It is widely known that we are living through a historic moment in the field of artificial intelligence (AI), capturing the attention of the entire world with spectacular results across multiple application fields, especially in text and image generation.

Artificial intelligence helps coordinate precision agriculture tasks

"Risk and resilience are interconnected concepts. In fact, one of our goals in SUNRISE is to integrate resilience metrics with risk metrics.

In the world of finance, where every decision can have significant ramifications, the possibility of predicting market movements is invaluable. Traditionally, analysts have relied on a combination of data analysis, market trends, and expert insights to make informed predictions.

The CROSSCON is a research project that targets developing research ideas into practical techniques and supporting prototypes, and the level of ambition is to validate results in lab conditions that are representative of a complex IoT system (i.e., technology readiness levels TRL 4 and TRL5).

The increasing development of cryptocurrencies has brought cryptojacking as a new security threat in which attackers steal computing resources for cryptomining.

In recent years, the development and refinement of artificial intelligence (AI) technologies have revolutionised various fields, including computer vision.

The full deployment of sixth-generation (6G) networks is inextricably connected with a holistic network redesign able to deal with various emerging challenges, such as integration of heterogeneous technologies and devices, as well as support of latency and bandwidth demanding applications.

As the global population is expected to reach 10 billion by 2050, the agricultural sector faces the challenge of achieving an increase of 60% in food production without using much more land.

Self-Sovereign Identity can be considered as the most significant paradigm shift, surpassing the more established centralised and federated approaches that have shaped identity management in the past decades.

Cloud and edge computing are essential technologies in a computing continuum to ensure data is managed more efficiently – closer to the originating source rather than transmitting raw data to data centres. As recent studies suggest, data processing is moving closer to the edge.

Following the Industry 4.0 vision of a full digitization of the industry, time-critical services and applications, allowing network infrastructures to deliver information with determinism and reliability, are becoming more and more relevant for a set of vertical sectors.

Due to its multivariate and multipurpose use and reuse, data’s worth is dramatically increasing, leading to an era characterized by the generation of data marketplaces towards accessing, selling, sharing, and trading data and data assets.

A proposal for a predictive analysis model for bike-sharing systems based on a mixed model of statistical and machine-learning approaches.The model assumes a Poisson distribution on bike station arrival and departures.

A trend in future networks (i.e., beyond 5G and 6G) is the increasing virtualization and disaggregation of networks (i.e., Open Radio Access Network, network function virtulization/software-defined networking, or disaggregated optical networks, among others).

Network Applications is seen as a full-potential enabler for future vertical industries beyond current deployment. Therefore, it must be considered along with other 6G enabling technologies in the next-generation network architecture.