Happy Hamster

Happy Hamster is on a mission to revolutionize pet healthcare and contribute meaningfully to biomedical research. Hamsters, not just adorable pets but also invaluable model organisms, offer a unique opportunity to improve healthcare outcomes for animals and humans alike.

Unlike traditional lab mice, hamsters possess a strikingly human-like immune system, making them an excellent model for diseases ranging from respiratory to cardiovascular. This has even more weight considering there are over 1.5 million pet hamsters in the U.S. alone [2]. Given the impressive funding recently received by pet healthcare companies like Loyal ($27M) [3] and Embark ($75M) [4], we see a massive untapped potential here.

Happy Hamster aims to shift the paradigm from traditional lab-based animal testing to a more humane and preventive model. Our solution utilizes decentralized technologies to promote transparency, collaboration, and diversity in healthcare research. In simple terms, your pet hamster could contribute invaluable data to science, improving the quality of life for animals and humans, all while reducing the reliance on lab animals. This is just the beginning; to truly thrive, Happy Hamster will require robust governance mechanisms and partnerships with veterinary labs.

1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6781508/
2. https://www.marketwatch.com/story/forget-dogs-and-cats-hamsters-are-quickly-becoming-the-it-pet-11642599895
3. https://techcrunch.com/2021/09/23/loyal-raises-27m-aims-to-give-dog-owners-more-time-with-their-pets/
4. https://techcrunch.com/2021/07/26/softbank-backed-embark-veterinary-valued-at-700m-after-75m-series-b/

Happy Hamster is built on a Next.js foundation, bolstered by an array of innovative technologies:

LivePeer: At the core of our project is LivePeer's decentralized video streaming. Currently, we are gathering real-time data from a toy hamster prop as a precursor to monitoring live pets.

OpenCV and YOLO (You Only Look Once): These open-source computer vision and machine learning libraries power our app's hamster object detection capabilities. During the hackathon, a custom dataset was annotated and trained using Roboflow, a platform for training machine learning models. With more time, we aim to implement a more transparent model training and analytics workflow using a decentralized computing network like Lilypad.

IPFS and Web3Storage: LivePeer auto-records data to IPFS. Web3Storage is also used in our app to auto-annotate and store data on IPFS, ensuring a transparent and tamper-proof data storage solution for collaboration.

Community Building: We've embraced the playful ethos of the Noun community in our design, aimed at democratizing and diversifying participation in biomedical research.

In addition, we've crafted a custom hamster-themed Noun artwork wearing a labcot. It's our whimsical nod to a community that celebrates diverse creatures and objects but lacked a hamster—until now!