Mapping Cloud-Edge-IoT opportunities and challenges in Europe

While current data processing predominantly occurs in centralized facilities, with a minor portion handled by smart objects, a shift is anticipated, with a surge in data originating from smart devices. This evolution necessitates reconfiguring the infrastructure, emphasising computing capabilities at the cloud's "edge" closer to data sources. This change symbolises the merging of cloud, edge, and IoT technologies into a unified network infrastructure - a Computing Continuum - poised to redefine tech interactions, offering novel prospects across diverse sectors. The computing continuum is emerging as a cornerstone of tech advancement in the contemporary digital era. This paper provides an in-depth exploration of the computing continuum, highlighting its potential, practical implications, and the adjustments required to tackle existing challenges. It emphasises the continuum's real-world applications, market trends, and its significance in shaping Europe's tech future

Advancing Towards the Cloud, Edge and IoT Continuum: Insights and Impacts

Advancing towards the Cloud, Edge, and IoT Continuum: Insights and Impacts” was an online event organised by UNLOCK-CEI as part of the EUCloudEdgeIoT (EUCEI) initiative. EUCEI is a collaborative effort to foster advancements in cloud, edge computing, and the Internet of Things (IoT) technologies within the European Union. This initiative is coordinated by UNLOCK-CEI and Open Continuum projects, respectively, focused on the demand and supply sides of the computing continuum. The initiative brings together experts, industry leaders, and researchers to drive innovation and explore the potential of these emerging fields

Visibility in Information Spaces and in Geographic Environments. Post-Proceedings of the KI'11 Workshop (October 4th, 2011, TU Berlin, Germany)

In the post-proceedings of the Workshop "Visibility in Information Spaces and in Geographic Environments" a selection of research papers is presented where the topic of visibility is addressed in different contexts. Visibility governs information selection in geographic environments as well as in information spaces and in cognition. The users of social media navigate in information spaces and at the same time, as embodied agents, they move in geographic environments. Both activities follow a similar type of information economy in which decisions by individuals or groups require a highly selective filtering to avoid information overload. In this context, visibility refers to the fact that in social processes some actors, topics or places are more salient than others. Formal notions of visibility include the centrality measures from social network analysis or the plethora of web page ranking methods. Recently, comparable approaches have been proposed to analyse activities in geographic environments: Place Rank, for instance, describes the social visibility of urban places based on the temporal sequence of tourist visit patterns. The workshop aimed to bring together researchers from AI, Geographic Information Science, Cognitive Science, and other disciplines who are interested in understanding how the different forms of visibility in information spaces and geographic environments relate to one another and how the results from basic research can be used to improve spatial search engines, geo-recommender systems or location-based social networks

AI at the Edge, 2021 EPoSS White Paper

In this paper members of the European Platform on Smart Systems Integration (EPoSS) have collected their views on the benefits of incorporating Artificial Intelligence in future Smart devices and defined the actions required to achieve this to implement "AI at the Edge"

“First Have a Plan then Make Sure It Is a Good Plan ” or Dealing with Underspecified Spatio-Temporal Relations in Unfamiliar Large-Scale Environments

Abstract. This paper introduces an approach for dealing with underspecified spatial and temporal relations during early stage spatio-temporal planning in large-scale unfamiliar environments. For that purpose a partial spatio-temporal constraint satisfaction algorithm is introduced. The algorithm operates on a qualitative as well as metric representation of the given spatio-temporal relations. In order to reduce the computational complexity structuring criteria of the problem space are introduced. The paper outlines procedures for handling of overspecified spatio-temporal relations by removing of location assignments or fixed points in time, or shortening durations of events under consideration of the corresponding priorities. The algorithm concludes with ordering procedure for events with no temporal order but specified spatial assignments. The alternative spatial locations for events with underspecified spatial assignment are represented using a qualitative distance scheme or region-based mapping to the environment structure