Big Data Car Crash Analysis With Python

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  DriveBuddy Running on Pebble

Inspiration

I'm very interested in data analysis, so when looking for a project for RedBirdHacks, it was my go to idea. I took a large data set about traffic collisions and made it my goal to use data analysis to understand the major causes of car crashes and consider how that knowledge could be used to prevent future accidents. ALL OF MY RESULTS ARE AT THIS ADDRESS -> frichetten.github.io (<-Thats a website. Put it in a browser)

How I built it

All of my analysis was done using tools I created myself in Python. The Matplotlib library was used to create graphs and charts. I got the data from http://catalog.data.gov/dataset/maryland-statewide-vehicle-crashes-cy2015-quarter-1 . It is a freely available repository of data on car crashes from the state of Maryland in 2015. It has over 19 million points of data that I consider during my analysis.

DriveBuddy

DriveBuddy was an idea spawned after seeing the results of my analysis. The majority of car accidents are caused by drivers failing to pay attention. How can we fix that? DriveBuddy may be a part of the solution. The idea is simple; the driver starts the DriveBuddy app on their Pebble smartwatch when they get in the car. The app will trigger a sharp vibration every few minutes. The idea is that the vibrations will be infrequent enough so that the user doesn't get accustomed to it, but still frequent enough to remind them to get off their phones and pay attention. A gentle reminder every few minutes may help reduce traffic accidents.

Built With

• python