2026
Conference article
Open Access
Remind me of something? Zero-Shot learning for trustworthy image comparison in rolling stock
Papini Oscar, Del Corso Giulio, Bulotta Davide, Carboni Andrea, Gravili Silvia, Leone Giuseppe Riccardo, Pascali Maria Antonietta, Moroni Davide, Colantonio Sara
This paper discusses the need for trustworthy AI in urban mobility, focusing on high-stakes security applications such as anomaly detection in public transportation. Because the accuracy required to identify potentially dangerous objects often surpasses the capabilities of current models, there is an unavoidable incidence of false positives. We suggest a "learning to defer" approach as a solution. Our technique uses the deep features and label relative importance of a pre-trained classifier (DenseNet/ImageNET-1k) to create a unique item "fingerprint". We then employ a zero-shot meta-learning approach to calibrate the system, enabling it to distinguish between normal background items and genuine anomalies by assigning a similarity score. This method significantly reduces the false "new object" alarms that would otherwise overwhelm human operators. Our proof-of-concept demonstrates that the system is computationally light and can be easily adapted to specific environments and integrated into existing classification modules.Source: LECTURE NOTES IN COMPUTER SCIENCE, vol. 16170, pp. 323-334. Roma, Italy, 15-19/09/2025
DOI: 10.1007/978-3-032-11381-8_28
Project(s): FAITH
Metrics:
Papini Oscar, Del Corso Giulio, Bulotta Davide, Carboni Andrea, Gravili Silvia, Leone Giuseppe Riccardo, Pascali Maria Antonietta, Moroni Davide, Colantonio Sara
This paper discusses the need for trustworthy AI in urban mobility, focusing on high-stakes security applications such as anomaly detection in public transportation. Because the accuracy required to identify potentially dangerous objects often surpasses the capabilities of current models, there is an unavoidable incidence of false positives. We suggest a "learning to defer" approach as a solution. Our technique uses the deep features and label relative importance of a pre-trained classifier (DenseNet/ImageNET-1k) to create a unique item "fingerprint". We then employ a zero-shot meta-learning approach to calibrate the system, enabling it to distinguish between normal background items and genuine anomalies by assigning a similarity score. This method significantly reduces the false "new object" alarms that would otherwise overwhelm human operators. Our proof-of-concept demonstrates that the system is computationally light and can be easily adapted to specific environments and integrated into existing classification modules.Source: LECTURE NOTES IN COMPUTER SCIENCE, vol. 16170, pp. 323-334. Roma, Italy, 15-19/09/2025
DOI: 10.1007/978-3-032-11381-8_28
Project(s): FAITH
Metrics:
See at:
CNR IRIS 
| link.springer.com | CNR IRIS 
| CNR IRIS
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
Open Access
Art and Science: a mutual exchange - The experience of the Signals and Images Laboratory of the ISTI-CNR
Magrini M., Carboni A., Pardini F.
In the Signals and Images Laboratory (SILab) at ISTI-CNR, science, technol- ogy and art have developed a symbiotic relationship where, often, each enhances the other. Initially, technologies like gesture recognition were created to support live artistic perfor- mances, allowing artists to control music and graphics interactively. Later, these same tech- nologies were adapted for medical purposes, particularly in motor rehabilitation for children and older people. For example, applications initially designed for art and cultural heritage were found to be helpful in rehabilitation, driving new scientific research. This paper shows some examples where this collaboration has produced innovation and research.Source: MEMORIE DELLA SOCIETÀ ASTRONOMICA ITALIANA, pp. 38-43
DOI: 10.36116/memsait_96n1.2025.38
Metrics:
Magrini M., Carboni A., Pardini F.
In the Signals and Images Laboratory (SILab) at ISTI-CNR, science, technol- ogy and art have developed a symbiotic relationship where, often, each enhances the other. Initially, technologies like gesture recognition were created to support live artistic perfor- mances, allowing artists to control music and graphics interactively. Later, these same tech- nologies were adapted for medical purposes, particularly in motor rehabilitation for children and older people. For example, applications initially designed for art and cultural heritage were found to be helpful in rehabilitation, driving new scientific research. This paper shows some examples where this collaboration has produced innovation and research.Source: MEMORIE DELLA SOCIETÀ ASTRONOMICA ITALIANA, pp. 38-43
DOI: 10.36116/memsait_96n1.2025.38
Metrics:
2025
Other
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Computer vision per la valutazione della performance
in ambito sportivo
Elia Grassetti, Grassetti E., Carboni A., Naretto F.
