This unreleased wearable technology did not have a visual app that they could show off to the average joe. Intrinsic Automations was the client for this project. Having a history developing for the Boogio platform, Protogenos was already equipped with an architectural understanding of the technology and accepted the contract. We worked tirelessly with IA to meet their May 15th deadline, successfully establishing a functioning Boogio AHRS. We worked with them to capture their foot movements and have cool 3D shoes mimic their every motion.
Find out more about IA’s involvement and read the science behind it all on IA’s website here.
Having had worked with the Boogio team for their user dashboard, our team was quick to determine their software needs. Jose Torres sent a hardware prototype by mail to our offices that we could interface with Bluetooth. We researched algorithms and advanced mathematics needed to turn numbers from the hardware into stable motion.
Given the staff budget we designed a simple app that would show a pair of shoes facing the viewer. The user could toggle between different pairs of shoes by pressing one button and calibrate the sensitivity by menu.
Work Begins April 1st
Our team used Git and their in-house Bonobo Server to pull and make changes across multiple branches during the development process. We communicated via their Slack channel and occasionally e-mail.
Completed May 19th
The app was able to display shoes and move with the foot in real time. The app was optimized and the user interface was cleaned up in order to look presentable for investors. After a series of minor visual changes requested by Jose Torres, the app was deployed, and the project complete.
The high level development model featuring the primary components needed in the futures trading system. We would build every component including the Client App.
This project was large, but nothing our team couldn’t handle. However our client depended on us for our software expertise and they had plans to scale the system later. They requested online documentation that could be followed with step-by-step instructions to build the project from source. It includes database table schemas, high-level overview, how to launch the server correctly, and finally the Python API that allows our client to upload scripts to be used as algorithms on-the-fly.