Freight Rate Mate

Project Overview

Dynamic visualization of truck location data
Crash risk heat map
Real-time machine learning based predictive analysis
Enables carriers and truckers to connect through SMS messaging directly availiable in our interface

Predicting and visualizing trucking risks using machine learning.

Insurance rates can be upward of $16,000 per year
By knowing high risk factors, insurance companies can provide incentives for truckers to avoid high risk areas
Our tool is also useful for carriers because it allows them to view information about their fleet and send drivers SMS messages directly from the interface

I used the Mapbox GL SDK to create the heatmap and real-time travel visualization. I also worked on routing API calls and manipulating the data that came from them.

Rashid Lasker
I'm a second-year at UVA majoring in CS. I'm primarily interested in machine learning, design and full-stack development.
I worked on cleaning and preparing the data, as well as the RGBoost regression model. I also used AWS SNS and Lambdas to enable text message notifications with the click of a button.

Austin Sullivan
I worked on integrating AWS into the visualization, utilizing Lambda, API Gateway, and real time machine learning learning.

Christopher Geier

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