L'oggetto della tesi è lo studio sviluppo di sistemi di visione artificiale a supporto dell’analisi delle prestazioni di sportivi professionisti. Il sistema oggetto di questa tesi `e il primo inerente allo studio di uno specifico colpo del golf, ovvero il putting. L’obiettivo del sistema sviluppato `e analizzare un colpo di putting a partire da un semplice video, utilizzando un marker ArUco applicato sulla testa del bastone da golf per estrarre informazioni spaziali e angolari sul movimento. Viene inoltre visualizzato l’arco percorso dal bastone prima dell’impatto e, tramite una rete neurale chiamata YOLO, viene tracciata la pallina attraverso un processo di machine learning. Questi dati risultano fondamentali per valutare la correttezza del gesto tecnico e identificare eventuali errori nell’esecuzione
Elia Grassetti, Grassetti E., Carboni A., Naretto F.
L'oggetto della tesi è lo studio sviluppo di sistemi di visione artificiale a supporto dell’analisi delle prestazioni di sportivi professionisti. Il sistema oggetto di questa tesi `e il primo inerente allo studio di uno specifico colpo del golf, ovvero il putting. L’obiettivo del sistema sviluppato `e analizzare un colpo di putting a partire da un semplice video, utilizzando un marker ArUco applicato sulla testa del bastone da golf per estrarre informazioni spaziali e angolari sul movimento. Viene inoltre visualizzato l’arco percorso dal bastone prima dell’impatto e, tramite una rete neurale chiamata YOLO, viene tracciata la pallina attraverso un processo di machine learning. Questi dati risultano fondamentali per valutare la correttezza del gesto tecnico e identificare eventuali errori nell’esecuzione
2025
Other
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Computer vision per la human activity recognition in ambito sportivo professionistico
Nicolò Nocera, Nocera N., Carboni A., Carta A.
L’idea alla base del progetto è creare un sistema di analisi video, a partire da immagini televisive, in grado di supportare la valutazione delle performance di tennisti professionisti all’inizio della loro carriera e ben lontani dalle prime posizioni della classifica ATP; un sistema di analisi delle loro prestazioni durante gli allenamenti e i match potrebbe essere un utile strumento di supporto per la loro crescita sportiva e per la loro carriera.
Nicolò Nocera, Nocera N., Carboni A., Carta A.
L’idea alla base del progetto è creare un sistema di analisi video, a partire da immagini televisive, in grado di supportare la valutazione delle performance di tennisti professionisti all’inizio della loro carriera e ben lontani dalle prime posizioni della classifica ATP; un sistema di analisi delle loro prestazioni durante gli allenamenti e i match potrebbe essere un utile strumento di supporto per la loro crescita sportiva e per la loro carriera.
2025
Conference article
Open Access
Towards trustworthy AI in the public transport domain
Leone G. R., Carboni A., Del Corso G., Gravili S., Moroni D., Pascali M. A., Colantonio S.
In the context of rapidly evolving urban landscapes, the demand for enhanced mobility services has become increasingly critical. Traditional transportation systems struggle to keep pace with the growing complexity of commuting patterns and the diverse needs of urban residents. While AI can play a strong role in addressing these emerging demands, a parallel need for trustworthy services is also arising, which must be adequately met to ultimately provide equitable and ethical services to society. Based on these considerations, we explore the relevant dimensions of AI trustworthiness and propose how they can be transferred and demonstrated in a large-scale pilot focused on public transportation and exploiting advanced visual analytics paradigms based on pervasive computing. To this end, we present the FAITH risk management framework, ongoing activities, and preliminary results towards its implementation in the pilot project.Source: CEUR WORKSHOP PROCEEDINGS, vol. 4121. Trieste, Italy, 23-24/06/2025
Leone G. R., Carboni A., Del Corso G., Gravili S., Moroni D., Pascali M. A., Colantonio S.
