2026
Conference article
Open Access
Advancements in Artificial Intelligence and Computer Vision for Biomedical Applications @SI-Lab
Marco Cafiso, Andrea Carboni, Claudia Caudai, Sara Colantonio, Francesco Conti, Mario D’acunto, Said Daoudagh, Giulio Del Corso, Riccardo Del Gratta, Danila Germanese, Giacomo Ignesti, Gianmarco Lazzini, Giuseppe Riccardo Leone, Barbara Leporini, Massimo Magrini, Massimo Martinelli, Davide Moroni, Ali Reza Omrani, Francesca Pardini, Maria Antonietta Pascali, Paolo Paradisi, Laura Sebastiaini, Marco Tampucci, Valeria Tateo, Federico Volpini
This paper summarizes recent research at the Signals and Images Lab (ISTI-CNR) leveraging artificial intelligence, machine learning, and computer vision to address complex biomedical challenges. We highlight advancements in trustworthy, explainable algorithmic foundations alongside their practical clinical applications across diagnostic imaging, physiological signal analysis and neuromotor rehabilitation.
Marco Cafiso, Andrea Carboni, Claudia Caudai, Sara Colantonio, Francesco Conti, Mario D’acunto, Said Daoudagh, Giulio Del Corso, Riccardo Del Gratta, Danila Germanese, Giacomo Ignesti, Gianmarco Lazzini, Giuseppe Riccardo Leone, Barbara Leporini, Massimo Magrini, Massimo Martinelli, Davide Moroni, Ali Reza Omrani, Francesca Pardini, Maria Antonietta Pascali, Paolo Paradisi, Laura Sebastiaini, Marco Tampucci, Valeria Tateo, Federico Volpini
This paper summarizes recent research at the Signals and Images Lab (ISTI-CNR) leveraging artificial intelligence, machine learning, and computer vision to address complex biomedical challenges. We highlight advancements in trustworthy, explainable algorithmic foundations alongside their practical clinical applications across diagnostic imaging, physiological signal analysis and neuromotor rehabilitation.
2025
Other
Open Access
SI-Lab Annual Research Report 2024
Awais Ch Muhammad, Baiamonte A., Benassi A., Berti A., Bertini G., Buongiorno R, Bulotta D., Cafiso M., Carboni A., Carloni G., Caudai C., Colantonio S., Conti F., Daoudagh S., Del Corso G., Fusco G., Galesi G., Germanese D., Gravili S., Ignesti G., Kuruoglu E. E., Lazzini G., Leone G. R., Leporini B., Magrini M., Martinelli M., Omrani Ali Reza, Pachetti E., Papini O., Paradisi P., Pardini F., Pascali M. A., Pieri G., Reggiannini M., Righi M., Salerno E., Salvetti O., Scozzari A., Sebastiani L., Straface S., Tampucci M., Tarabella L., Tonazzini A., Moroni D.
The Signal & Images Laboratory (SI-Lab) is an interdisciplinary research group in computer vision, signal analysis, intelligent vision systems and multimedia data understanding. It is part of the Institute of Information Science and Technologies (ISTI) of the National Research Council of Italy (CNR). This report accounts for the research activities of the Signal and Images Laboratory of the Institute of Information Science and Technologies during the year 2024.DOI: 10.32079/isti-ar-2025/002
Metrics:
Awais Ch Muhammad, Baiamonte A., Benassi A., Berti A., Bertini G., Buongiorno R, Bulotta D., Cafiso M., Carboni A., Carloni G., Caudai C., Colantonio S., Conti F., Daoudagh S., Del Corso G., Fusco G., Galesi G., Germanese D., Gravili S., Ignesti G., Kuruoglu E. E., Lazzini G., Leone G. R., Leporini B., Magrini M., Martinelli M., Omrani Ali Reza, Pachetti E., Papini O., Paradisi P., Pardini F., Pascali M. A., Pieri G., Reggiannini M., Righi M., Salerno E., Salvetti O., Scozzari A., Sebastiani L., Straface S., Tampucci M., Tarabella L., Tonazzini A., Moroni D.
The Signal & Images Laboratory (SI-Lab) is an interdisciplinary research group in computer vision, signal analysis, intelligent vision systems and multimedia data understanding. It is part of the Institute of Information Science and Technologies (ISTI) of the National Research Council of Italy (CNR). This report accounts for the research activities of the Signal and Images Laboratory of the Institute of Information Science and Technologies during the year 2024.DOI: 10.32079/isti-ar-2025/002
Metrics:
2025
Journal article
Restricted
NAVIGATOR: a regional multimodal imaging biobank initiative powered by AI tools for precision medicine in oncology
Aghakhanyan G., Barucci A., Pascali M. A., Assante M., Bagnacci G., Bertelli E., Caputo F. P., Cuibari M. E., Carlini E., Carpi R., Caudai C., Cioni D., Colantonio S., Colcelli V., Dell'Amico A., Vecchio V. D., Gangi D. D., Faggioni L., Formica V., Francischello R., Frosini L., Kotsa C., Lipari G., Manghi P., Martino V. D., Marzi C., Mazzei M. A., Mangiacrapa F., Meglio N. D., Miele V., Molinaro E., Paiar F., Pagano P., Panichi G., Pasquinelli F., Peccerillo B., Perrella A., Piccioli T., Oliviero A., Olivoni M., Rucci D., Tampucci M., Tumminello L., Volpini F., Zanuzzi A., Fanni S. C., Neri E.
