There are 8.1 Million cats and 7.7 million dogs in Canadian households and by expert estimation 1/3 go missing in their lifetime. That is an estimated 5.26 million family members that are lost in their lifetime. I know that everyone here that is a pet owner would want to find their lost animal and there is hope. Experts estimate a dog will travel 2-16 Kms from their home but a cat travels a median distance of roughly 2-17-houses from their home. The most effective strategy of finding a missing animal is to conduct a physical search of the area and put-up signage to get members of the community to help with the search.

What it does

We believe our product, the findmypet app, will help in the search and rescue of lost pets by revolutionizing the signage strategy, we aim to build a social network that brings the community together to find our lost family members.

How we built it

Our app is built on a modern tech stack that is both easy to use and very powerful. Going forward this provides us with a framework to build on our current functionality. We utilized a flutter frontend and used the Google Cloud Platform for storage but also a Database, Authentication System and for it’s Cloud Functions. Using the Cloud Functions we have built input forms, profile and home pages and many more features. We used the Cloud Functions to connect our Docker container that we use to spin up the ML features.

Challenges we ran into

Integrating Machine Learning built with python and into an app base built with Node.js, TypeScript and Flutter. Learning new tools such as Flutter

Accomplishments that we're proud of

Used GCPs Cloud Function to work with the Docker container that housed the python script. Able to learn new tools and complete the project

What we learned

New Tools Having pre-definied features for proof-of-concept (helped in avoiding feature creep) How to deploy ML models

What's next for findmypet

Additional features such as vicinity-based notifications, enhanced ML models and tools such as description based keyword extraction for tags A monetization strategy

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