In the context of rapidly evolving urban landscapes, the demand for enhanced mobility services has become increasingly critical. Traditional transportation systems struggle to keep pace with the growing complexity of commuting patterns and the diverse needs of urban residents. While AI can play a strong role in addressing these emerging demands, a parallel need for trustworthy services is also arising, which must be adequately met to ultimately provide equitable and ethical services to society. Based on these considerations, we explore the relevant dimensions of AI trustworthiness and propose how they can be transferred and demonstrated in a large-scale pilot focused on public transportation and exploiting advanced visual analytics paradigms based on pervasive computing. To this end, we present the FAITH risk management framework, ongoing activities, and preliminary results towards its implementation in the pilot project.Source: CEUR WORKSHOP PROCEEDINGS, vol. 4121. Trieste, Italy, 23-24/06/2025
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2025
Conference article
Open Access
Leveraging AI for Signal and Image Analysis in Medicine and Health
Marco Cafiso, Andrea Carboni, Claudia Caudai, Sara Colantonio, Francesco Conti, Mario D’acunto, Said Daoudagh, Giulio Del Corso, Danila Germanese, Giacomo Ignesti, Gianmarco Lazzini, Giuseppe Riccardo Leone, Massimo Magrini, Davide Moroni, Francesca Pardini, Maria Antonietta Pascali, Paolo Paradisi, Federico Volpini
The integration of artificial intelligence (AI) into the medical domain is driving innovation and progress in healthcare. This paper summarizes the research activities that a multidisciplinary research group within the Signals and Images Lab of the Institute of Information Science and Technologies of the National Research Council of Italy is carrying out to explore the great potential of AI in several applications, e.g., in the analysis of biomedical data, and in the development of tools for enhancing trustworthiness and reliability of AI based systems. From cancer diagnosis and grading, to the analysis of body physiological signals to improve the understanding of dance movement therapy as an approach to healthy aging, this work highlights the paradigm shift that AI has brought into medicine and healthcare.Source: CEUR WORKSHOP PROCEEDINGS, vol. 4121. Trieste, June 23-24, 2025
Marco Cafiso, Andrea Carboni, Claudia Caudai, Sara Colantonio, Francesco Conti, Mario D’acunto, Said Daoudagh, Giulio Del Corso, Danila Germanese, Giacomo Ignesti, Gianmarco Lazzini, Giuseppe Riccardo Leone, Massimo Magrini, Davide Moroni, Francesca Pardini, Maria Antonietta Pascali, Paolo Paradisi, Federico Volpini
The integration of artificial intelligence (AI) into the medical domain is driving innovation and progress in healthcare. This paper summarizes the research activities that a multidisciplinary research group within the Signals and Images Lab of the Institute of Information Science and Technologies of the National Research Council of Italy is carrying out to explore the great potential of AI in several applications, e.g., in the analysis of biomedical data, and in the development of tools for enhancing trustworthiness and reliability of AI based systems. From cancer diagnosis and grading, to the analysis of body physiological signals to improve the understanding of dance movement therapy as an approach to healthy aging, this work highlights the paradigm shift that AI has brought into medicine and healthcare.Source: CEUR WORKSHOP PROCEEDINGS, vol. 4121. Trieste, June 23-24, 2025
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2025
Other
Open Access
Realizzazione di un’Interfaccia grafica e gestore di eventi per un sistema di match analysis basato su tecniche di computer vision
Alessio Iacullo, Iacullo A., Carboni A., Malizia A.
Durante il tirocinio, il candidato ha realizzato un insieme di algoritmi in grado di elaborare video di partite di tennis, utilizzando una rete neurale per identificare e selezionare solamente le scene di gioco effettivo, escludendo quelle non rilevanti, come stacchi pubblicitari o cambi di campo. In parallelo a questo lavoro è stata realizzata un’interfaccia grafica intuitiva che permette l’utilizzo degli algoritmi realizzati nel contesto di questo tirocinio, ma anche la possibilità di integrarne di altri, oltre all’importante funzionalità di poter associare i vari spezzoni di video a specifiche situazioni di punteggio della partita analizzata.
Alessio Iacullo, Iacullo A., Carboni A., Malizia A.
