Deployment and Evaluation of an Active RFID Tracking System for Precision Animal Management

Authors

Brian Barnes, University of Nebraska - LincolnFollow

First Advisor

Dr. Deepak R. Keshwani

Second Advisor

Dr. Tami M. Brown-Brandl

Date of this Version

12-2016

Citation

Barnes, B. Deployment and Evaluation of an Active RFID Tracking System for Precision Animal Management. MS Thesis, Department of Biological Systems Engineering, University of Nebraska-Lincoln, 2016.

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Agricultural and Biological Systems Engineering, Under the Supervision of Professors Deepak R. Keshwani and Tami M. Brown-Brandl. Lincoln, Nebraska: December, 2016

Copyright (c) 2016 Brian L. Barnes

Abstract

A better understanding of animal space utilization in current livestock facilities could lead to improved facility design and animal health. This study was conducted to determine whether an active RFID tag tracking system could accurately provide animal locomotion data on an individual animal basis. The system is composed of four sensors, located in the corners of a swine pen, and compact tags, which attach to the animals and transmit a signal. The sensors use the tag signals to determine 3-D positions in real-time. A data acquisition system was developed to capture raw data from the system software into a database for analysis. The first test was performed with 34 tags placed at a known location, followed by a second test with 34 tags arranged in a 1-m×1-m grid across the pen. Results from the first test were consistent with the manufacturer’s claim of 15 cm accuracy. Error was higher in the second test. The system was used to track pigs for two days. Visual analysis indicated 84.4% tracking accuracy. Finally, the system was used to track animals from different genetic lines and temperaments. Statistical analysis of this data indicated significant differences in movement data based on sex of the animal, lineage, and temperament. Further work revealed that the system is prone to generate large jumps in the data that need to be filtered if the desired use is for instantaneous measurements. Without data filtering, the system is best suited for monitoring hourly or daily average values for animal movement parameters.

Advisors: Deepak Keshwani and Tami Brown-Brandl