Summer Creative Practice Course

/

Personal Project

BetterPaw

BetterPaw

BetterPaw

Project Context

This project is a personal exploration inspired by my dog Better, whose hind leg weakness made it difficult for her to walk, requiring her to relieve herself indoors. I finished the project during the summer creative practice course.

Output

Data Collection Units, Database, Data Learning Model, Data visualization, Mechanism Prototypes, User Testing, Product Modeling and Rendering.

May.2024 -Sep.2024

Beijing.China

What Problem Am I Solving?

Training Dogs to Relieve Themselves in Specific Spots Indoors

Helping dogs learn to urinate in specific spots at home independently through the designed mechanism, reinforcing behavior without direct owner supervision.

Why Am I Doing This?

To assist the dog and owner with managing indoor toileting.

I have a 14-year-old dog named Better. As she has aged, her legs have weakened, making it difficult for her to walk. I wanted to design a device to assist her with indoor toileting and provide convenience for my family.

Training dogs to use specific spots indoors is essential for both the dog and the owner. The goal is to create a low-cost, easy-to-learn system that dogs can use independently when the owner is unavailable.

User Research —— 57 Questionnaire Responses from Dog-owning Households

01 Basic Information about Dogs

46.43% are medium-sized dogs. 42.86% are aged 1–3 years. 66.07% live in apartments.

02 Average Walking Frequency and Duration

80.36% spend less than 30 minutes on each walk.

75% of respondents walk their dogs fewer than three times a day.

03 Training Status and Reasons for Not Attempting Training

60.71% attempted to train their dogs but failed. 25% successfully trained their dogs.

37.5% gave up due to a lack of time or energy. 12.5% were unsure how to start training.

12.5% felt no need for training as they could walk their dogs three times a day consistently.

04 Challenges and Reasons for Training Failures

71.43% faced conflicts between training and other commitments, such as work, making it difficult to continue.

72.92% mentioned that working during the day prevented timely feedback, leading to poor training outcomes.

78.57% reported frequent accidents during training, indicating their dogs struggled to adapt.

60.42% had to frequently clean up after their dogs' inappropriate toileting, adding to their burden.

05 Methods for Successful Training and Desired Features in the Device

75% use reward mechanisms (e.g., treats or toys).

100% incorporate attractants (e.g., urination inducers).

53.57% want the device to include behavior monitoring and reminders, such as tracking success in toileting.

Design Concept — A Guided Toileting System with Behavior Reinforcement

Three Parts of the Whole System:

  1. Data Collection

Collects data on the dog's water bowl and behavior, then sends it to the server.

  1. Data Learning Model

Analyzes and predicts urination behavior, sprays pet urination attractant.

3. Reinforcement Prototypes

Dog urinates in the correct spot, reward mechanism activates, like treat dispensing.

Part 01 — Data Collection

Gathering Dog Data to Predict Toilet Habits
Unit 1: Dog's Motion Collection Unit

Tracks the dog’s movement and sends the data to the server.

Unit 2: Water Level Collection Unit

Monitors the dog’s water bowl and sends the data to the server.

Code Snippet for Data Collection
Actual Data Collection Process
Database for Storing Collected Data

The ESP8266 board collects data and sends it to the server, where it is stored in an SQLite3 database.

Part 02Data Learning model

Outputting Predicted Results to Control the Water Pump and Spray Urine Attractant
Data Parsing

Processes sensor data for model training.

Model Structure

Built using Paddle, Baidu’s AI framework.

Data Learning Visualization: Visualizing Urination Data and Patterns
Data Model Prediction Accuracy

The data model's success rate is around 75%, given the limited data and the complexity of the dataset.

Part 03 — Reward Prototype for Positive Reinforcement

Unit 1: Receiving Results from the Data Model to Control the Water Pump and Spray Pet Urine Attractant.
Unit 2: Providing Positive Reinforcement by Dispensing Treats and Playing Recorded Encouragement.

When the sensors detect that the dog has urinated in the correct spot, the servo will rotate to drop treats, and the MP3 player will play the owner's voice as encouragement.

Demonstration Video: Showcasing the Entire Device in Action

Product Appearance Design

Product Draft
High-Fidelity Design Rendering

Ruoting (Linda) Sun © 2024

Ruoting (Linda) Sun © 2024

Ruoting (Linda) Sun © 2024

Ruoting (Linda) Sun © 2024