Cithaeron

Connecting emergency dispatchers to victims in need

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Inspiration

I wanted to create a platform that would allow victims of natural disasters to easily reach out and find supplies and assistance, even if they didn't have access to a stable wifi connection. Witnessing the aftermath of Hurricanes Irma and Harvey, this problem has become even more prevalent, and finding a viable solution that would allow dispatchers to best address problems faced by victims of these disasters would be the best way to target future disasters while utilizing current technologies to better assist those in need.

What it does

Cithaeron relies on Verizon's Thingspace SDK and MapQuest API to map out ideal routes for dispatchers to take in order to reach victims in need. It provides easy access and visual data on the quickest roads to take to reach a location, as well as ideal means of traveling to address victims.

The application also makes use of Amazon AWS's Lex AI and Nexmo's SMS and WebSocket API in order to create a streamlined means for victims to announce their needs to dispatchers, as well as their locations. Volunteers can easily assign themselves to tasks, as well as determine the best course of action to take to help out the greatest number of victims.

How I built it

I used Express.JS and Node.js to build a server on which I was able to host the site. In addition, I was also able to use a Node.js server to receive SMS messages and distribute the data to a Firebase realtime database from which Cithaeron could pull data onto its main platform for dispatchers to view.

Challenges I ran into

It was difficult to integrate the Firebase datatypes and database format into the MapQuest API, especially since there were numerous encoding issues with UTF-8. I also had difficulty with setting up the Lexbot AI service and deploying the bot - initially, I tried using Facebook Messenger and several other platforms to test out the AWS client, but I ultimately settled on using Nexmo's API and integration with Lexbot.

Accomplishments that I'm proud of

I'm proud to have built this in the short <20 hours of the hackathon, and to have been able to demo a working product that demonstrates elements of chatbot intelligence and automated machine learning.

What I learned

I learned a lot about how to integrate AWS products into web applications, building with Express.JS and Node.js, and Javascript web development. I also learned about deploying webhooks and bot integrations through Hyphenate's REST API.

What's next for Cithaeron

I'm hoping to build out the chatbot functionality to become even more helpful to victims of natural disasters, as well as to deploy the application so more dispatchers will be able to utilize the software to determine the most efficient routes to reach victims in need.

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