The NAVIGATOR project established an Italian regional imaging biobank and interactive research platform designed to support precision oncology through the integration of multimodal imaging, clinical, and omics data. The platform goes beyond a static repository, offering a secure Virtual Research Environment (VRE) where users can upload data, test AI algorithms, and execute complete analytical pipelines. The platform incorporates artificial intelligence (AI)-driven radiomics and deep learning methodologies to enable biomarker extraction, disease stratification, and predictive modeling. This manuscript presents the development and implementation of the NAVIGATOR infrastructure, including its data governance framework, ethical and legal considerations, and application to three oncological use cases: prostate, rectal, and gastric cancers. To date, the biobank has collected imaging and clinical data from over 700 patients across these cohorts. AI models were deployed within a dedicated VRE to facilitate image analysis, feature extraction, and classification tasks. The project addresses critical challenges related to data harmonization, regulatory compliance, privacy safeguards and fairness in AI systems. NAVIGATOR demonstrates the feasibility of integrating AI methodologies within imaging biobanks and provides a scalable framework to advance oncological research and support clinical decision-making.Source: EUROPEAN JOURNAL OF RADIOLOGY, vol. 191 (issue 112327)
DOI: 10.1016/j.ejrad.2025.112327
Project(s): An Imaging Biobank to Precisely Prevent and Predict cancer, and facilitate the Participation of oncologic patients to Diagnosis and Treatment
Metrics:
Aghakhanyan G., Barucci A., Pascali M. A., Assante M., Bagnacci G., Bertelli E., Caputo F. P., Cuibari M. E., Carlini E., Carpi R., Caudai C., Cioni D., Colantonio S., Colcelli V., Dell'Amico A., Vecchio V. D., Gangi D. D., Faggioni L., Formica V., Francischello R., Frosini L., Kotsa C., Lipari G., Manghi P., Martino V. D., Marzi C., Mazzei M. A., Mangiacrapa F., Meglio N. D., Miele V., Molinaro E., Paiar F., Pagano P., Panichi G., Pasquinelli F., Peccerillo B., Perrella A., Piccioli T., Oliviero A., Olivoni M., Rucci D., Tampucci M., Tumminello L., Volpini F., Zanuzzi A., Fanni S. C., Neri E.
The NAVIGATOR project established an Italian regional imaging biobank and interactive research platform designed to support precision oncology through the integration of multimodal imaging, clinical, and omics data. The platform goes beyond a static repository, offering a secure Virtual Research Environment (VRE) where users can upload data, test AI algorithms, and execute complete analytical pipelines. The platform incorporates artificial intelligence (AI)-driven radiomics and deep learning methodologies to enable biomarker extraction, disease stratification, and predictive modeling. This manuscript presents the development and implementation of the NAVIGATOR infrastructure, including its data governance framework, ethical and legal considerations, and application to three oncological use cases: prostate, rectal, and gastric cancers. To date, the biobank has collected imaging and clinical data from over 700 patients across these cohorts. AI models were deployed within a dedicated VRE to facilitate image analysis, feature extraction, and classification tasks. The project addresses critical challenges related to data harmonization, regulatory compliance, privacy safeguards and fairness in AI systems. NAVIGATOR demonstrates the feasibility of integrating AI methodologies within imaging biobanks and provides a scalable framework to advance oncological research and support clinical decision-making.Source: EUROPEAN JOURNAL OF RADIOLOGY, vol. 191 (issue 112327)
DOI: 10.1016/j.ejrad.2025.112327
Project(s): An Imaging Biobank to Precisely Prevent and Predict cancer, and facilitate the Participation of oncologic patients to Diagnosis and Treatment
Metrics:
See at:
European Journal of Radiology 
| Archivio della Ricerca - Università di Pisa | CNR IRIS | CNR IRIS | Archivio della Ricerca - Università di Pisa
2024
Journal article
Open Access
Remote sensing for maritime traffic understanding
Reggiannini M, Salerno E, Bacciu C, D'Errico A, Lo Duca A, Marchetti A, Martinelli M, Mercurio C, Mistretta A, Righi M, Tampucci M, Di Paola C
The capability of prompt response in case of critical circumstances occurring within a maritime scenario depends on the awareness level of the competent authorities. From this perspective a quick and integrated surveillance service represents a tool of utmost importance. This is even more true when the main purpose is to tackle illegal activities such as smuggling, waste flooding or malicious vessel trafficking. This work presents an improved version of the OSIRIS system, a previously developed ICT framework devoted to understand the maritime vessel traffic through the exploitation of optical and radar data captured by satellite imaging sensors. A number of dedicated processing units are cascaded with the objective of i) detecting the presence of vessel targets in the input imagery, ii) estimating the vessel types on the basis of their geometric and scatterometric features, iii) estimating the vessel kinematics, iv) classifying the navigation behaviour of the vessel and predicting its route and, eventually, v) integrating the several outcomes within a webGIS interface to easily assess the traffic status inside the considered area. The entire processing pipeline has been tested on satellite imagery captured within the Mediterranean Sea or extracted from public, annotated data sets.Source: REMOTE SENSING (BASEL), vol. 16 (issue 3)
DOI: 10.3390/rs16030557
Metrics:
Reggiannini M, Salerno E, Bacciu C, D'Errico A, Lo Duca A, Marchetti A, Martinelli M, Mercurio C, Mistretta A, Righi M, Tampucci M, Di Paola C
The capability of prompt response in case of critical circumstances occurring within a maritime scenario depends on the awareness level of the competent authorities. From this perspective a quick and integrated surveillance service represents a tool of utmost importance. This is even more true when the main purpose is to tackle illegal activities such as smuggling, waste flooding or malicious vessel trafficking. This work presents an improved version of the OSIRIS system, a previously developed ICT framework devoted to understand the maritime vessel traffic through the exploitation of optical and radar data captured by satellite imaging sensors. A number of dedicated processing units are cascaded with the objective of i) detecting the presence of vessel targets in the input imagery, ii) estimating the vessel types on the basis of their geometric and scatterometric features, iii) estimating the vessel kinematics, iv) classifying the navigation behaviour of the vessel and predicting its route and, eventually, v) integrating the several outcomes within a webGIS interface to easily assess the traffic status inside the considered area. The entire processing pipeline has been tested on satellite imagery captured within the Mediterranean Sea or extracted from public, annotated data sets.Source: REMOTE SENSING (BASEL), vol. 16 (issue 3)
DOI: 10.3390/rs16030557
Metrics:
See at:
Remote Sensing 
| Remote Sensing | IRIS Cnr | IRIS Cnr | CNR IRIS | CNR IRIS
2024
Conference article
Open Access
Advancing sustainability: research initiatives at the Signals and Images Lab
Bruno A., Caudai C., Conti F., Leone G. R., Magrini M., Martinelli M., Moroni D., Muhammad A. Ch, Papini O., Pascali M. A., Pieri G., Reggiannini M., Righi M., Salerno E., Scozzari A., Tampucci M.
