To achieve the overall objective of this project, further advancement of current scientific and technical developments is necessary. This global objective can be implemented into the following specific goals of the coordinated project:

O1 To develop an abstract model for Adaptive Smart Areas.

O2 To design and to implement networks of energy efficient IIoT devices to collect all the data that characterize the different internal processes of the models.

O3 To investigate and to develop techniques and methodologies for intelligent interaction, monitorization and distributed and decentralized decision-making as well as the transfer of cognitive and decision-making models between the Cloud and the Edge, including, among others, federated machine learning mechanisms.

O4 To specify a model of Digital Twin to be used to synchronize, to predict and to simulate (even when facing significant changes and/or problems in environment conditions) the behavior of the nodes in the edge level of the system.

O5 To define the different communication protocols allowing to not only coordinate the action of the agents modeling the digital twins, but also allowing to negotiate and share the different resources in the real world that are limited and must be time-restricted shared.

O6 To study and to design new Federated-like learning algorithms allowing a fully distributed and adaptable learning process. These algorithms are intended to be used on the edge level, or in the cloud level, or between both levels.

O7 To develop methods for adaptation of edge-cloud decision making processes in dynamic changing environments.

O8 To analyze ethical and legal aspects of solutions for Adaptive Smart Areas and define a framework for trustworthy AI solutions.

O9 To address some challenges in Adaptive Smart Areas, specifically in rural ones, applying the methods devised for the characteristics and problems found in agriculture-based areas.