I’m starting a nonprofit to save the lives of dogs and cats by finding out where they are statistically more likely to be adopted and then moving them there. A description is below:
With a team of data scientists, I am collecting data about what dog traits make a dog more likely to be adopted in which locations. After I obtain the data, I will analyze it by breed, age of dog, and size, and then relocate dogs to where they’re statistically more likely to be adopted. For example, if terriers are more likely to be adopted in Dallas than Houston, we’ll move a certain number there according to the model. Given that 800,000 dogs can cats per year are killed nationwide in shelters, this has the promise to save many pet lives.
I am using machine learning and data science techniques to find the optimal distribution of dogs to ensure adoption. I’m also using Google image recognition technology to identify the breeds in photographs since they are often mislabeled. Natural Language Processing will be used to determine if there are any trends to uncover in the dog's description on PetFinder/Adopt-a-Pet.
After I get the process in place with dogs, I’ll expand to cats. I'm working with the head of a company called Doobert that has more than 23,000 volunteers who transport animals all over the nation, and I am also exploring partnerships with other organizations.
I’d love to hear suggestions and ideas from this forum about ways to make this even better and ensure success. I’m currently talking to major media outlets and am excited about the prospect to save lives. Also feel free to reach out to me privately if you’d like to contribute. Thanks so much!
#DataandTechnology