Mercedes-Benz VI.OS

The Vans Intelligent Operation System (VI.OS) is a data platform set up for the Mercedes-Bens Vans organization. It originates in Charleston, where I worked on it, but it will be used throughout the world in all of the Mercedes-Benz Vans manufacturing plants.

The platform is for conducting analytics on all sides of the organization. We focused on production purposes, but the platform will grow into supply chain as well as business in the fullness of time.

Check out my colleague's documentation to find out more about the Microsoft Azure cloud suite and how to navigate it here.

NASA Research Grant

My team worked with JPL engineers to develop a mission concept for the exploration of Martian lava tubes. This mission concept is unique in that it incorporates multiple robots, but not in the traditional "swarm" style.

To navigate a tight space such as a lava tube, the robots need to be small and nimble. They still must carry all of the scientific instruments required to conduct thorough exploration and testing, so the tools are distributed amongst a coordinated fleet.

View our poster for the mission here.

To learn more about my coworkers' main focus (CADRE), click here.

Satellite Imagery Pathfinding

This project was created to find travel routes for extraterrestrial rovers using satellite imagery. This would allow us to search through many imaged locations of different planets to find potential landing sites that are highly travelable by rovers.

To learn more about the procedure and results, click here.

Spectral Unmixing

Spectral unmixing is used to identify materials using hyperspectral imagery. Different materials have different spectral signatures, allowing computers to categorize them into a library of pre-selected endmembers. This project tested the ability to automatically generate a library of endmembers for spectral unmixing using k-means clustering.

To learn more about the procedure and results, click here.

Street Flood Monitoring

This project was an attempt to host a flood map for Charleston city streets. Street flooding is a huge problem in Charleston. My team developed sensors that could be installed at flood-prone intersections to measure the real-time water level. This data could then be communicated with the public via an internet-based map.

A successful execution of this project would inclued the capabilities to host a visual map of flooded intersections, as well as an API for navigation/weather applications to query. The beginnings of this are hosted here.