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Innovative processing for flight practices

Project description

DEENESFRITPL

Supporting flight dispatchers for improved pre-departure operations

The EU-funded Dispatcher3 project, an Innovative Action within the framework of the Clean Sky 2 ITD System, will enhance airline operations by improving flight operating processes prior to departure. It will provide an infrastructure able to automatically gather and prepare historical data, use machine learning techniques for estimating the variability between planned and executed flight plans, and provide advice to dispatchers, pilots and schedulers. Dispatcher3 will support dispatchers in the design and selection of flight plans, also advising pilots on expected outcomes. The data infrastructure will be driven by DataBeacon, a multi-sided and open-source data storage and processing platform. The software prototype will be comprised of three layers: a data acquisition and preparation module, a predictive model and a dedicated advice generator module.

Objective

"Dispatcher3 will develop a software prototype for the acquisition and preparation of historical flight data in order to give support to the optimisation of future flights providing predictive capabilities and advice to dispatchers and pilots. This will be done considering airline preferences and the impact of flight missions on overall airline objectives. Dispatcher3 focuses on activities prior to departure: dispatching and pilot advice on how to operate the flight.

Dispatcher3 is composed of three layers: data infrastructure, predictive capabilities and advice capabilities.

The data infrastructure will be powered by DataBeacon, a multi-sided and open-source data storage and processing platform. DataBeacon provides private environments, secure data frames, a full-stack artificial intelligence environment and a scalable highly available on-demand cluster. DataBeacon has been developed and successfully been used in other initiatives by members of the consortium. The infrastructure will allow further developments, based on data science techniques, to be built on the pre-processed datasets.

The predictive capabilities will be provided by the development of two modules: data acquisition and preparation, encompassing data wrangling and descriptive analytics, and a predictive model, which will perform target variable labelling and feature engineering, plus the training, testing and validation of machine learning predictive models for targeted airlines' KPIs.

With the same predictions, different advice could be generated considering user policies. The advice capabilities of Dispatcher3 will be provided by a dedicated advice generator module, which will collect all the information from the predictive analytics and build a decision framework, which could be used by dispatchers and pilots.

Dispatcher3 fits within the activities of CS2 Systems ITD WP1.3 ""FMS and functions"" and addresses some of the high-level objectives and challenges for this ITD defined by CS2."

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Programme(s)

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Call for proposal

H2020-CS2-CFP10-2019-01

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Funding Scheme

IA - Innovation action

Coordinator

THE UNIVERSITY OF WESTMINSTER LBG
Net EU contribution
€ 188 375,00
Address
REGENT STREET 309
W1B 2UW London
United Kingdom

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Region
London Inner London — West Westminster
Activity type
Higher or Secondary Education Establishments
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Total cost
€ 188 375,00

Participants (5)

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Last update: 18 December 2023

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Permalink: https://cordis.europa.eu/project/id/886461

European Union, 2024