The computing continuum aims to break the isolation of edge and cloud computing, creating a smooth and heterogeneous infrastructure surface for deploying applications. However, the continuum is practically fragmented, with infrastructure managed in isolation by various parties in a vertical dimension, i.e., edge, fog, and cloud layers, and horizontally, i.e., computing, network, and storage domains. This scenario negatively impacts the fulfillment of the application objectives. We propose inCoord, an intent-aware solution that enables the creation of a unified computing continuum by coordinating its instances to fulfill application objectives. Each instance represents a cluster of (compute, storage, or network) nodes with their own manager component. Traditionally, systems take low-level actions on these instances. In contrast, inCoord learns their emerging behaviors and adapts their managers’ objectives to fulfill the application’s intents. Here, through a Reinforcement-Learning-based Proof of Concept, we show the potential of this system to understand emerging behavior and manage multi-domain, independently managed instances.

Visual analytics have an important role in the exploration and analysis of large amounts of data in IoT applications. Data visualizations can provide overviews of different aspects of data and user interaction can assist exploration. Recent advances in machine learning and Artificial Intelligence have provided methods that can be used in conjunction with visual analytics to enhance user perception. However, AI methods are often used as "black boxes", making them difficult for end-users to trust. In this paper, a novel visual analytics platform is presented, targeting two goals: a) an architecture for the creation of custom interactive visual analytics dashboards using well-defined components linked to each other, and b) the inclusion of components specifically for making AI methods more explainable. The proposed architecture and components are being used in the context of the AI4IoT pilot within the AI4EU project, which targets air quality monitoring through AI and visualization.

Many service providers (e.g. mobile network operators) want to turn their business into fully digitalised regimes and offer personalised services. To do so they need access to the consumers’ personal data and must explicitly ask consumers for consent. In this cross-national study, including representative samples from seven countries covering Scandinavia, Central-Eastern Europe and South-Eastern Asia, we investigate the effect of trust vs. privacy concerns and the moderating impact of culture when consents are requested. The study shows that trust in service provider has stronger impact on consent giving than privacy concerns, and indicates that ‘digital native’ more than ‘digital immigrant’ providers should focus on trust building activities when they enter countries with an individualistic culture. The analyses were made within a PLS-SEM framework.