First, a workshop with the Advisory Board was carried out (09OCT20) followed up by bilateral discussions. Several meetings were held with Vueling to better understand their pre-departure operations and needs. These activities were reported in D1.1 - Technical resources and problem definition (01DEC20 - M7) reaching MS2 - Technical resources and problem definition completed.
Acquiring the datasets was a complex task due to difficulties on gathering the data from Vueling. Data Protection Agreements were put in place to facilitate the data transfer. D2.1 - Data definition and processing report (30APR21 - M11) was produced identifying data sources required for labelling and feature engineering and a roadmap for their acquisition; MS3 - Domain driven data engineering techniques identified was achieved.
The activities of WP3 - Data engineering and analytic techniques were extended to overlap the model development (WP4) and validation (WP5). D3.1 (22SEP22 - M28) describes the data, pipelines and the challenges of machine learning projects. With this MS5 - Domain driven analytic techniques identified was reached. In machine learning models development and validation are conducted interactively. An Extract-Load-Transform data pipeline was implemented for the definition and usage of a data lake. Two releases of Dispatcher3 were produced. The first release focused on the individual models targeting key performance indicators at two prediction horizons: pre-departure and planned flights. D4.1 - Technical documentation first release and D4.2 - Prototype package (first release) (27JUL22 - M26) formed this release (MS5 - First release results review). A workshop (followed by surveys) was then carried out with the Advisory Board (17MAY22 - M24). This, along a set of internal meetings and workshops, allowed the consortium to prioritise the further development of the models and the definition of the Advice Generator. The focus of the final release (D4.3 - Architecture and prototype description and D4.4 - Prototype package (final release) (17NOV22 - M30)) was on improving the models (ensuring data availability at the prediction horizon), the interface, and integration into high-level models to produce actionable advice.
The activities of WP5 - Prototype verification and validation were conducted in parallel to the models development once the Verification and Validation plan (D5.1) was submitted (11AUG21 - M15). The outcome of all these activities was presented in D5.2 - Verification and validation report (9DEC22 - M31); MS7 - Prototype verification and validation completed.
Steps towards industrialisation are summarised in D6.1 (13DEC22 - M31). Dispatcher3's components are suitable to be exploited independently. Pre-departure models could be incorporated into flight planning systems or crew support decision tools (such as Pilot3 (project 863802) or FPO cloud system by PACE). The pre-tactical (ATFM) and reactionary models could be integrated into support tools for duty managers.
Communication and dissemination activities include: the definition of the communication, dissemination and exploitation plan (D7.1 - 30NOV20 - M6), the launch of the project website, publication of 6 blog entries and 19 social media post (LinkedIn), participation in 7 conferences (papers and posters/videos) and industrial exhibitions. In addition a journal paper are under development. D7.2 (25NOV22 - M30) summarise these actions.
WP8 ensured the project management with D8.1 - Project management plan (30JUN20 - M1), D8.2 - Proof of signature of Consortium Agreement (04AUG20 - M3), 7 periodic monitoring reports and 2 Periodic Reports. The milestone MS1 - Project kick-off was reached at M1 (25JUN20), MS4 - Intermediate Review Meeting at M13 (7JUN21), and MS8 - Final acceptance with the finalisation of the action (close out meeting held 29NOV22 (M30)).
