Challenge Accepted

Inspiration

Our team was interested in many problems but, we wanted to solve a problem that we felt deeply impacted the Black community across generations. We felt inspired to create Challenge Accepted because we know people whose health is worse than it should be because they did not live healthy lifestyles. We were motivated to find a solution to reduce the leading cause of death in our community--heart disease.

What it does

Challenge Accepted is an app where you can connect with friends and engage in live fitness challenges. Not just another fitness app Challenge Accepted uses unique machine learning pose analysis to automatically count reps and make sure competitors are playing fair.

With Challenge Accepted, you can upload a pic of your meal and get real time stats on nutrition. Easiest calorie tracker, ever!

No bulky equipment or expensive new tech needed. Challenge Accepted helps all people build fun habits for a healthier future.

How we built it

We made use of the Xcode compiler along with the language swift for the development of the mobile IOS application. We made use of computer vision and Pose estimation to gather the joint locations on the body and used predictive analysis to recognize when a user performs a rep to increment the counter. The Image recognition software implemented within is a feature of Apple’s Core ML model. We recognize the food type and trace it’s ingredients and benefits using the spoonacular API.

Challenges we ran into

Our intended API’s were not working Our team run in a million errors Had a lot of knowledge games and huge learning curve

Accomplishments that we're proud of

Making the models work for on our app Taking on ambitious problem to heal our community Working together to encourage each other and come up with new ideas.

What we learned

Learned how to work with machine learning models The less practice you have with you something, the slower you are We learned that heart disease expanded far beyond our original scope

What's next for Challenge Accepted

Future implementations for Challenge Accepted includes developing a feature that detects abnormalities of the skin and recommends seeing a doctor about a skin condition.