Real-Time Monitoring of Grazing Cattle Using LORA-WAN Sensors to Improve Precision in Detecting Animal Welfare Implications via Daily Distance Walked Metrics
Shelemia Nyamuryekung’e,
Glenn Duff,
Santiago Utsumi,
Richard Estell,
Matthew M. McIntosh,
Micah Funk,
Andrew Cox,
Huiping Cao,
Sheri Spiegal,
Andres Perea,
Andres F. Cibils
Affiliations
Shelemia Nyamuryekung’e
Division of Food Production and Society, Norwegian Institute of Bioeconomy Research (NIBIO), PB 115, N-1431 Ås, Norway
Glenn Duff
Department of Animal and Range Sciences, New Mexico State University, Las Cruces, NM 88003, USA
Santiago Utsumi
Department of Animal and Range Sciences, New Mexico State University, Las Cruces, NM 88003, USA
Richard Estell
United States Department of Agriculture-Agriculture Research Service, Jornada Experimental Range, Las Cruces, NM 88003, USA
Matthew M. McIntosh
United States Department of Agriculture-Agriculture Research Service, Jornada Experimental Range, Las Cruces, NM 88003, USA
Micah Funk
Department of Animal and Range Sciences, New Mexico State University, Las Cruces, NM 88003, USA
Andrew Cox
Department of Animal and Range Sciences, New Mexico State University, Las Cruces, NM 88003, USA
Huiping Cao
Department of Computer Science, New Mexico State University, Las Cruces, NM 88003, USA
Sheri Spiegal
United States Department of Agriculture-Agriculture Research Service, Jornada Experimental Range, Las Cruces, NM 88003, USA
Andres Perea
Department of Animal and Range Sciences, New Mexico State University, Las Cruces, NM 88003, USA
Andres F. Cibils
United States Department of Agriculture Southern Plains Climate Hub, United States Department of Aagricultulre-Agriculture Rearch Services, Oklahoma and Central Plains Agricultural Research Center, El Reno, OK 73036, USA
Animal welfare monitoring relies on sensor accuracy for detecting changes in animal well-being. We compared the distance calculations based on global positioning system (GPS) data alone or combined with motion data from triaxial accelerometers. The assessment involved static trackers placed outdoors or indoors vs. trackers mounted on cows grazing on pasture. Trackers communicated motion data at 1 min intervals and GPS positions at 15 min intervals for seven days. Daily distance walked was determined using the following: (1) raw GPS data (RawDist), (2) data with erroneous GPS locations removed (CorrectedDist), or (3) data with erroneous GPS locations removed, combined with the exclusion of GPS data associated with no motion reading (CorrectedDist_Act). Distances were analyzed via one-way ANOVA to compare the effects of tracker placement (Indoor, Outdoor, or Animal). No difference was detected between the tracker placement for RawDist. The computation of CorrectedDist differed between the tracker placements. However, due to the random error of GPS measurements, CorrectedDist for Indoor static trackers differed from zero. The walking distance calculated by CorrectedDist_Act differed between the tracker placements, with distances for static trackers not differing from zero. The fusion of GPS and accelerometer data better detected animal welfare implications related to immobility in grazing cattle.
