Sammanfattning

There is a need for reliable and efficient methods for monitoring the activity and social behaviour in cows, in order to optimise management in modern dairy farms. This research presents an embedded system that could track individual cows using Ultra-wideband technology. At the same time, social interactions between individuals around the feeding area were analysed with a computer vision module. Detections of the dairy cows’ negative and positive interactions were performed on foreground video stream using a Long-term Recurrent Convolution Networks model. The sensor fusion system was implemented and tested on seven dairy cows during 45 days in an experimental dairy farm. The system performance was evaluated at the feeding area. The real-time locating system based on Ultra-wideband technology reached an accuracy with mean error 0.39 m and standard deviation 0.62 m. The accuracy of detecting the affiliative and agonistic social interactions reached 93.2%. This study demonstrates a potential system for monitoring social interactions between dairy cows.

Nyckelord

ultra-wideband; computer vision; dairy cows; social interactions; machine learning

Publicerad i

Journal of Systems Architecture
2021, Volym: 116, artikelnummer: 102139

SLU författare

• Ren, Keni

  • Institutionen för husdjurens biovetenskaper, Sveriges lantbruksuniversitet
    
  • Umeå Universitet

• Bernes, Gun

  • Institutionen för norrländsk jordbruksvetenskap, Sveriges lantbruksuniversitet
    

• Hetta, Mårten

  • Institutionen för norrländsk jordbruksvetenskap, Sveriges lantbruksuniversitet
    

UKÄ forskningsämne

Jordbruksvetenskap
Övrig annan teknik


Publikationens identifierare

DOI: https://doi.org/10.1016/j.sysarc.2021.102139

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/111542