Create a web app.
Budget: $30 – $250 USD
⦁ Deliverable: We aim to deliver an accessibility tool that generates novel and intelligently designed routes for the kilter board from the browser. The app will provide a social login to allow users to easily identify themselves, and create favorite routes for each kilter board. Also allowing sharing the route with friends and via the existing mobile application.
⦁ Motivation: A Kilter Board is a climbing entertainment and training tool used by many climbing gyms and individuals around the world. The Kilter Board is a grid of standardized climbing holds that light up allowing its users to follow and climb on a preset path up it. Because it’s a standardized product anyone with access to a Kilter Board could climb the same routes as their friends anywhere in the world. The idea was to create an app that allows for it’s users to generate random climbs with parameters to diversify their climbing experience.
⦁ Technical Approach: We’ll be building a web app using Flask in the backend and React/JS in the frontend, tied together using API’s. The app will feature social login via Google, and be deployed on Heroku. The app’s functionality will be easily accessible. The machine learning model that generates the routes will run in browser on the client side using Tensorflow.js
⦁ Motivation: A Kilter Board is a climbing entertainment and training tool used by many climbing gyms and individuals around the world. The Kilter Board is a grid of standardized climbing holds that light up allowing its users to follow and climb on a preset path up it. Because it’s a standardized product anyone with access to a Kilter Board could climb the same routes as their friends anywhere in the world. The idea was to create an app that allows for it’s users to generate random climbs with parameters to diversify their climbing experience.
⦁ Technical Approach: We’ll be building a web app using Flask in the backend and React/JS in the frontend, tied together using API’s. The app will feature social login via Google, and be deployed on Heroku. The app’s functionality will be easily accessible. The machine learning model that generates the routes will run in browser on the client side using Tensorflow.js