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Projects

Ongoing Projects

HPCLAB is currently participating in the following research  projects.

ACCORDION (H2020 RIA 2020-2023 contract N. 871793) aspires to support the enlargement of the edge resource & infrastructure pool so as to cover morgeographies and users, thus truly enabling ubiquitous and collaborative applications that will benefit from the edge computing offerings.

A system will be created, called ACCORDION system, that will address the needs of both NextGen application developers and local infrastructure owners, and will encompass frameworks for application development, establishment of an adaptive and robust cloud/edge infrastructure continuum, and the abstraction of widely heterogeneous pools.

MASTER (H2020-MSCA-RISE-2017 2018-2022 – contract N. 777695) is a EC funded under the H2020 Marie-Slodowska Curie actions as the RISE funding scheme. The objective is to  form an international and inter-sectoral network of organisations working on a joint research programme to define new methods to build, manage and analyse multiple aspects semantic trajectories.  We propose methods to analyze and infer knowledge from multiple aspects trajectories, considering as vital issues the privacy and big data dimensions.

HPC Lab is the coordinator of the project and its main role is in developing efficient methods for trajectories representation, management and analysis.

SoBigData++ (H2020 RI, 2020-2023 contract N. 871042) strives to deliver a distributed, Pan-European, multi-disciplinary research infrastructure for big social data analytics, coupled with the consolidation of a cross-disciplinary European research community, aimed at using social mining and big data to understand the complexity of our contemporary, globally-interconnected society. Becoming an advanced community, SoBigData++ will strengthen its tools and services to empower researchers and innovators through a platform for the design and execution of large-scale social mining experiments. It will be open to users with diverse background, accessible on project cloud (aligned with EOSC) and also exploiting supercomputing facilities.

NAVIGATOR aims to boost precision medicine in oncology by advancing translational research based on quantitative imaging and multi-omics analyses, towards a better understanding of cancer biology, cancer care, and, more generally, cancer risk.

NAVIGATOR relies on a strong regional network of Hospitals and University hospitals and Research Institutions in Pisa, Florence, and Siena, which have partnered with European universities (i.e., Cambridge and Bournemouth) to grant an international grounding of the work. ISTI-CNR plays a key role in the project, as the three Labs involved (i.e., NeMIS, HPC, and SI) will lead the design and deployment of the Virtual Research Environment as well as of the AI algorithms for the Radiomics analyses.

MobiDataLab (2021-2023, funded by the EU under the H2020 Research and Innovation Programme – Grant Agreement No 101006879). ) is the EU-funded lab for prototyping new mobility data sharing solutions. The aim is to foster data sharing in the transport sector, providing mobility organising authorities with recommendations on how to improve the value of their data, contributing to the development of open tools in the cloud, and organising hackathons aiming to find innovative solutions to concrete mobility problems.

HPC is participating in MobiDatalab contributing to the Cloud federation for Transport Cloud and the semantic enrichment of mobility data.

EV-CHIP (2019-2021 ERA-NET) Electric Vehicles Charging Platform for Community Demand Response Aggregators. The objective of the EVCHIP project is to explore and validate a business model for realising the commercial value of EV charging services aggregation. In doing so, the project team aims to create a replicable, enduring modelling capacity within the participating institutions, and to produce scalable prototype software for the integration of electric transportation in the power grid.The project research goals are the assessment of a standard methodology to evaluate the impact of electric vehicles charging point at the distribution level and the validation of a real-time predictive algorithm for the bi-directional charging power management of the charging stations.

HPCLab participates in EV-CHIP for the development of a machine learning approach for parking prediction.

CHARITY (H2020 RIA, G.A. No 101016509) aspires to leverage the benefits of intelligent, autonomous orchestration of cloud, edge, and network resources, to create a symbiotic relationship between low and high latency infrastructures that will facilitate the needs of emerging applications.

TEACHING (H2020 RIA 2020 – 2022 contract N. 871385) addresses the challenge by integrating AI with fundamental concepts of security and dependability stemming from the AI-human-CPSoS interactions, as well as by considering their impact on the underlying computing system. TEACHING develops a human-aware CPSoS for autonomous safety-critical applications, based on a distributed, energy-efficient and dependable AI, leveraging edge computing platforms, and integrating specialized computing fabric for AI and in-silico support for intelligent cybersecurity.

HPCLab leads WP2 (Distributed Computing and Communication platform for CPSoS) and is responsible of the innovation coordination for the whole project.

HPCLAB is also involved in the National project OK-INSAID (Operational Knowledge from Insights and Analytics on Industrial Data, PON e FSC – Fabbrica Intelligente – n. ARS01_00917) funded by the Ministero dell’Istruzione, Università e Ricerca (MIUR).

OK-INSAID offers scientific, technological and application innovation thanks to the introduction of Big Data Analytics in the industrial context, helping to redesign production processes and business models, to obtain, thanks to data and analytics, a change of pace in creation of digital services for the industrial sector.

OK-INSAID also proposes a new approach to analytics, based on the coordination, collaboration and synchronization of existing ones at the cloud and edge levels. This approach will be supported by the adoption of a reference architecture and its implementation, aimed at developing new “cloud-edge” hybrid analytics for Industry 4.0.

Recent Projects

Some of the projects recently concluded are listed below

The BigDataGrapes project (H2020 PPP RIA, 2018-2021 contract N. 780751)  aimed at building knowledge and methodologies to support companies in the grapevine industry.

SoBigData (H2020 RI, 2016-2019 contract N. 654024)  designed the Social Mining & Big Data Research Infrastructure

BASMATI (H2020 ICT-EU-Korea). Contract n. 723131. Cloud Brokerage Across Borders for Mobile Users and Applications BASMATI (2016-2018)

LIGA, Large-scale Indie Gaming Analytics. Contract n. 680481. Experiment of Fortissimo 2 H2020 project, (2016-2018)

InGeoClouds project (CIP-ICT-PSP-2011-5). Contract No 297300. The INspired GEOdata CLOUD Services (INGEOCLOUDS) (2012-2014)

 

Past Projects