Software Infrastructure – Multimodal Data Fusion and Analytics Group

MaaSAI

MaaSAI MaaSAI | Agile Manufacturing as a Service through AI Autonomous Agents The goal of the project is the creation of the MaaSAI System, a comprehensive digital system to automate and facilitate interactions between suppliers of manufacturing systems (Providers) and manufacturing companies (Consumers) in a Manufacturing-as-a-Service (MaaS) ecosystem, in an agile, efficient, and transparent manner. The MaaSAI System aims to revolutionise manufacturing and remanufacturing processes by facilitating access to flexible and decentralised capacities, through the MaaS business model, which extends the principles of the service-oriented economy to the manufacturing industry. The MaaSAI System aims to contribute to the reduction of the heavy investments that manufacturers have traditionally had to make to set up and maintain their operations. With an emphasis on production flexibility, agility, and responsiveness, the MaaSAI System enables…

HYPER-AI

HYPER-AI Hyper-Distributed Artificial Intelligence Platform for Network Resources Automation and Management Towards More Efficient Data Processing Applications HYPER-AI overarching objective is the development of the required mid-tier and the necessary cloud-edge connectors that will enable the seamless integration of heterogeneous computing environments and the establishment of new-generation interoperable and adaptive hybrid computing ecosystems exploiting cognitive clouds and edge intelligence beyond today’s limitations. HYPER-AI objectives are listed as follows: Design and implement the HYPER-AI open architecture that will empower swarms of nodes to develop collaboratively collective intelligence, bringing the computation closer to the edge, utilizing decentralized AI/ML-based intelligence. Ensure dynamic cognitive and informative optimized decision-making across all phases of the application lifecycle (design, execution, maintenance) through continuous inference resources. Develop autonomic system entities ensuring autonomous Smart-Nodes and rapid coordination of Smart-Nodes…

CYCLOPS

CYCLOPS Automated end-to-end data life cycle management for FAIR data integration, processing and re-use The CYCLOPS project is dedicated to advancing data integration and management across diverse and evolving data sources. It directly aligns with the European Strategy for Data, aiming to cultivate a cohesive data market. CYCLOPS sets its sights on pivotal future EU data spaces: tourism and mobility, the green deal, public procurement, and manufacturing. These four (4) thematic areas form the core of CYCLOPS's mission to establish a groundbreaking framework for the comprehensive governance of the data lifecycle. Through the application of Artificial Intelligence (AI) in Artificial Intelligence Operations (AIOps) and Data Operations (DataOps), augmented by Knowledge Graphs (KGs) and a human-in-the-loop approach, CYCLOPS strives to automate data processing pipelines. This approach is designed to eliminate data…

RAISE

RAISE Research Analysis Identifier SystEm The EU-funded RAISE project aims to address the challenge of an open, fair and reliable Research Community, where every researcher will be accredited for its work and all research data will be equally accessible for processing without violating data protection regulations. RAISE vision is to provide the infrastructure for a distributed crowdsourced data processing system, moving from open data to open access data for processing. RAISE will produce the mechanism for sending the algorithm to the dataset instead of sending the data to the algorithm. The success of such an application will provide to users a transparent way of processing and sharing data, enabling the research community to publish their outcomes with evidence-based authenticity of the data-analysis performed, ensuring at the same time the accreditation…

SODALITE

SODALITE SOftware Defined AppLication Infrastructures managemenT and Engineering SODALITE (SOftware Defined AppLication Infrastructures managemenT and Engineering) is aimed at tackling the complexity of deploying and operating modern applications onto heterogeneous HPC and cloud-based software-defined infrastructures, under arbitrary operational conditions and requirements. This challenge is addressed through (a) the abstraction of the application and software-defined infrastructures, (b) the automation of maintaining a dynamic balance between the application and the infrastructure, and (c) the design and runtime analysis of software-defined infrastructures. The novelty of the SODALITE’s approach lies in developing and using an application, infrastructure, and performance abstraction library to enable dynamically optimized multi-target application execution via an optimal mixture of Cloud, HPC, GPUs, FPGAs, etc., based on the requirements of the application itself and the dynamic state of the infrastructure. Further…