultry production systems. The purpose of this study is to develop an infrared proximity sensor based system to serve as a substitute a camera system to perform real-time monitoring of sow posture in farrowing stalls for a potentially lower cost and computational power. Monitoring sow posture can provide producers an indicator of farrowing and aid in evaluating sow demeanor during lactation. During the development of this system the long range infrared (IR) proximity sensors were individually calibrated, a sow posture algorithm was developed, and the IR-Sow Posture Detection System (IR-SoPoDS) system was evaluated in a commercial setting to a Kinect V2® camera for a range of sow postures. Average accuracy of the sow posture algorithm on the training data was found to be 96%. The overall accuracy of the IR-SoPoDS system across the three sow frame sizes were:87% (small), 90% (medium), and 89% (large). This IR-SoPoDS system shows a strong promise for further development for sow posture and behavior detection in the farrowing stall environment.

Comments

This presentation is published as Smith, Benjamin C., Brett C. Ramirez, and Steven J. Hoff. "Infrared proximity measurement system development and validation for classifying sow posture." ASABE Annual International Meeting. Boston, MA. July 7-10, 2019. Paper No. 1900327. DOI: 10.13031/aim.201900327. Posted with permission.

Copyright Owner
American Society of Agricultural and Biological Engineers
Language
en
File Format
application/pdf
Citation Information
Benjamin C. Smith, Brett C. Ramirez and Steven J. Hoff. "Infrared proximity measurement system development and validation for classifying sow posture" Boston, MA(2019) p. 1900327
Available at: http://works.bepress.com/steven_hoff/169/