Durante il tirocinio, il candidato ha realizzato un insieme di algoritmi in grado di elaborare video di partite di tennis, utilizzando una rete neurale per identificare e selezionare solamente le scene di gioco effettivo, escludendo quelle non rilevanti, come stacchi pubblicitari o cambi di campo. In parallelo a questo lavoro è stata realizzata un’interfaccia grafica intuitiva che permette l’utilizzo degli algoritmi realizzati nel contesto di questo tirocinio, ma anche la possibilità di integrarne di altri, oltre all’importante funzionalità di poter associare i vari spezzoni di video a specifiche situazioni di punteggio della partita analizzata.
2024
Other
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Tecniche di computer vision per l’analisi automatica delle partite di tennis
Barresi Gaetano, Barresi G., Carboni A., Turchi T.
L’obiettivo generale e` quello di sviluppare un sistema di analisi video capace di riconoscere e tracciare i giocatori, il campo, la palla e rilevare i rimbalzi da una semplice ripresa video. A partire da questi elementi sara` possibile estrarre vari dati e metriche (e.g. spazio percorso, numero di cambi di direzione effettuati, tipologia di colpi giocati, etc.), utili agli allenatori per la valutazione delle performance di tennisti professionisti all’inizio della loro carriera, lontani dalle prime posizioni della classifica ATP. In questa tesi e` stata data enfasi al riconoscimento del campo focalizzandosi sullo studio di una rete neurale esistente e sull’accrescimento del suo dataset, il cui modello risultante viene impiegato per rilevare efficacemente il campo da gioco indipendentemente dall’angolazione e dalla tipologia dello stesso.
Barresi Gaetano, Barresi G., Carboni A., Turchi T.
L’obiettivo generale e` quello di sviluppare un sistema di analisi video capace di riconoscere e tracciare i giocatori, il campo, la palla e rilevare i rimbalzi da una semplice ripresa video. A partire da questi elementi sara` possibile estrarre vari dati e metriche (e.g. spazio percorso, numero di cambi di direzione effettuati, tipologia di colpi giocati, etc.), utili agli allenatori per la valutazione delle performance di tennisti professionisti all’inizio della loro carriera, lontani dalle prime posizioni della classifica ATP. In questa tesi e` stata data enfasi al riconoscimento del campo focalizzandosi sullo studio di una rete neurale esistente e sull’accrescimento del suo dataset, il cui modello risultante viene impiegato per rilevare efficacemente il campo da gioco indipendentemente dall’angolazione e dalla tipologia dello stesso.
2024
Other
Restricted
Computer vision per il monitoraggio delle attività durante i match
Daniele Freschi, Freschi D., Carboni A.
In seguito ad alcuni incontri con i preparatori del centro, `e emerso che l’utilizzo di tecnologie per l’analisi delle prestazioni degli atleti `e, ad oggi, estremamente limitato. I fattori che ostacolano l’introduzione di nuove tecnologie di analisi sono molteplici: da un lato c’`e il rifiuto da parte dei giocatori di utilizzare tecnologie indossabili, soprattutto durante partite ufficiali, dall’altro le tecnologie presenti sono quelle ereditate dal calcio che, basandosi su gps, non offrono una precisione tale da risultare accurate nel tennis. Esistono sistemi di analisi video [4], ma oltre ad essere molto costosi, hanno necessit`a di un’installazione fissa e si concentrano principalmente su moto e traiettorie della pallina. E’ quindi emersa un’apertura all’utilizzo e alla sperimentazione di nuove tecnologie che permettono l’analisi delle performance di un giocatore, soprattuto durante una partita ufficiale.
Daniele Freschi, Freschi D., Carboni A.
In seguito ad alcuni incontri con i preparatori del centro, `e emerso che l’utilizzo di tecnologie per l’analisi delle prestazioni degli atleti `e, ad oggi, estremamente limitato. I fattori che ostacolano l’introduzione di nuove tecnologie di analisi sono molteplici: da un lato c’`e il rifiuto da parte dei giocatori di utilizzare tecnologie indossabili, soprattutto durante partite ufficiali, dall’altro le tecnologie presenti sono quelle ereditate dal calcio che, basandosi su gps, non offrono una precisione tale da risultare accurate nel tennis. Esistono sistemi di analisi video [4], ma oltre ad essere molto costosi, hanno necessit`a di un’installazione fissa e si concentrano principalmente su moto e traiettorie della pallina. E’ quindi emersa un’apertura all’utilizzo e alla sperimentazione di nuove tecnologie che permettono l’analisi delle performance di un giocatore, soprattuto durante una partita ufficiale.
