PROJECT SUMMARY
This project proposes an innovative Digital Information Management (DIM) concept, i.e. the AICHAIN solution, that aims at enabling the cyber-secured exploitation of large private data sets that belong to different stakeholders and that contain valuable information that is valuable for ATM operations. To overcome the stakeholders’ reluctance to share sensitive data, the exploitation of such data will not be performed by exchanging the data itself but by articulating an advanced privacy-preserving federated machine learning architecture in which neither the training data nor the training model need to be exposed. This will be possible thanks to the innovative combination of two emerging DIM technologies: Federated Machine Learning (FedML) and Blockchain technologies.
The potential benefits of the new proposed DIM concept will be explored through ATM research use cases related to advanced Demand Capacity Balancing (DCB) predictive models of the Network Manager (NM), whose prediction performance is expected to significantly improve thanks to the exploitation of relevant operational private data from Airspace Users. The accuracy of the new DCB predictive models augmented with real operational data accessed through the AICHAIN solution will be benchmarked against the machine learning models for DCB that are currently in use or under research by NM.
The project will also address the exploration of governance and incentives mechanisms as part of the AICHAIN solution concept architecture, to facilitate the “buy-in”/adoption of the concept and the alignment of interests of the key stakeholders (especially of the data owners). The design of advanced governance & incentives mechanisms, which could be implemented using the mechanism of “smart contracts” available in the toolset of Blockchain, will be complemented with a qualitative identification of data exploitation benefits and with discussions in workshops participated by external experts.
GENERAL OBJECTIVE
The goal of the AICHAIN solution is to enhance –by enabling the secured exploitation of private data with relevant operational value– the performance of the artificial intelligence and machine learning models that are researched and/or used today in the context of air traffic management (ATM) system. In this sense it is expected that, if the access to private data is unlocked to enable its exploitation by current artificial intelligence algorithms, then the network operations and the ATM performance could be significantly improved. In addition, the proposed AICHAIN solution could also potentially enable the design of new SESAR operational improvements (OIs) that could take advantage of the new capabilities to exploit private data that was unavailable in the past.
The ambition of this project is to help in determining –after the project ending and results delivering– whether the proposed AICHAIN solution should be included or not as a potential new SESAR technology enabler to solve the technical and motivational problems identified in the call for projects (topic 04 – DIM) related to the secured exploitation of private data in ATM operations. Therefore, the research of this project has been planned to generate the due qualitative and quantitative evidence required to make such a decision.
The project is positioned as a fundamental oriented (FO) research towards application-oriented (AO) research, targeting the FO/AO maturity gate (TRL1) as defined in the SESAR JU maturity assessment methodology, with the overall expected outcome of delivering a “concept outline and identification of potential benefits and risks”.
SPECIFIC OBJECTIVES
The specific objectives of the research have been structured in three areas of research that will be covered with different levels of deepness: i) the DIM technological solution, ii) the operational value of the DIM solution, and iii) the governance & incentives aspects.
OBJECTIVE #1 (O1): In the technological dimension, to define the AICHAIN Solution architecture as a potential SESAR technology enabler for the exploitation of private data value, and to implement a functional small-scale prototype for user validation and operational value experimentation.
OBJECTIVE #2 (O2): In the operational dimension, to demonstrate and quantify the operational value of the AICHAIN concept with an ATM use case in the area of Advanced Demand Capacity Balancing (A-DCB) services.
OBJECTIVE #3 (O3): In the governance dimension, to develop an incentive mechanism that addresses the motivational aspects of the data owners in order to facilitate the adoption and the effective utilisation of the AICHAIN concept.
