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ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Publications at this Location » Publication #402191
Research Project: Science and Technologies for the Sustainable Management of Western Rangeland Systems

Location: Range Management Research

Title: Calculation of daily distance walked by grazing cattle using real-time activity and position data collected by LORA-WAN sensors

Author
item NYAMURYEKUNG'E, S - New Mexico State University
item DUFF, G - New Mexico State University
item UTSUMI, S - New Mexico State University
item Estell, Richard - Rick
item MCINTOSH, MATTHEW - New Mexico State University
item FUNK, M - New Mexico State University
item COX, A - New Mexico State University
item CAO, H - New Mexico State University
item CHEN, H - New Mexico State University
item Spiegal, Sheri
item PEREA, A - New Mexico State University
item RAHMAN, S - New Mexico State University
item CIBILS, A - New Mexico State University

Submitted to: Symposium Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 12/15/2022
Publication Date: 5/21/2023
Citation: Nyamuryekung'E, S., Duff, G.C., Utsumi, S.A., Estell, R.E., McIntosh, M.M., Funk, M., Cox, A., Cao, H., Chen, H., Spiegal, S.A., Perea, A., Rahman, S., Cibils, A.F. 2023. Calculation of daily distance walked by grazing cattle using real-time activity and position data collected by LORA-WAN sensors. 2nd U.S. Precision Livestock Farming Conference. Proceedings.

Interpretive Summary:

Technical Abstract: LoRa-WAN sensors were used to compare methods for determining walking distances by grazing cattle in near real-time. The accuracy of relying on a global positioning system (GPS) alone or in combination with motion data derived from triaxial accelerometers was compared using stationary control trackers (Control) placed in fixed field locations (n=6) vs. trackers (Test) mounted on cows (n=6) grazing on pasture at the New Mexico State University’s Clayton Livestock Research Center. Trackers communicated motion data at 1-minute intervals and GPS positions at 15-minute intervals for seven days. Daily distance walked was determined using: 1) raw GPS data (RawDist), 2) data with erroneous GPS locations removed (CorrDist), or 3) data with erroneous GPS locations removed and with GPS data associated with the static state excluded (CorrActDist). Distances were analyzed via one-way ANOVA to compare Control vs. Test deployment effects. No difference (P=0.43) in walking distance was detected between Control vs. Test for RawDist. However, distances calculated for CorrDist differed (P<0.01) between the two tracker deployments. Due to the random error of GPS measurements, CorrDist for stationary devices differed (P=0.01) from zero. The walking distance calculated by CorrActDist differed (P<0.01) between Control vs. Test trackers, with distances for Control trackers not differing (P=0.44) from zero. The fusion of GPS and accelerometer data was a more suitable method for calculating walking distance by grazing cattle. This result may highlight the value of combining more than one source of independent sensor data in Precision Livestock Farming applications.