2024
Other
Open Access
A comprehensive system supporting sustainable agricultural production from farm to fork
Carboni A., Galesi G., Ignesti G., Leone G. R., Magrini M., Martinelli M., Martino G., Moroni D., Pardini F., Scozzari A.
Poster presented at ISTI Day 2023-2024 edition on June 14 2024.DOI: 10.5281/zenodo.12168200
Metrics:
Carboni A., Galesi G., Ignesti G., Leone G. R., Magrini M., Martinelli M., Martino G., Moroni D., Pardini F., Scozzari A.
Poster presented at ISTI Day 2023-2024 edition on June 14 2024.DOI: 10.5281/zenodo.12168200
Metrics:
2024
Other
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VARIOUS INNOVATIVE TECHNOLOGICAL EXPERIENCES - VITE II, Verso un futuro inclusivo: tecnologie e metodi per l'Active and Healthy Ageing (AHA) e i Disturbi di Sviluppo
Carboni A.
Verso un futuro inclusivo: tecnologie e metodi per l'Active and Healthy Ageing (AHA) e i Disturbi dello SviluppoDOI: 10.36116/videomem_2.2024.14
Metrics:
Carboni A.
Verso un futuro inclusivo: tecnologie e metodi per l'Active and Healthy Ageing (AHA) e i Disturbi dello SviluppoDOI: 10.36116/videomem_2.2024.14
Metrics:
2024
Journal article
Open Access
Transforming public transport through responsible AI: insight from the FAITH project
Leone G. R., Carboni A., Moroni D., Colantonio S.
In the framework of the FAITH project, an AI-powered large-scale pilot is being organized to showcase the opportunities offered by advancements in edge computing and computer vision. The goal is to provide innovative ways to ensure safer and more sustainable public transport, encouraging modal shifts. Challenges in deploying responsible and trustworthy AI-based services will be addressed by assessing regulatory aspects and fostering co-design with end users and all the other stakeholders involved.Source: ERCIM NEWS, vol. 138, pp. 23-24
Project(s): FAITH
Leone G. R., Carboni A., Moroni D., Colantonio S.
In the framework of the FAITH project, an AI-powered large-scale pilot is being organized to showcase the opportunities offered by advancements in edge computing and computer vision. The goal is to provide innovative ways to ensure safer and more sustainable public transport, encouraging modal shifts. Challenges in deploying responsible and trustworthy AI-based services will be addressed by assessing regulatory aspects and fostering co-design with end users and all the other stakeholders involved.Source: ERCIM NEWS, vol. 138, pp. 23-24
Project(s): FAITH
See at:
ercim-news.ercim.eu | CNR IRIS | CNR IRIS
2024
Journal article
Open Access
Towards an inclusive future: technologies and methods for active and healthy ageing and developmental disorders
Carboni A., Magrini M., Pardini F.
This article presents an overview of the technological advancements and research initiatives in the fields of Active and Healthy Ageing (AHA) and Autism Spectrum Disorder (ASD). Through the integration of IoT platforms, AI-based systems, and sensor networks, several projects have demonstrated significant improvements in quality of life for elderly individuals and children with developmental disorders. In this article, we will reference projects conducted by the SiLAB laboratory of ISTI-CNR in these two fields, which are united by the shared emphasis on inclusiveness and the application of similar technologies. These initiatives emphasize personalized approaches to healthcare, rehabilitation, and monitoring, highlighting the potential of technology in creating inclusive environments. The article also consider the implications of European regulations, such as the GDPR and the AI Act, for projects dealing with sensitive data, stressing the importance of stakeholder engagement and ethical considerations in the development of these technologies.Source: MEMORIE DELLA SOCIETÀ ASTRONOMICA ITALIANA, vol. 96, pp. 44-49
Carboni A., Magrini M., Pardini F.
