# Who's a Good Boy? Reinforcing Canine Behavior in Real-Time using Machine Learning

Source: [Who's a Good Boy? Reinforcing Canine Behavior in Real-Time using Machine Learning](<https://www.sota2.com/research/paper/68fa690c1e209131cea1fbe4>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-28T13:56:46.063Z

Authors: Jason Stock, Tom Cavey

Published: 2021-01-07T05:38:09.000Z

## Abstract

In this paper we outline the development methodology for an automatic dog treat dispenser which combines machine learning and embedded hardware to identify and reward dog behaviors in real-time. Using machine learning techniques for training an image classification model we identify three behaviors of our canine companions: "sit", "stand", and "lie down" with up to 92% test accuracy and 39 frames per second. We evaluate a variety of neural network architectures, interpretability methods, model quantization and optimization techniques to develop a model specifically for an NVIDIA Jetson Nano. We detect the aforementioned behaviors in real-time and reinforce positive actions by making inference on the Jetson Nano and transmitting a signal to a servo motor to release rewards from a treat delivery apparatus.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2101.02380>)

[PDF](<https://arxiv.org/pdf/2101.02380.pdf>)