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Guy Creates A Gadget That Can Track Destination And Origin Of Flights Flying Above His Home


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Meet Jeremy Merrill who lives underneath a flight path to LaGuardia Airport in New York. Merrill is a curious person and after observing hundreds of planes land at LaGuardia and wondering where they were coming from, the New York Times journalist/developer came up with a system that is able to display the flight’s origin on his window sill.Amazing Genius Airplane Tracker Created By A Journalist For LaGuardia Airport 3

The software that he has created is known as ‘Flyover’ and works by collecting the information that airplanes are transmitting over their transponders, making use of a number of programs and then displaying the origin airport of the plane flying over Merrill’s apartment at that moment.

The passenger jets broadcast information about themselves every few seconds over the radio systems known as ADS-B and Mode S. These packets of information contain the plane’s location, registration number, and altitude along with its flight number. Merrill is able to collect this information by making use of a SDR antenna.


Flyover uses the program Dump1090 for collecting the information that is being released by the airplanes. This information is then sent to a webpage where flights are tracked and then displayed on a map. Merrill doesn’t bother himself with the flights that are above 10,000 feet since they are unlikely to land at LaGuardia. Once the information has been sent to a webpage, he uses Virtual Radar Service for determining the plane’s route.Amazing Genius Airplane Tracker Created By A Journalist For LaGuardia Airport

Once the route has been established, the only issue left is of displaying the origin airport on the LED display at his window sill. The LED screen works similar to ‘ambient notification’.

He said, “I really like building ambient/automatic notifiers for myself, to protect against my own absentmindedness. For instance, a computer sends me an email each morning telling me which subway to take based on delays — so I don’t have to remember to go to the MTA’s status page. I also have a computer that predicts (using machine learning and the city’s BusTime API) when a bus near my apartment is about to arrive, then notifies me with red and green lights to tell me when to go catch it.’

Pretty cool, isn’t it?


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