This article presents an overview of the technological advancements and research initiatives in the fields of Active and Healthy Ageing (AHA) and Autism Spectrum Disorder (ASD). Through the integration of IoT platforms, AI-based systems, and sensor networks, several projects have demonstrated significant improvements in quality of life for elderly individuals and children with developmental disorders. In this article, we will reference projects conducted by the SiLAB laboratory of ISTI-CNR in these two fields, which are united by the shared emphasis on inclusiveness and the application of similar technologies. These initiatives emphasize personalized approaches to healthcare, rehabilitation, and monitoring, highlighting the potential of technology in creating inclusive environments. The article also consider the implications of European regulations, such as the GDPR and the AI Act, for projects dealing with sensitive data, stressing the importance of stakeholder engagement and ethical considerations in the development of these technologies.Source: MEMORIE DELLA SOCIETÀ ASTRONOMICA ITALIANA, vol. 96, pp. 44-49
See at:
CNR IRIS | www.memsait.it | CNR IRIS
2023
Journal article
Open Access
Privacy by design in systems for assisted living, personalized care and well-being: a stakeholder analysis
Carboni A, Russo D, Moroni D, Barsocchi P
The concept of privacy-by-design within a system for assisted living, personalized care and well-being is crucial to protect users from misuse of the data collected about their health. Especially if the information is collected through audio-video devices, the question is even more delicate due to the nature of this data. In fact, in addition to guaranteeing a high level of privacy, it is necessary to reassure end-users about the correct use of these streams. The evolution of data analysis techniques began to take In review on an important role and increasingly defined characteristics in recent years. In this article, with reference to European projects in the AHA/AAL domain, we will see a differentiation of the concept of privacy-by-design according to different dimensions (Technical, Contextual, Business) and to the Stakeholders involved. The analysis is intended to cover technical aspects, legislative and policies-related aspects also regarding the point of view of the municipalities and aspects related to the acceptance and, therefore, to the perception of the safety of these technologies by the final end-users.Source: FRONTIERS IN DIGITAL HEALTH
DOI: 10.3389/fdgth.2022.934609
Project(s): PlatformUptake.eu
Metrics:
Carboni A, Russo D, Moroni D, Barsocchi P
The concept of privacy-by-design within a system for assisted living, personalized care and well-being is crucial to protect users from misuse of the data collected about their health. Especially if the information is collected through audio-video devices, the question is even more delicate due to the nature of this data. In fact, in addition to guaranteeing a high level of privacy, it is necessary to reassure end-users about the correct use of these streams. The evolution of data analysis techniques began to take In review on an important role and increasingly defined characteristics in recent years. In this article, with reference to European projects in the AHA/AAL domain, we will see a differentiation of the concept of privacy-by-design according to different dimensions (Technical, Contextual, Business) and to the Stakeholders involved. The analysis is intended to cover technical aspects, legislative and policies-related aspects also regarding the point of view of the municipalities and aspects related to the acceptance and, therefore, to the perception of the safety of these technologies by the final end-users.Source: FRONTIERS IN DIGITAL HEALTH
DOI: 10.3389/fdgth.2022.934609
Project(s): PlatformUptake.eu
Metrics:
See at:
CNR IRIS | ISTI Repository | ISTI Repository | www.frontiersin.org | CNR IRIS | CNR IRIS
2023
Conference article
Open Access
A novel smart camera network for real time public transport monitoring and surveillance
Carboni A., Leone G. R., Nardi S., Corrado A., Moroni D.
In this paper, we present the environment perception layer of the Smart Passenger Center (SPaCe), a novel integrated framework for public transport management. This layer is a pervasive vision architecture for improved safety and security in the context of public transportation. Privacy and technological constraints are still significant limitations for the real-time analysis of video streams from video capture devices installed on public transport vehicles. In fact, in almost all cases, this analysis is carried out offline and lacks any predictive processing, which is now potentially applicable to all transport sectors, thanks to machine learning and artificial vision techniques. The architecture described is designed to combine the output of a set of parallel processing, all running onboard in real-time, thus allowing the separation of the information collected from actual passengers' identities. The analysis highlights aspects that affect travel and travellers safety, such as people's behaviour and the state of maintenance of vehicles.Source: PROCEEDINGS IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS, pp. 5223-5228. Bilbao, Spain, 24-28/09/2023
DOI: 10.1109/itsc57777.2023.10421861
Metrics:
Carboni A., Leone G. R., Nardi S., Corrado A., Moroni D.
