Challenge Data

Predicting response times of the Paris Fire Brigade vehicles
by Paris Fire Brigrade

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Competitive challenge
10MB to 1GB
Basic level


Started on June 10, 2019

Challenge context

The response time is one of the most important factors for emergency services because their ability to save lives and rescue people depends on it. A non-optimal choice of an emergency vehicle for a rescue request may lengthen the arrival time of the rescuers and impact the future of the victim. This choice is therefore highly critical for emergency services and directly rely on their ability to predict precisely the arrival time of the different units available. Any use of the image or name of the Paris Fire Brigade is subject to authorization from the Paris Fire Brigade.

Challenge goals

Your task will be to predict the delay between the selection of a rescue vehicle (the time when a rescue team is warned) and the time when it arrives at the scene of the rescue request (manual reporting via portable radio).

A first solution from a challenger has been published on GitHub:
It was not possible for us to wait any longer for the publication of this fabulous work. We will as soon as possible enhance it with the contributions of other challengers who also agreed to share their work with us. Thanks to all of them very much for the work carried out and shared.

What is extraordinary with this type of challenge is that the multitude of minds leads to the design of a multitude of methods which when combined lead us to a amazing solution that woud have not been possible to reach with the involvement of only one mind.

Data description

For an up-to-date description of that challenge consult the following page:

Benchmark description

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Paris Fire Brigade

Congratulation for the winners of the challenge

1 Nai Minh Quach
2 Nicolas Dieu
3 Pitterson Ibara

You can find the whole list of winners of the season here