Team

bosthacks2017

Fall Boston Hacks 2017. Our team has decided to work with the Liberty Mutual API to implement a web application that recommends the safest and most optimal mode of transportation (Uber/Lyft, personal car, or public transportation) to users.

Our algorithm uses metric such as FBI crime data, Liberty Mutual API Data, and weather data. In addition, our application has the potential to expand by incorporating data from Liberty Mutual's upcoming API's on parking and safest route.

Furthermore as self driving cars become a reality, our application will lay the groundwork that allows a vehicle and its owner to make intelligent decisions on the road. These decisions might include whether or not to park in a specific location (based on parking availability and crime data), find a more optimal spot, or drive itself home.

We would like to emphasize that our application is fully functional for any given input (contingent on the data being available from our API's) and is not hard coded.

Built With

Submitted to

BostonHacks Fall 2017
- Winner BU Spark — Fellowship

Created by

I worked on integrating Liberty Mutual's home score API and Open-weather-map's current weather data API into our program. Once those two sections were solid and adjusted to work with any given input by the user, I began to work on our algorithm and how to incorporate the data from these two API's into it. Lastly, I created the main function that aggregates and processes the API data and outputs a final quantitative value along with a transportation recommendation based on that aggregate API data.

Tuna Sogut
Harsh Patel
Boston University CS 2019
Ali Kinay

Updates

Harsh Patel started this project — Oct 29, 2017 10:51 AM EDT

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