In this paper, we aim to briefly survey the relations of the work conducted at the Signals and Images Lab of CNR-ISTI, Pisa, with the themes of sustainability. We explore both the broader implications and the application-specific aspects of our work, highlighting references to published research and collaborative projects undertaken with key stakeholders and industrial partners.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3762, pp. 499-504. Napoli, Italy, 29-30/05/2024
Bruno A., Caudai C., Conti F., Leone G. R., Magrini M., Martinelli M., Moroni D., Muhammad A. Ch, Papini O., Pascali M. A., Pieri G., Reggiannini M., Righi M., Salerno E., Scozzari A., Tampucci M.
In this paper, we aim to briefly survey the relations of the work conducted at the Signals and Images Lab of CNR-ISTI, Pisa, with the themes of sustainability. We explore both the broader implications and the application-specific aspects of our work, highlighting references to published research and collaborative projects undertaken with key stakeholders and industrial partners.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3762, pp. 499-504. Napoli, Italy, 29-30/05/2024
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2024
Conference article
Open Access
NAUTILOS Data Management Infrastructure
Pieri G., Tampucci M., Volpini F., Alba M., Misurale F., Novellino A.
NAUTILOS Project is an H2020 project devoted to fill-in marine observation and modelling gaps for chemical, biological and deep ocean physics variables through the development of a new generation of cost-effective sensors and samplers. Its infrastructure is organized with a data layer designed to manage data and data products, a service layer to organize them to offer the services, and an application layer i.e., the end-user interface (and features) to access and use the developed and provided services.Source: MISCELLANEA INGV, vol. 80, pp. 344-346. Bergen, Norvegia, 27-29/05/2024
DOI: 10.13127/misc/80/132
DOI: https://commons.datacite.org/doi.org/10.13127/misc/80/132
Project(s): NAUTILOS
Metrics:
Pieri G., Tampucci M., Volpini F., Alba M., Misurale F., Novellino A.
NAUTILOS Project is an H2020 project devoted to fill-in marine observation and modelling gaps for chemical, biological and deep ocean physics variables through the development of a new generation of cost-effective sensors and samplers. Its infrastructure is organized with a data layer designed to manage data and data products, a service layer to organize them to offer the services, and an application layer i.e., the end-user interface (and features) to access and use the developed and provided services.Source: MISCELLANEA INGV, vol. 80, pp. 344-346. Bergen, Norvegia, 27-29/05/2024
DOI: 10.13127/misc/80/132
DOI: https://commons.datacite.org/doi.org/10.13127/misc/80/132
Project(s): NAUTILOS
Metrics:
2024
Other
Open Access
NAUTILOS Citizen Science App
Tampucci M., Chatzinikolaou E., Keklikoglou K., Pieri G.
NAUTILOS application is a tool able to send reports, resulting from the campaigns, to a dedicated Erddap data server through a set of HTTP services.Source: MISCELLANEA INGV, vol. 80. Bergen, Norvegia, 27-29/05/2024
Project(s): NAUTILOS
Tampucci M., Chatzinikolaou E., Keklikoglou K., Pieri G.
NAUTILOS application is a tool able to send reports, resulting from the campaigns, to a dedicated Erddap data server through a set of HTTP services.Source: MISCELLANEA INGV, vol. 80. Bergen, Norvegia, 27-29/05/2024
Project(s): NAUTILOS
See at:
CNR IRIS | share.ifremer.fr | CNR IRIS
2024
Conference article
Open Access
NAUTILOS Citizen Science App
Tampucci M., Chatzinikolaou E., Keklikoglou K., Pieri G.
Citizen Science projects including crowd sourcing of plastic litter data have been implemented successfully in many countries and within several long term monitoring projects. The involvement of local communities in the collection of data gives them the opportunity to actively participate in the problem’s solution and has the potential to raise environmental awareness. Within NAUTILOS Project, many different partners are involved in Citizen Science (CS) campaigns. Each one does not necessarily perform the same type of activities or focus on the same kind of citizens or citizens organisations. The primary goal of this activity is to develop an App which can support various CS activities arranged by different partners in the NAUTILOS project and with different focuses.Source: MISCELLANEA INGV, vol. 80, pp. 349-351. Bergen, Norvegia, 27-29/05/2024
DOI: 10.13127/misc/80/134
DOI: https://commons.datacite.org/doi.org/10.13127/misc/80/134
Project(s): NAUTILOS
Metrics:
Tampucci M., Chatzinikolaou E., Keklikoglou K., Pieri G.
