Automated evaluation of cattle behavior under stable fly infestations
Our remote sensing device is based upon the CraneTracker (Anthony et al. 2012) with capabilities for tracking and recording animal’s behavior with GPS and accelerometers. Currently, we are calibrating the device to translate sensor outputs into defensive behavior event counts. For calibration, we are video recording animals with the device, obtaining two types of data: video and sensors. Video and sensor data are aligned and behavioral events demarcated. Machine learning methods are being used to create algorithms to translate sensor outputs to event counts. Once calibration is complete, we will verify that the devices are recording event counts correctly by video recording animals with devices. This time, we will compare the device counts with manual counts derived from the videos. After validation, CattleTracker will be ready for the second objective, evaluate cattle behaviors in response to stable fly infestations. Stable fly adult population will be monitor with sticky traps. At the same time, twenty animals will be monitored with Cattletrackers. Cattle behavioral data will be analyzed relative to stable fly populations with mixed linear models. Spatial data derived from GPS will be analyzed for quantifying grouping behavior, and will be correlated with stable fly populations as well. Results will help us to understand and quantify the effects of stable flies on cattle.
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