Inspiration

Natural disasters happen. We can't change that. However, we didn't set out to solve natural disasters, we sought to alleviate disaster pain. From this concept, one thing that is pervasive to all natural disaster problems is the massive amount of traffic and chaos which scorns the roads from the disaster to safety. We realized that while natural disasters in our local communities may be inevitable, we can facilitate a service that both builds community and helps others during times of need. Introduce Hestia. The free rideshare app that will revolutionize the scheduling problem of getting as many people to safety as possible, while also not increasing extra traffic or chaos.

What it does

Hestia alleviates traffic congestion during natural disasters and helps those who otherwise wouldn't be able to get out. It puts drivers able to assist with preventing damage associated with natural disasters in touch with those who are in danger of losing their lives from such a disaster, distributing such drivers in an optimal manner across a natural disaster area in order to maximize the number of lives saved from a potential tragedy.

How I built it

The main engine uses Python on the backend to collect information about natural disasters and store it in a MongoDB database. A node.js server provides an API that allows drivers and those who may need rescuing to register for the service. A React front-end powers the mobile app.

Challenges I ran into

We decided to pick up many new technologies while developing this application, and learning these technologies took a significant amount of time.

What I learned

We learned how to use Python to conduct data analysis and develop an algorithmic engine for determining where cars should pick people up next, allotting drivers to people in a way that will minimize time for the sake of the safety of the drivers. We also learned how to develop cross-platform mobile apps through a service such as React Native.

What's next for Hestia

Ideally, we'd love to complete the functionality of the application, fleshing out the relationship between mobile driver and rescuee through plotting precise paths using population density in various parts of disaster areas as well as breaking news reports to determine the best and safest paths for escaping such a disaster area, as well as focusing on locating a precise shelter outside of the disaster radius.

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