Citizen Science projects including crowd sourcing of plastic litter data have been implemented successfully in many countries and within several long term monitoring projects. The involvement of local communities in the collection of data gives them the opportunity to actively participate in the problem’s solution and has the potential to raise environmental awareness. Within NAUTILOS Project, many different partners are involved in Citizen Science (CS) campaigns. Each one does not necessarily perform the same type of activities or focus on the same kind of citizens or citizens organisations. The primary goal of this activity is to develop an App which can support various CS activities arranged by different partners in the NAUTILOS project and with different focuses.Source: MISCELLANEA INGV, vol. 80, pp. 349-351. Bergen, Norvegia, 27-29/05/2024
DOI: 10.13127/misc/80/134
DOI: https://commons.datacite.org/doi.org/10.13127/misc/80/134
Project(s): NAUTILOS
Metrics:
2024
Other
Open Access
NAUTILOS Data Management Infrastructure
Pieri G., Tampucci M., Volpini F., Alba M., Misurale F., Novellino A.
NAUTILOS Project is an H2020 project devoted to fill-in marine observation and modelling gaps for chemical, biological and deep ocean physics variables through the development of a new generation of cost-effective sensors and samplers. Its infrastructure is organized with a data layer designed to manage data and data products, a service layer to organize them to offer the services, and an application layer i.e., the end-user interface (and features) to access and use the developed and provided services.Source: MISCELLANEA INGV, vol. 80. Bergen (Norway), 27-29/05/2024
Project(s): NAUTILOS
Pieri G., Tampucci M., Volpini F., Alba M., Misurale F., Novellino A.
NAUTILOS Project is an H2020 project devoted to fill-in marine observation and modelling gaps for chemical, biological and deep ocean physics variables through the development of a new generation of cost-effective sensors and samplers. Its infrastructure is organized with a data layer designed to manage data and data products, a service layer to organize them to offer the services, and an application layer i.e., the end-user interface (and features) to access and use the developed and provided services.Source: MISCELLANEA INGV, vol. 80. Bergen (Norway), 27-29/05/2024
Project(s): NAUTILOS
See at:
CNR IRIS | share.ifremer.fr | CNR IRIS
2023
Conference article
Restricted
Anoressia Nervosa, percezione dell'immagine corporea e applicazioni terapeutiche della realtà virtuale: una revisione sistematica di letteratura, stato dell'arte e proposte operative
Curzio O., Tampucci M., Maestro S., Donzelli G., Moroni D., Cori L., Imiotti M. C., Magrini M.
Le pazienti affette da anoressia nervosa (AN) evidenziano rappresentazioni corporee distorte legate a problemi percettivi e cognitivo-emotivi. L'AN è una condizione che colpisce principalmente gli adolescenti ed è più frequente nelle donne; contribuisce a disfunzioni psicologiche e biologiche. La prevalenza nell'arco della vita dell'AN negli adulti è di circa lo 0,6% (0,9% nelle donne e 0,3% nei maschi). Le indagini neuropsicologiche hanno rilevato una compromissione in diversi ambiti: capacità visuo-spaziali ed empatiche, funzionamento esecutivo. Potrebbero essere di utilità paradigmi sperimentali per interagire con il contenuto spaziale ed emotivo di queste così specifiche rappresentazioni corporee. La tecnologia della realtà virtuale (VR) sembra rivelarsi utile nell'applicazione clinica.
Curzio O., Tampucci M., Maestro S., Donzelli G., Moroni D., Cori L., Imiotti M. C., Magrini M.
Le pazienti affette da anoressia nervosa (AN) evidenziano rappresentazioni corporee distorte legate a problemi percettivi e cognitivo-emotivi. L'AN è una condizione che colpisce principalmente gli adolescenti ed è più frequente nelle donne; contribuisce a disfunzioni psicologiche e biologiche. La prevalenza nell'arco della vita dell'AN negli adulti è di circa lo 0,6% (0,9% nelle donne e 0,3% nei maschi). Le indagini neuropsicologiche hanno rilevato una compromissione in diversi ambiti: capacità visuo-spaziali ed empatiche, funzionamento esecutivo. Potrebbero essere di utilità paradigmi sperimentali per interagire con il contenuto spaziale ed emotivo di queste così specifiche rappresentazioni corporee. La tecnologia della realtà virtuale (VR) sembra rivelarsi utile nell'applicazione clinica.
