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Air Traffic Control skill for Amazon Alexa
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alexa Was using wrong language+locale code for JP Nov 16, 2017
misc Added en-IN Language Capability Oct 24, 2017
requests Added local requests library for use on AWS Lambda Nov 15, 2016
strings Converted a bunch more hardcoded strings to Japanese Nov 16, 2017
util Converted a bunch more hardcoded strings to Japanese Nov 16, 2017
LICENSE Converted a bunch more hardcoded strings to Japanese Nov 16, 2017 Moved Google Maps API to /api, broke out credentials Nov 18, 2016 Added new features! Dec 29, 2016

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Air Traffic Control skill for Amazon Alexa. Gives information about what is flying over any location. Submitted as contest entry to the Alexa API Mashup competition on Hackster. (

Alexa Skill Deployment Status:

  • (2016.11.17 @ 19:15) Submitted for certification
  • (2016.11.20 @ 20:02) Re-submitted with updates for certification

How It Works

Given a location (string) by a user, we query the Google Maps API for the approximate latitude and longitude corresponding to it. We then query the ADS-B Exchange for any radar data within a 20-kilometer radius and return information about the one flying the lowest.

Future Work

  • Aircraft filtering (E.g. "What's the highest helicopter near Rochester?" or "Are there any blimps in Tillamook?"
  • Conditional filtering (E.g. "Is anything in Portland flying higher than 10,000 feet?")


  1. Clone the repo
  2. Get an API Key for the Google Maps Geocoding API. Go here for more information:
  3. Modify the key values in with your credentials. Open in an editor for more detailed instructions. (If not deploying to AWS Lambda, no need to modify the Alexa App ID.)
  4. Execute the AirTrafficControl class (python to make sure everything is working. Modify line 72 of with different location strings to test how that works.
  5. If you want to deploy using AWS Lambda and the Alexa Skills Kit, zip all of the files and upload. See the Amazon Alexa developer portal ( for more information on how to deploy. Look in /alexa for the intent schema and training utterances.


This project makes use of the following APIs:

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