WIDGETs: Wireless Interactive Devices for Gauging and Evaluating Temperament for Service and Working Dogs

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Byrne, Ceara Ann
Jackson, Melody Moore
Starner, Thad
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Both service and working dogs are significantly beneficial to society; however, a substantial number of dogs are released from time consuming and expensive training programs when their behavior is unsuitable for the role they are training to enter. Early predictions of which dogs will succeed in which programs would not only increase the availability of dogs, but also save time, training resources, and funding. This research explores whether aspects of canine temperament can be detected from interactions with sensors and develops machine learning models that use sensor data to predict the success of service and working dogs-in-training. In this dissertation, we show the potential of instrumented ball and tug toys for predicting, with 87.5% accuracy, the success (or failure) of dogs entering advanced training in the Canine Companions for Independence (CCI) Program. We also find that the toys can predict whether a working dog-in-training at Auburn University's Canine Performance Sciences center (CPS) is suitable for advanced detection training with 83% accuracy. Lastly, we provide an exploratory analysis of the relationship between independent interaction features and (1) a canine's suitability outcomes in service dog programs, (2) a canine's suitability outcomes in working dog programs, (3) a canine's reasons for being released from a working dog program, and (4) the differences between successful service and working dogs.
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