TWINKLE - digital TWIN continuum: a Key enabler for pervasive cyberphysicaL Environments Role: Principal Investigator Affiliation: University of Modena and Reggio Emilia - Department of Sciences and Methods for Engineering
Type: PRIN (Progetti di Ricerca di rilevante Interesse Nazionale)
Link: https://twinkle-project.github.io/ Duration: 2023 - 2025 (24 Months)
Description: Digital Twins are evolving as a versatile paradigm for cyber-physical applications, bridging the physical and digital realms.
Our project aims to develop a new open and distributed DT platform, Digital Twin Continuum (DTC),
focusing on three main research areas: DT As Service, Ecosystems of DT, and Deployment Independence.
Twinkle is a project within the PRIN (Progetti di Ricerca di rilevante Interesse Nazionale) Program 2022 for
Research projects of national interest. The project has been funded by
the European Union - Next Generation EU (Finanziato dall’Unione europea – Next Generation EU).
DATRUST - Connecting the physical and DigitAl worlds through TRUSTworthy data-flows Role: Substitute Principal InvestigatorUnit Coordinator Affiliation: University of Modena and Reggio Emilia - Department of Sciences and Methods for Engineering
Type: PRIN (Progetti di Ricerca di rilevante Interesse Nazionale) - Program PNRR (Piano Nazionale di Ripresa e Resilienza)
Link: https://unipisa.github.io/DATRUST/ Duration: 2023 - 2025 (24 Months)
Description: This project aims to address the challenges and opportunities presented by the increasing use of data in various industrial sectors.
The project focuses on ensuring the trustworthiness of data flows. Key objectives include defining requirements for
Data Flows Trustworthiness, modeling guidelines for new Digital Twins, and implementing a unified computing and networking infrastructure.
Additionally, the project seeks to develop methodologies and algorithms for deploying and maintaining DTs,
ensuring their interaction with physical objects and software services supports reliable data flows.
DATRUST is a project within the PRIN (Progetti di Ricerca di rilevante Interesse Nazionale) Program PNRR (Piano Nazionale di Ripresa e Resilienza) for
Research projects of national interest. The project has been funded by
the European Union - Next Generation EU (Finanziato dall’Unione europea – Next Generation EU).
Sustainable and Orchestrated Digital Twin Ecosystem for Human-Centric Industry 5.0 Role: Principal Investigator Affiliation: University of Modena and Reggio Emilia - Department of Sciences and Methods for Engineering
Type: FAR (Fondo di Ateneo per la Ricerca) 2023 - Progetti Interdisciplinari - University of Modena and Reggio Emilia
Duration: 2023 - 2025 (18 Months)
Description: This project focuses on creating a human-centric industrial ecosystem under the Industry 5.0 paradigm.
It prioritizes worker well-being while enhancing productivity through innovative technologies.
By leveraging Digital Twin (DT) technology, particularly Operator DTs (ODTs), it aims to optimize the interaction between humans and machines.
Objectives include analyzing work-related stress, defining ODTs, developing DT-driven ecosystems, and assessing the impacts of human-in-the-loop applications.
The project has been fundend within the FAR (Fondo di Ateneo per la Ricerca) program of the University of Modena and Reggio Emilia.
EcoMobility: For A Sustainable SocietyWith Intelligent Mobility Solutions Role: Unit-Researcher Affiliation: University of Modena and Reggio Emilia - Department of Sciences and Methods for Engineering
Type: European Project - HORIZON-KDT-JU-2022-2-RIA - Project Id: 101112306
Link: https://www.ecomobility-project.eu/ Duration: 2023 - 2026 (36 Months)
Description: EcoMobility will create and demonstrate an adaptive data-driven development, deployment and operation framework for connected / electric vehicles to enable a digital mobility ecosystem.
The project has received funding within the Chips Joint Undertaking (Chips JU), a public-private partnership in collaboration with the Horizon Europe (HORIZON) Framework Programme and National Authorities under grant agreement number 101112306.
🏢 Industrial Projects
European Telecommunications Standards Institute (ETSI) - STF 628 Role: Unit Coordinator Affiliation: University of Modena and Reggio Emilia - Department of Sciences and Methods for Engineering
Type: ETSI Special Task Force (STF) Project
Link: https://portal.etsi.org/XTFs/#/xTF/628 Duration: 2023 - 2024 (16 Months)
Description: This project aims to standardize Digital Twins within ETSI, leveraging its
strong position in IoT. It seeks to identify use cases, requirements,
and guidelines for cross-domain interoperability and standards.
The goal is to establish uniform communication concepts and reference architectures
for IoT Digital Twins, contributing to ISO/JTC1/SC41 for new specifications.
Ultimately, the project aims to enable the effective adoption of IoT Digital Twins
across various domains while ensuring compatibility with existing standards and functionalities.
Design and Prototyping of IoT Software Architecture for the Fuel Management System Role: Principal Investigator Affiliation: University of Modena and Reggio Emilia - Department of Sciences and Methods for Engineering
Type: Private Company
Duration: 2023 (12 Months)
Description:
The project focuses on designing and prototyping an IoT software architecture tailored for the
Fuel Management System. It emphasizes interoperability and platform development to ensure
seamless communication, management and integration among various components within the system.
Development of a software library for the analysis of OpenStreetMap data Role: Principal Investigator Affiliation: University of Modena and Reggio Emilia - Department of Sciences and Methods for Engineering
Type: Private Company
Duration: 2022 (6 Months)
Description:
The project aims to develop a versatile software library tailored for analyzing OpenStreetMap data.
This endeavor involves comprehensive software development, testing, and experimentation phases.
The library seeks to provide robust tools for extracting insights and information from OpenStreetMap datasets to support mobility applications and integrated data analysis through multiple data sources.
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