Inspiration

We realized that while there are many news sources out there, with this, we can see what countries in the world are news hotspots - the ones that have the most things going on. You can view the world from a new perspective with our World New Map, seeing which countries are the centers of action and events.

What it does

It uses UiPath for web scraping to gather data from news sites. The program will then create a heat map based on the number of news reports sorted by category and the severity. The mobile app will then notify it's users when there is a problem with an area that they are in or is near them.

How we built it:

WebScraping(UI Path)

We used UiPath to gather data from news sites via web scraping. We accumulated around 5000 different data entries and exported them into CSVs, which are then put in a MongoDB Atlas database.

Cloud Storage(MongoDB Atlas)

We created a main database and sorted our data into about 100 different subfolders for different countries around the world.

Web Application (NodeJS)

Using Node.js and Google Charts we created a heat map based on the media coverage of the areas. We exported the mongoDB as a json and created it into a graph. We had a seperate file for each country to show the news. Clicking on Canada would show each province and show many articles each province has.

Android App(Radar.io)

We used Kotlin for the moblie app and used Radar.io to get the location of the user and notify them if they are in an area with a safety concern.

Deploy with Heroku

We deployed this software to the web with Heroku. Originally we had it running locally for testing, afterwards, we converted to a version that we could deploy with Heroku.

Assign a domain name

We used the free domain code to assign it to a .online domain.

Challenges we ran into

Radar.io software was complicated, there was very little documentation. Radar.io also had a bug on their end that did not allow the location tracking to work properly which forced us to hard code the app. There was also numerous issues with Heroku as we struggled to convert it from the local to a version we could deploy.

MongoDB's official documentation was vague and confusing, we had to resort to third-party documentation to use it.

We also had to create a heat map, which we were originally going to make in plot.ly.

Accomplishments that we're proud of

Learning how to use Radar.io, UiPath, and MongoDB Atlas.

What we learned

How to use Radar.io, UiPath, MongoDB Atlas, Heroku, Custom Domains, Static web-hosting. We also learned fast json manipulation to create graphs and output files.

What's next for WorldNewsMap

We could use machine learning to allow the application to predict future media coverage. We could then alert users that there could be potential danger in the area in the future. We also need more data from UIPath, the data should be proportional.

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