2022
Conference article
Open Access
Augmented reality, artificial intelligence and machine learning in Industry 4.0: case studies at SI-Lab
Bruno A, Coscetti S, Leone Gr, Germanese D, Magrini M, Martinelli M, Moroni D, Pascali Ma, Pieri G, Reggiannini M, Tampucci M
In recent years, the impressive advances in artificial intelligence, computer vision, pervasive computing, and augmented reality made them rise to pillars of the fourth industrial revolution. This short paper aims to provide a brief survey of current use cases in factory applications and industrial inspection under active development at the Signals and Images Lab, ISTI-CNR, Pisa.DOI: 10.5281/zenodo.6322733
Metrics:
Bruno A, Coscetti S, Leone Gr, Germanese D, Magrini M, Martinelli M, Moroni D, Pascali Ma, Pieri G, Reggiannini M, Tampucci M
In recent years, the impressive advances in artificial intelligence, computer vision, pervasive computing, and augmented reality made them rise to pillars of the fourth industrial revolution. This short paper aims to provide a brief survey of current use cases in factory applications and industrial inspection under active development at the Signals and Images Lab, ISTI-CNR, Pisa.DOI: 10.5281/zenodo.6322733
Metrics:
See at:
CNR IRIS | ISTI Repository | www.ital-ia2022.it | CNR IRIS
2022
Journal article
Open Access
Anorexia nervosa, body image perception and virtual reality therapeutic applications: state of the art and operational proposal
Magrini M, Curzio O, Tampucci M, Donzelli G, Cori L, Imiotti Mc, Maestro S, Moroni D
Anorexia Nervosa (AN) patients exhibit distorted body representation. The purpose of this study was to explore studies that analyze virtual reality (VR) applications, related to body image issues, to propose a new tool in this field. We conducted a systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, EMBASE, Scopus, and Web of Science databases were explored; the review included 25 studies. Research has increased over the last five years. The selected studies, clinical observational studies (n = 16), mostly concerning patients' population with AN (n = 14) or eating disorders (EDs) diagnosis, presented multiple designs, populations involved, and procedures. Some of these studies included healthy control groups (n = 7). Studies on community sample populations were also selected if oriented toward clinical applications (n = 9). The VR technologies in the examined period (about 20 years) have evolved significantly, going from very complex and bulky systems, requiring very powerful computers, to agile systems. The advent of low-cost VR devices has given a big boost to research works. Moreover, the operational proposal that emerges from this work supports the use of biofeedback techniques aimed at evaluating the results of therapeutic interventions in the treatment of adolescent patients diagnosed with AN.Source: INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (ONLINE), vol. 19 (issue 5), pp. 1-30
DOI: 10.3390/ijerph19052533
Metrics:
Magrini M, Curzio O, Tampucci M, Donzelli G, Cori L, Imiotti Mc, Maestro S, Moroni D
Anorexia Nervosa (AN) patients exhibit distorted body representation. The purpose of this study was to explore studies that analyze virtual reality (VR) applications, related to body image issues, to propose a new tool in this field. We conducted a systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, EMBASE, Scopus, and Web of Science databases were explored; the review included 25 studies. Research has increased over the last five years. The selected studies, clinical observational studies (n = 16), mostly concerning patients' population with AN (n = 14) or eating disorders (EDs) diagnosis, presented multiple designs, populations involved, and procedures. Some of these studies included healthy control groups (n = 7). Studies on community sample populations were also selected if oriented toward clinical applications (n = 9). The VR technologies in the examined period (about 20 years) have evolved significantly, going from very complex and bulky systems, requiring very powerful computers, to agile systems. The advent of low-cost VR devices has given a big boost to research works. Moreover, the operational proposal that emerges from this work supports the use of biofeedback techniques aimed at evaluating the results of therapeutic interventions in the treatment of adolescent patients diagnosed with AN.Source: INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (ONLINE), vol. 19 (issue 5), pp. 1-30
DOI: 10.3390/ijerph19052533
Metrics:
See at:
CNR IRIS | ISTI Repository | www.mdpi.com | CNR IRIS
2022
Conference article
Open Access
A mobile crowdsensing app for improved maritime security and awareness
Moroni D, Pieri G, Reggiannini M, Tampucci M
The marine and maritime domain is well represented in the Sustainable Development Goals (SDG) envisaged by the United Nations, which aim at conserving and using the oceans, seas and their resources for sustainable development. At the same time, there is a need for improved safety in navigation, especially in coastal areas. Up to date, there exist operational services based on advanced technologies, including remote sensing and in situ monitoring networks which provide aid to the navigation and control over the environment for its preservation. Yet, the possibilities offered by crowdsensing have not yet been fully explored. This paper addresses this issue by presenting an app based on a crowdsensing approach for improved safety and awareness at sea. The app can be integrated into more comprehensive systems and frameworks for environmental monitoring as envisaged in our future work.DOI: 10.1109/percomworkshops53856.2022.9767516
Project(s): NAUTILOS
Metrics:
Moroni D, Pieri G, Reggiannini M, Tampucci M
The marine and maritime domain is well represented in the Sustainable Development Goals (SDG) envisaged by the United Nations, which aim at conserving and using the oceans, seas and their resources for sustainable development. At the same time, there is a need for improved safety in navigation, especially in coastal areas. Up to date, there exist operational services based on advanced technologies, including remote sensing and in situ monitoring networks which provide aid to the navigation and control over the environment for its preservation. Yet, the possibilities offered by crowdsensing have not yet been fully explored. This paper addresses this issue by presenting an app based on a crowdsensing approach for improved safety and awareness at sea. The app can be integrated into more comprehensive systems and frameworks for environmental monitoring as envisaged in our future work.DOI: 10.1109/percomworkshops53856.2022.9767516
