Clear for Take Off

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46 solutions from 37 locations were created.
Description

To comply with security and airline protocol, air travelers should arrive at the airport well in advance of their flight. Without realizing the probability of adverse conditions at the time of the scheduled departure, they may experience inconvenient delays at the airport. Delays can be short and relatively easy to manage, or they can cause long hours of waiting in crowded airports. Flight delays can even cause forced overnight stays at local hotels or inside the terminal. Travelers could benefit from knowing the likelihood of a delay as it could help them prepare for the wait time. Can an app be developed that predicts the impact of weather on airplane departure times?

Background

Air travelers pay close attention to the local weather because weather may cause flight delays. However, delays can occur when the local airport has great weather, leaving the traveler stranded for hours and/or missing a connecting flight. A departing flight can be delayed because of weather at the destination airport, or a delay could occur if the flight has to be re-routed to avoid hazardous conditions along the traditional flight path. Changing local conditions at airports may also cause delays (examples: wind gusts, wind shear, icing, fog, etc.). All of these variables can be examined with a practical app that combines the various probabilities and gives the user advance warning that a delay is likely.

Considerations

Using the locator on the mobile device and various airport locations, the app should convey the expected weather conditions to the nearest possible time of departure. Based on flight safety rules, the app should predict whether the flight will take off on time or be delayed.

Solutions
Project teams from 37 locations solved Clear for Take Off
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Discussion
Sharath Chandra Ram 3 years ago
It's a really badly designed Challenge, without having data sources and imagining up a wild idea. However, the Bangalore team managed to do something cool with the limited data. Another way could be to acouple this challenge with local air traffic gathered directly from ADS-B signals.
Fatima Khalid 3 years ago
Agreed. We started out scraping some data, but then paying for it since it was reliable (only came out to around $5). Our app is fully functional :) https://github.com/christinakayastha/clearfortakeoff
Marius Petriman 3 years ago
Guys, we managed without paying a cent. That was this challenge about, using the free resources not paying for them. We aggregated even ILS information from a flight simulator database and it still did justice for the proof of concept.
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