Deliverables
The document will analyse the business requirements of the application areas to improve the impact of the pilots.
This deliverable will report a preliminary market analysis and business requirement for the FANDANGO application areas. This report will also include the FANDANGO Innovation strategy.
This report will describe the aspects of scalability and replicability of the big data tool.
In collaboration and extension of D1.1, D1.2 and D1.3 this deliverable will define the technical work plan and system requirements necessary to fulfill the goals.
This deliverable contains the comprehensive pilot execution and evaluation plans (PEEPs) for each pilot use-case domain, detailing how the pilots will be executed and evaluated. The document will be revised accordingly as the project progresses.
This report will present a full exploitation plan and action/analysis of technology uptake from FANDANGO
The deliverable will provide the design and the specification of every single FANDANGO component as well as the description of their implementation, integration and validation process.
This deliverable will describe how the FANDANGO project manages data throughout its life cycle, according to the regulatory framework.
This deliverable will include a description of the dissemination strategies and activities to be followed by the FANDANGO partners, as well as KPIs and metrics to be monitored.
This deliverable will contain the organization of data elements and how are related with both internal and external modules.
This deliverable contains the updated PEEPs as well as an overview of the outcomes of the first pilot iteration for each use-case domain. It will also contain the results of the validation of the different piloting activities.
This deliverable present an assessment of the impact of the project, both qualitatively, through case studies that demonstrate its impact, and quantitatively, via the metrics developed in the Dissemination Plan (D.7.2).
The deliverable will define FANDANGO reference architecture describing how the FANDANGO components will interact each other.
An initial list of available data will be collected very early. It contains the data which is available for starting the first pilots.
This deliverable will collect the user requirement and will be the basis od D2.4.
This deliverable contains the updated PEEPs as well as an overview of the outcomes of the second pilot iteration for each use-case domain. It will also contain the results of the validation of the different piloting activities.
The deliverable will provide both: a) a report providing a detailed state of the art of the topics of Task 4.3 as well as the algorithms that are selected to be integrated in FANDANGO prototypes, and b) a prototype deliverable of the work done in Task 4.3 and will deliver the appropriate software and a report acting as manual of the provided software.
The deliverable will provide both: a) a report providing a detailed state of the art of the topics of Task 4.4 as well as the algorithms that are selected to be integrated in FANDANGO prototypes, and b) a prototype deliverable of the work done in Task 4.4 and will deliver the appropriate software and a report acting as manual of the provided software.
This is a prototype deliverable that will provide updates in all modules of WP4 following the evaluation phase as well as a report with all the necessary details on the provided software.
This deliverable will be formed by the software tools that normalize the incoming data.
This deliverable will be a software package containing the components for data lake with its corresponding relevancy label.
A platform for ongoing public engagement, including areas for news releases, project reports and technical documentation. Will include links to tools and source code created by the project, as well as datasets.
The deliverable will provide both: a) a report providing a detailed state of the art of the topics of Task 4.2 as well as the algorithms that are selected to be integrated in FANDANGO prototypes, and b) a prototype deliverable of the work done in Task 4.2 and will deliver the appropriate software and a report acting as manual of the provided software.
This deliverable will implement the data gathering tasks and data preparation for ML models.
The deliverable will provide both: a) a report providing a detailed state of the art of the topics of Task 4.5 as well as the algorithms that are selected to be integrated in FANDANGO prototypes, and b) a prototype deliverable of the work done in Task 4.5 and will deliver the appropriate software and a report acting as manual of the provided software.
The deliverable will provide both: a) a report providing a detailed state of the art of the topics of Task 4.1 as well as the algorithms that are selected to be integrated in FANDANGO prototypes, and b) a prototype is a prototype of the work done in Task 4.1 and will deliver the appropriate software and a report acting as manual of the provided software.
This deliverable will describe how the FANDANGO project manages data throughout its life cycle, in order to be compliant to the regulatory framework.
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Publications
Author(s): Anargyros Chatzitofis, Pierandrea Cancian, Vasileios Gkitsas, Alessandro Carlucci, Panagiotis Stalidis, Georgios Albanis, Antonis Karakottas, Theodoros Semertzidis, Petros Daras, Caterina Giannitto, Elena Casiraghi, Federica Mrakic Sposta, Giulia Vatteroni, Angela Ammirabile, Ludovica Lofino, Pasquala Ragucci, Maria Elena Laino, Antonio Voza, Antonio Desai, Maurizio Cecconi, Luca Balzarini, Arturo
Published in: International Journal of Environmental Research and Public Health, 18/6, 2021, Page(s) 2842, ISSN 1660-4601
Publisher: Int. J. Environ. Res. Public Health
DOI: 10.3390/ijerph18062842
Author(s): F. Nucci, S. Boi, M. Magaldi
Published in: IFDAD 2020, 2020
Publisher: IFDAD
Author(s): G. Palaiopanos, P. Stalidis, T. Semertzidis, N. Vretos, P. Daras
Published in: 2019 IEEE International Conference on Engineering, Technology and Innovation, 2019
Publisher: IEEE
Author(s): Francesco Nucci, Massimo Magaldi, Luca Bevilacqua
Published in: Ital-IA, 2019
Publisher: Ital-IA
Author(s): D. Martín-Gutiérrez, G. Hernández-Peñaloza, J.M. Menéndez, F. Álvarez
Published in: NEM Summit, 2020
Publisher: Nem summit