Project(s): NAUTILOS
Metrics:
See at:
CNR IRIS | ieeexplore.ieee.org | CNR IRIS | CNR IRIS
2022
Conference article
Open Access
ARTiCo - AR in tissue converting
Moroni D, Pieri G, Tampucci M, Masini D
For fully up-taking the advances achieved in pervasive monitoring systems within Industry 4.0, novel intelligent interfaces are needed to ease interactions with human personnel and enable them to access the available data and services ergonomically. To this end, we present a mobile app based on augmented reality that allows operators to receive location-aware notifications and access and visualize real-time information and guidance for troubleshooting and plant maintenance. The app has been tailored to respond to the needs of a specific scenario, i.e. tissue converting, where it has provided encouraging results.DOI: 10.1109/percomworkshops53856.2022.9767409
Metrics:
Moroni D, Pieri G, Tampucci M, Masini D
For fully up-taking the advances achieved in pervasive monitoring systems within Industry 4.0, novel intelligent interfaces are needed to ease interactions with human personnel and enable them to access the available data and services ergonomically. To this end, we present a mobile app based on augmented reality that allows operators to receive location-aware notifications and access and visualize real-time information and guidance for troubleshooting and plant maintenance. The app has been tailored to respond to the needs of a specific scenario, i.e. tissue converting, where it has provided encouraging results.DOI: 10.1109/percomworkshops53856.2022.9767409
Metrics:
See at:
CNR IRIS | ieeexplore.ieee.org | ISTI Repository | CNR IRIS | CNR IRIS
2022
Other
Open Access
NAUTILOS - Fully developed graphic user interface. Accompanying report
Tampucci M, Pieri G, Volpini F
This deliverable consist of the deployment of the project's web portal through which the storage and management of the integrated data regarding NAUTILOS, and the services defined and implemented during Task 8.4 have been organised. The implemented tools and services for data management and visualisation, designed in close connection with end-users requirements, are described.Project(s): NAUTILOS
Tampucci M, Pieri G, Volpini F
This deliverable consist of the deployment of the project's web portal through which the storage and management of the integrated data regarding NAUTILOS, and the services defined and implemented during Task 8.4 have been organised. The implemented tools and services for data management and visualisation, designed in close connection with end-users requirements, are described.Project(s): NAUTILOS
See at:
CNR IRIS | ISTI Repository | zenodo.org | CNR IRIS
2022
Other
Open Access
NAUTILOS - Citizen Science tools and interface
Pieri G, Tampucci M
This deliverable will consist of the specific tools and interface for supporting the Citizen Science Campaigns, to integrate the data produced during these activities (see Task 12.2) within the web portal. The interface, realised in Task 8.4, will be based on geo-referenced maps indicating, for instance, plastic litter data. An accompanying report with the guidelines for the usage of these tools and interface will be produced.Project(s): NAUTILOS
Pieri G, Tampucci M
This deliverable will consist of the specific tools and interface for supporting the Citizen Science Campaigns, to integrate the data produced during these activities (see Task 12.2) within the web portal. The interface, realised in Task 8.4, will be based on geo-referenced maps indicating, for instance, plastic litter data. An accompanying report with the guidelines for the usage of these tools and interface will be produced.Project(s): NAUTILOS
See at:
CNR IRIS | ISTI Repository | zenodo.org | CNR IRIS
2022
Conference article
Open Access
Exploring UAVs for structural health monitoring
Germanese D, Moroni D, Pascali Ma, Tampucci M, Berton A
The preservation and maintenance of architectural heritage on a large scale deserve the design, development, and exploitation of innovative methodologies and tools for sustainable Structural Heritage Monitoring (SHM). In the framework of the Moscardo Project (https://www.moscardo.it/), the role of Unmanned Aerial Vehicles (UAVs) in conjunction with a broader IoT platform for SHM has been investigated. UAVs resulted in significant aid for a safe, fast and routinely operated inspection of buildings in synergy with data collected in situ thanks to a network of pervasive wireless sensors (Bacco et al. 2020). The main idea has been to deploy an acquisition layer made of a network of low power sensors capable of collecting environmental parameters and building vibration modes. This layer has been connected to a service layer through gateways capable of performing data analysis and presenting aggregated results thanks to an integrated dashboard. In this architecture, the UAV has emerged as a particular network node for extending the acquisition layer by adding several imaging capabilities.
Germanese D, Moroni D, Pascali Ma, Tampucci M, Berton A
The preservation and maintenance of architectural heritage on a large scale deserve the design, development, and exploitation of innovative methodologies and tools for sustainable Structural Heritage Monitoring (SHM). In the framework of the Moscardo Project (https://www.moscardo.it/), the role of Unmanned Aerial Vehicles (UAVs) in conjunction with a broader IoT platform for SHM has been investigated. UAVs resulted in significant aid for a safe, fast and routinely operated inspection of buildings in synergy with data collected in situ thanks to a network of pervasive wireless sensors (Bacco et al. 2020). The main idea has been to deploy an acquisition layer made of a network of low power sensors capable of collecting environmental parameters and building vibration modes. This layer has been connected to a service layer through gateways capable of performing data analysis and presenting aggregated results thanks to an integrated dashboard. In this architecture, the UAV has emerged as a particular network node for extending the acquisition layer by adding several imaging capabilities.
See at:
CNR IRIS | ISTI Repository | ISTI Repository | www.dsiteconference.com | CNR IRIS | CNR IRIS
2022
Conference article
Open Access
An intelligent platform of services based on multimedia understanding and telehealth for supporting the management of SARS-CoV-2 multi-pathological patients
Ignesti G., Bruno A., Deri C., D'Angelo G., Bastiani L., Pratali L., Memmini S., Cicalini D., Dini A., Galesi G., Pardini F., Tampucci M., Benassi A., Salvetti O., Moroni D., Martinelli M.
