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An integrated sensor network for monitoring pastured cattle health and location.

B. R. dos Reis

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06-23-2020

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Abstract:

T77
An integrated sensor network for monitoring pastured cattle health and location.
B. R. dos Reis*, R. R. White. Virginia Tech Blacksburg, VA.

Although systems exist for monitoring health and location of cattle housed in confinement operations, analogous monitoring systems for pastured cattle are not commonly available. Our objective was to demonstrate an integrated sensor network for monitoring pastured cattle health and location. The integrated sensor network (Mahindra & Mahindra; Mumbai, India) links data obtained from a subcutaneous temperature sensor (Livestock Labs Inc., Pittsburgh, PA) with GPS data obtained from a solar-powered collar sensor (Sodaq; Hilversum, the Netherlands) via a satellite gateway (Hiber Global, Amsterdam, the Netherlands) to a cloud-based data storage platform. The subcutaneous temperature sensor is implanted surgically through a 5 mm vertical incision in the neck. After initiation, the sensor logs temperature and activity hourly and transmits data using a Bluetooth communication protocol to a solar-powered base station. If animals are out of range of the base station, the logger has capacity to store data for 2 weeks, or until animals come back into range of the station. Battery life on the sensors is expected to last 2 years. The base station is designed to use cellular communication but was retrofitted with LoRa communication for the purposes of this demonstration. The GPS collar sensors are commercially available and use solar power and LoRa-based communication. Data from the GPS collars and the implantable temperature sensors was transmitted via LoRa communication to the satellite gateway. The sensor network was deployed on 10 grazing cattle over a 6-mo period to test data reliability. The subcutaneous sensors were able to detect within-animal differences in body temperature associated with diurnal cycling, but improvements to base station design are needed to optimize data reliability (recover rates ~50%). Collars were able to reliably report on animal location for the duration of the trial. Further refinement of the data processing is needed to maximize the utility of this sensor network for monitoring cattle health and location.

Keywords: cattle health, GPS, precision technologies.

Biography: Barbara Roqueto dos Reis is a PhD student�at Department of Animal & Poultry Sciences, Virginia Polytechnic Institute and State University. Barbara does research in ruminant nutrition and production.