LABBRA is an acronym honoring six students and pedestrians who were tragically killed by vehicles near the UCF campus. Their names are not shared publicly out of respect for their families.
Benjamin walked and rollerbladed past their memorials often on the way to class. That, combined with his own close calls with cars, is what started all of this.
The team that turned the idea into the first working prototype as a university capstone.
Originated the idea, designed the system architecture, led hardware development across all three generations, and rollerbladed 500 miles to fund the first prototype.
Developed the web application and built an LLM chatbot that lets users interact with road data using natural language.
Created the simulation pipeline and built the data generation system used to train the machine learning model.
Designed and developed the proprietary machine learning algorithm for detecting accidents from sensor data.
It started on the walk to class at UCF. From there: research, crash data, and pitching cities and DOTs to validate the concept and sharpen the direction.
Benjamin recruited Lydia, Andres, and Caleb to build the first prototype together as a senior design capstone.
Benjamin rollerbladed 500+ miles across Florida. The team promoted the journey on social media and ran a GoFundMe to fund the prototype.
Built the first generation hardware, the initial accident detection ML model, and the web application.
Built the second generation hardware, collected real traffic data in the field, and completed a full traffic study.
Benjamin is now developing Gen 3 hardware, securing pilot opportunities, and forming the company.
Conceptual render. Not final product.
We're going from campus project to real world deployment. If you want to be part of what comes next, whether as a partner, a pilot city, or an investor, we'd love to talk.