The combination of pervasive sensing and multimedia understanding with the advances in communications makes it possible to conceive platforms of services for providing telehealth solutions responding to the current needs of society. The recent outbreak has indeed posed several concerns on the management of patients at home, urging to devise complex pathways to address the Severe Acute Respiratory Syndrome (SARS) in combination with the usual diseases of an increasingly elder population. In this paper, we present TiAssisto, a project aiming to design, develop, and validate an innovative and intelligent platform of services, having as its main objective to assist both Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) multi-pathological patients and healthcare professionals. This is achieved by researching and validating new methods to improve their lives and reduce avoidable hospitalisations. TiAssisto features telehealth and telemedicine solutions to enable high-quality standards treatments based on Information and Communication Technologies (ICT), Artificial Intelligence (AI) and Machine Learning (ML). Three hundred patients are involvedin our study: one half using our telehealth platform, while the other half participate as a control group for a correct validation. The developed AI models and the Decision Support System assist General Practitioners (GPs) and other healthcare professionals in order to help them in their diagnosis, by providing suggestions and pointing out possible presence or absence of signs that can be related to pathologies. Deep learning techniques are also used to detect the absence or presence of specific signs in lung ultrasound images.DOI: 10.1109/sitis57111.2022.00089
Metrics:
Ignesti G., Bruno A., Deri C., D'Angelo G., Bastiani L., Pratali L., Memmini S., Cicalini D., Dini A., Galesi G., Pardini F., Tampucci M., Benassi A., Salvetti O., Moroni D., Martinelli M.
The combination of pervasive sensing and multimedia understanding with the advances in communications makes it possible to conceive platforms of services for providing telehealth solutions responding to the current needs of society. The recent outbreak has indeed posed several concerns on the management of patients at home, urging to devise complex pathways to address the Severe Acute Respiratory Syndrome (SARS) in combination with the usual diseases of an increasingly elder population. In this paper, we present TiAssisto, a project aiming to design, develop, and validate an innovative and intelligent platform of services, having as its main objective to assist both Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) multi-pathological patients and healthcare professionals. This is achieved by researching and validating new methods to improve their lives and reduce avoidable hospitalisations. TiAssisto features telehealth and telemedicine solutions to enable high-quality standards treatments based on Information and Communication Technologies (ICT), Artificial Intelligence (AI) and Machine Learning (ML). Three hundred patients are involvedin our study: one half using our telehealth platform, while the other half participate as a control group for a correct validation. The developed AI models and the Decision Support System assist General Practitioners (GPs) and other healthcare professionals in order to help them in their diagnosis, by providing suggestions and pointing out possible presence or absence of signs that can be related to pathologies. Deep learning techniques are also used to detect the absence or presence of specific signs in lung ultrasound images.DOI: 10.1109/sitis57111.2022.00089
Metrics:
See at:
CNR IRIS | ieeexplore.ieee.org | ISTI Repository | CNR IRIS | CNR IRIS
2022
Other
Open Access
SI-Lab annual research report 2021
Righi M, Leone G R, Carboni A, Caudai C, Colantonio S, Kuruoglu E E, Leporini B, Magrini M, Paradisi P, Pascali M A, Pieri G, Reggiannini M, Salerno E, Scozzari A, Tonazzini A, Fusco G, Galesi G, Martinelli M, Pardini F, Tampucci M, Berti A, Bruno A, Buongiorno R, Carloni G, Conti F, Germanese D, Ignesti G, Matarese F, Omrani A, Pachetti E, Papini O, Benassi A, Bertini G, Coltelli P, Tarabella L, Straface S, Salvetti O, Moroni D
The Signal & Images Laboratory is an interdisciplinary research group in computer vision, signal analysis, intelligent vision systems and multimedia data understanding. It is part of the Institute of Information Science and Technologies (ISTI) of the National Research Council of Italy (CNR). This report accounts for the research activities of the Signal and Images Laboratory of the Institute of Information Science and Technologies during the year 2021.DOI: 10.32079/isti-ar-2022/003
DOI: https://doi.org/10.32079/isti-ar-2022/003
Metrics:
Righi M, Leone G R, Carboni A, Caudai C, Colantonio S, Kuruoglu E E, Leporini B, Magrini M, Paradisi P, Pascali M A, Pieri G, Reggiannini M, Salerno E, Scozzari A, Tonazzini A, Fusco G, Galesi G, Martinelli M, Pardini F, Tampucci M, Berti A, Bruno A, Buongiorno R, Carloni G, Conti F, Germanese D, Ignesti G, Matarese F, Omrani A, Pachetti E, Papini O, Benassi A, Bertini G, Coltelli P, Tarabella L, Straface S, Salvetti O, Moroni D
The Signal & Images Laboratory is an interdisciplinary research group in computer vision, signal analysis, intelligent vision systems and multimedia data understanding. It is part of the Institute of Information Science and Technologies (ISTI) of the National Research Council of Italy (CNR). This report accounts for the research activities of the Signal and Images Laboratory of the Institute of Information Science and Technologies during the year 2021.DOI: 10.32079/isti-ar-2022/003
DOI: https://doi.org/10.32079/isti-ar-2022/003
Metrics:
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2022
Other
Restricted
Smart Converting 4.0 - Sistema di indoor localization
Zani F, Moroni D, Tampucci M, Antonetti M, Masini D
