Pawfessor

Hefan Lim

A customized dog training application with a 3D avatar function that fits each user’s individual needs

Thesis Statement

Dog parents no longer have to wander through sites to look for training information about their unique dogs. Pawfessor is a customized dog training app that fits each user’s individual needs and provides accessibility for all dog parents to reduce the chances of dog abandonment due to the undesired behavior of their dogs.

Abstract

Americans adopted millions of dogs during the pandemic. However, as new pet parents return to work, many pets might be returned to the shelter. The top reason dogs get returned to animal shelters is because of behavior problems such as destructive aggression, barking, and disobedience. Many dog parents don’t want to pay for a trainer or classes because of the high cost. If dog owners know how to train their dogs, they can bond with their new dogs. Unfortunately, returning dogs to shelters increases their risk of premature death. Most animal shelters have capacity issues, often resulting in dogs euthanasia when capacity is full. Therefore, training dogs is a good way to avoid dogs returning to the animal shelter or being abandoned.

Every dog and owner is different in their needs, and it’s challenging to find a suitable training method or professional trainer. Therefore, I want to create an accessible for all training levels and rescue and special needs dog training app to fulfill users' needs and help users solve their dogs’ undesired behavior. There are various dog training apps to learn commands and tricks in the current application market. Most dog training apps only offer professionally tailored programs, but they cannot help offer fixed textbook solutions without much flexibility to consider the different personalities a dog may have. Based on my research and communication with the professional dog trainer, I learned that different dogs have distinct personalities and require different training methods. Some dogs are open and friendly, whereas some are very timid. The most effective way to train a dog is based on its behavior and characteristics.

To create a unique application different from others, Pawfessor has an avatar function that can transform the user’s dog image into a 3D look-alike and automatically bring the avatar to the dog profile and embed it into the training documentation as well. Therefore, users will see the avatar as a representation of their ideal dog.

Research Questions

  1. Why do so many people not train their dog? How to engage and motivate dog parents to train their dogs?
  2. How to help users easily find the right class or professional trainer without being overwhelmed by too many choices.
  3. What are the most struggling or challenging things when owners train their own dogs? Do they stop trying or continue trying?

Outcome

A dog training Application that has accessibility for all dog parents and the customization ability could tailor to each user’s need individually, so users don’t have to spend too much time wandering through sites to find the training information for their dogs. By using the Pawfessor application, users can add ratings for each session to track their dog training performance progress. The progress result will display on the homepage, allowing the user to view dog performance over a day, week, month, or year. In addition, Pawfessor provides a dog avatar function by scanning or taking a picture of the user’s dog and then embedding it into the training instruction. Therefore, users can see a dog avatar in the application as a representation of their ideal dogs.

Designer
Hefan Lim

Chang Kim—Primary Advisor
Graphic Design Professor, SJSU

Jennifer Ting—Secondary Advisor
Senior UX designer /JP Morgan Chase

Rose Fu—Tertiary Advisor
Co-Founder / Ultra k9 Dog training School

Brandon Brown Mary Gutierrez Phi Ho Linh Hoang Brandon Huynh Rachel Lee Hefan Lim En Yu Ma Miguel Morejon Dana Nissan Anela Oliveros Sylvia Ow-Yang Ryan Parajas Karla Peralta Sarah Sauerzopf Chako Shinmoto Tanya Shrivastava Wenwen Su Tianting Sun Hung Tsai Thanhthao Van Effy Wang