Powered by a Raspberry Pi, audio input is translated and displayed on an LED matrix. This project is written in Python and uses the CircuitPython and PIL libraries to process and display images on the LED matrices. These matrices are connected to the Raspberry Pi's GPIO ports. Mozilla's DeepSpeech API is used for audio processing, and it uses an offline machine learning model to transcribe audio to text for the matrices to display.
Using the UNIX API, I implemented a custom shell in Linux. The program is written in C++, and takes advantage of the fork and exec functions to duplicate the process and execute the command, respectively.
This was a class team project over the span of four weeks, with two dedicated to design/planning and two dedicated to implementation. The project utilized a PostgreSQL database connected to a JavaFX project using JDBC. The system allowed customers to view and order products, and allowed management to modify products and view trends. I worked on the front-end and back-end for the some scenes including the expanded menus, the cart, and order queue/status.