L'obiettivo operativo OO2 del progetto Smart Converting 4.0 mira a realizzare soluzioni innovative per la sicurezza basate su intelligenza artificiale, tecnologie evolute di localizzazione e robotica collaborativa integrandole nella operatività delle linee di converting. Le soluzioni consentiranno di incrementare il livello di sicurezza della linea, portandolo ben al di sopra dei vigenti requisiti normativi. Come già richiamato in D2.1.1, il sistema oggetto di studio consentirà di conoscere in tempo reale lo stato dell'impianto di trasformazione per carta tissue e per nonwoven ("tessuto-non-tessuto"), in particolare, in relazione alla posizione degli operatori e di eventuali mezzi mobili e, grazie a questo, consentire una notevole riduzione del rischio di incidenti. Il sistema funzionerà attraverso due diverse modalità: modalità "on line" e modalità "off line". Nella modalità "on line", il sistema, grazie della conoscenza dello stato e delle posizioni delle persone intorno al macchinario e sulla base di opportune policies, implementerà delle azioni sia verso gli operatori sia verso le macchine e i componenti robotici stessi, quali, ad esempio, il rilevamento di una eccessiva presenza di operatori in una zona dove operano mezzi mobili potenzialmente pericolosi, o la vicinanza o l'intrusione di un operatore in un'area interdetta. Quando la logica di una di queste policies risulterà verificata, il sistema genererà allarmi o interverrà automaticamente sull'impianto o sul singolo componente robotico, ad esempio rallentandone il funzionamento o inibendolo. Nella modalità "off line" sarà possibile analizzare i dati a posteriori ed effettuare delle analisi utili a comprendere lo stato dell'arte delle procedure "de facto" in essere consentendo quindi di definire ed implementare ottimizzazioni procedurali basate su cosa realmente accade nell'impianto nella sua normale operatività, il tutto ovviamente sempre nel rispetto dei diritti e delle privacy degli operatori. A titolo di esempio potremmo ipotizzare di verificare quante volte un operatore si avvicina o entra in una zona pericolosa. La conoscenza delle procedure effettive, vale a dire non quelle previste o schedulate ma quelle che effettivamente si verificano, avrà ovviamente ricadute positive non solo in termini di aumento della sicurezza ma anche in termini di incremento della produttività dell'intera linea di converting. Inoltre, in un momento in cui il distanziamento sociale e le modalità per rispettarlo sui luoghi di lavoro sono un tema di grande centralità, la conoscenza del posizionamento e della distanza tra gli operatori può aiutare a rispettare e mantenere le distanze dovute e, allo stesso tempo, consentire ai responsabili della sicurezza raccogliere preziose informazioni quantitative sulle aree della linea e sulle operazioni che hanno dato luogo a violazioni delle disposizioni in merito. Il presente deliverable ha lo scopo di illustrare il prototipo hardware software realizzato per il progetto e su cui si baseranno le attività di integrazione e test in Futura Lab previste in AO2.5. Il documento si articola come segue. Nella sezione 2 si riportano alcune immagini dei componenti del prototipo e alcuni screenshot del software realizzato. mentre la sezione 3 conclude il documento con una descrizione delle attività future previste.
Zani F, Moroni D, Tampucci M, Antonetti M, Masini D
L'obiettivo operativo OO2 del progetto Smart Converting 4.0 mira a realizzare soluzioni innovative per la sicurezza basate su intelligenza artificiale, tecnologie evolute di localizzazione e robotica collaborativa integrandole nella operatività delle linee di converting. Le soluzioni consentiranno di incrementare il livello di sicurezza della linea, portandolo ben al di sopra dei vigenti requisiti normativi. Come già richiamato in D2.1.1, il sistema oggetto di studio consentirà di conoscere in tempo reale lo stato dell'impianto di trasformazione per carta tissue e per nonwoven ("tessuto-non-tessuto"), in particolare, in relazione alla posizione degli operatori e di eventuali mezzi mobili e, grazie a questo, consentire una notevole riduzione del rischio di incidenti. Il sistema funzionerà attraverso due diverse modalità: modalità "on line" e modalità "off line". Nella modalità "on line", il sistema, grazie della conoscenza dello stato e delle posizioni delle persone intorno al macchinario e sulla base di opportune policies, implementerà delle azioni sia verso gli operatori sia verso le macchine e i componenti robotici stessi, quali, ad esempio, il rilevamento di una eccessiva presenza di operatori in una zona dove operano mezzi mobili potenzialmente pericolosi, o la vicinanza o l'intrusione di un operatore in un'area interdetta. Quando la logica di una di queste policies risulterà verificata, il sistema genererà allarmi o interverrà automaticamente sull'impianto o sul singolo componente robotico, ad esempio rallentandone il funzionamento o inibendolo. Nella modalità "off line" sarà possibile analizzare i dati a posteriori ed effettuare delle analisi utili a comprendere lo stato dell'arte delle procedure "de facto" in essere consentendo quindi di definire ed implementare ottimizzazioni procedurali basate su cosa realmente accade nell'impianto nella sua normale operatività, il tutto ovviamente sempre nel rispetto dei diritti e delle privacy degli operatori. A titolo di esempio potremmo ipotizzare di verificare quante volte un operatore si avvicina o entra in una zona pericolosa. La conoscenza delle procedure effettive, vale a dire non quelle previste o schedulate ma quelle che effettivamente si verificano, avrà ovviamente ricadute positive non solo in termini di aumento della sicurezza ma anche in termini di incremento della produttività dell'intera linea di converting. Inoltre, in un momento in cui il distanziamento sociale e le modalità per rispettarlo sui luoghi di lavoro sono un tema di grande centralità, la conoscenza del posizionamento e della distanza tra gli operatori può aiutare a rispettare e mantenere le distanze dovute e, allo stesso tempo, consentire ai responsabili della sicurezza raccogliere preziose informazioni quantitative sulle aree della linea e sulle operazioni che hanno dato luogo a violazioni delle disposizioni in merito. Il presente deliverable ha lo scopo di illustrare il prototipo hardware software realizzato per il progetto e su cui si baseranno le attività di integrazione e test in Futura Lab previste in AO2.5. Il documento si articola come segue. Nella sezione 2 si riportano alcune immagini dei componenti del prototipo e alcuni screenshot del software realizzato. mentre la sezione 3 conclude il documento con una descrizione delle attività future previste.