Adaptive ML system to predict air traffic delays - MIM Solutions - We make artificial intelligence work for you

Case study

Adaptive ML system to predict air traffic delays.

Challenge

Creation of an adaptive ML system for predicting and scoring flights based on online flight data

CHALLENGES continued

Project implemented in coordination with GIVT Sp. z o.o. This Warsaw-based company specialises in helping passengers obtain compensation for disrupted flights from appropriate airlines.

The system is able to:

predict in real time possible flight disruptions, i.e. delays, cancellations and redirections to other airports;
classify in real time possible reasons for flight disruptions after their occurrence and verify the applicability of WE 261/2004 compensation;
estimate the claim value related to disrupted flights and propose the optimal procedures for handling it.

Organisation profile

This project is to help scale up activities that should enable expansion throughout the European market. The project will solve one of the key problems in air traffic and its disruptions.

Other similar systems that are currently being developed rely on limited data and therefore produce results of unacceptable significance. One of the most important aspects of this project is the creation of understandable ML systems as a detailed understanding of each claim is required when communicating with the airlines.

Solution

This project aims to build the first reliable flight disruption prediction and assessment system that will use the full spectrum of available data.

Other similar systems that are currently being developed rely on limited data and therefore produce results of unacceptable significance. One of the most important aspects of this project is the creation of understandable ML systems, as a detailed understanding of each claim is required when communicating with the airlines.

Business value:

The project was conducted in cooperation with GIVT AG and aimed to:

help passengers in applying for flight compensation;
deliver flight reliability predictions, i.e. for a specific flight, it gives the probability that the flight will be delayed;
alert travellers that the flight might get delayed even before it departs.

For example, our system is able to deliver high quality predictions before the actual flight departure. The figure on the right shows the precision-recall curve for predicting serious flight disruption (i.e. a delay of more than 3h) that was created 3h before the flight departure.

Go ahead and learn what our client thinks about the project in our case study – Case Study GIVT

Results

The claim is handled fully automatically in over 60 percent of cases. When detecting delayed flights, we were able to achieve a precision of 90 percent with an accuracy of 57 percent.

Our work in AI is a tangible result of our team's commitment to research and development.

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We would like to express our satisfaction with MIM Solutions regarding the development of our web application. Piotr Wygocki and the development team did a very professional job. We are really pleased with the solution they provided and with the communication flow throughout the project. We would like to recommend Piotr Wygocki and his development team. We look forward to working with them on future projects.

ML/AI production-grade projects require adopting a very practical approach. Our partnership with MIM Solutions was a true pleasure; they are professional, highly skilled and thorough. Therefore, I highly recommend collaborating with the team, both at conceptual stage as well as in delivery.

I am really impressed by the quality of services I received from MIM Solutions. They are definitely professionals. They do not miss deadlines, cooperation with them is smooth, and they are fully committed to what they do. They are world-class specialists in their field. Even the most difficult challenges in the field of algorithmics, data analysis and artificial intelligence are feasible for them.

MIM Solutions can help develop AI in your company, please contact us and we’ll talk you through it.

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Case study