The goal of this project is to develop and implement a CAN protocol based communication system for the University of Texas’ Solar Vehicle Team. CAN stands for communication area network and is by allow each sub-system of the car to communicate with each other and give telemetric diagnostic data to the solar vehicle team during races.

Our platform consists of two implementations of a custom Feature Network Description language that will generate features for State Street's proprietary machine learning algorithms as well as serve as a back-testing and live Forex trading system. Our Python implementation of the FND will allow for historical back-testing with large amounts of data, and our GOLang implementation utilizes a multi threaded design to quickly ingest live data, process the data, and then send buy/sell orders based on a basic trading strategy we developed.