In this paper, we present the environment perception layer of the Smart Passenger Center (SPaCe), a novel integrated framework for public transport management. This layer is a pervasive vision architecture for improved safety and security in the context of public transportation. Privacy and technological constraints are still significant limitations for the real-time analysis of video streams from video capture devices installed on public transport vehicles. In fact, in almost all cases, this analysis is carried out offline and lacks any predictive processing, which is now potentially applicable to all transport sectors, thanks to machine learning and artificial vision techniques. The architecture described is designed to combine the output of a set of parallel processing, all running onboard in real-time, thus allowing the separation of the information collected from actual passengers' identities. The analysis highlights aspects that affect travel and travellers safety, such as people's behaviour and the state of maintenance of vehicles.Source: PROCEEDINGS IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS, pp. 5223-5228. Bilbao, Spain, 24-28/09/2023
DOI: 10.1109/itsc57777.2023.10421861
Metrics:
See at:
IRIS Cnr | IRIS Cnr | IRIS Cnr | doi.org | CNR IRIS | CNR IRIS
2022
Conference article
Open Access
Measuring the uptaking of digital health platforms on AAL/AHA domain
Juiz C, Bermejo B, Nikolov A, Rus S, Carboni A, Russo D, Moroni D, Karanastasis We, Andronikou V, Samuelsson C, Lievens F, Van Berlo A, Van Staalduinen W, Cabreraumpierrez Mf
This paper presents a method to determine the metrics to assess the uptake of Ambient Assisted Living (AAL) platforms. The different platforms are offering various resources to construct digital health products oriented to Active and Healthy Ageing (AHA) and social health care. This research work is ad-dressed to identify and define which metrics could be Key Performance Indicators (KPIs) to be tracked for successful uptake, interoperability, synergies, and cost-benefit analysis of open platforms.DOI: 10.1007/978-981-19-1610-6_45
Project(s): PlatformUptake.eu
Metrics:
Juiz C, Bermejo B, Nikolov A, Rus S, Carboni A, Russo D, Moroni D, Karanastasis We, Andronikou V, Samuelsson C, Lievens F, Van Berlo A, Van Staalduinen W, Cabreraumpierrez Mf
This paper presents a method to determine the metrics to assess the uptake of Ambient Assisted Living (AAL) platforms. The different platforms are offering various resources to construct digital health products oriented to Active and Healthy Ageing (AHA) and social health care. This research work is ad-dressed to identify and define which metrics could be Key Performance Indicators (KPIs) to be tracked for successful uptake, interoperability, synergies, and cost-benefit analysis of open platforms.DOI: 10.1007/978-981-19-1610-6_45
Project(s): PlatformUptake.eu
Metrics:
See at:
CNR IRIS | link.springer.com | ISTI Repository | doi.org | hal.archives-ouvertes.fr | CNR IRIS | CNR IRIS
2022
Conference article
Open Access
Computer vision per sistemi di trasporto intelligenti: il progetto S.Pa.Ce.
Leone Gr, Carboni A, Nardi S, Moroni D
Lo Smart Passenger Center (SPaCe) è una piattaforma integrata che mira a superare la complessità della gestione centralizzata delle infrastrutture di trasporto pubblico e dei veicoli. Il motore di intelligenza artificiale esamina i flussi quotidiani di persone, correla dati ed eventi diversi, prevede minacce ed eventi critici e propone contromisure. Questa enorme mole di dati proviene da una rete pervasiva di telecamere intelligenti che monitora costantemente le attività in stazioni, treni, autobus e altri luoghi di interesse. In questo lavoro, presentiamo il sottosistema distribuito di visione artificiale, lo stato dell'arte delle tecniche adottate e le funzionalità avanzate che questo sistema di sorveglianza intelligente offre ai livelli superiori di SPaCe. Tutto è sviluppato seguendo il paradigma della privacy-by-design: nessuna immagine viene registrata o trasmessa, ma tutte le elaborazioni avvengono sui nodi periferici del sistema.
Leone Gr, Carboni A, Nardi S, Moroni D
Lo Smart Passenger Center (SPaCe) è una piattaforma integrata che mira a superare la complessità della gestione centralizzata delle infrastrutture di trasporto pubblico e dei veicoli. Il motore di intelligenza artificiale esamina i flussi quotidiani di persone, correla dati ed eventi diversi, prevede minacce ed eventi critici e propone contromisure. Questa enorme mole di dati proviene da una rete pervasiva di telecamere intelligenti che monitora costantemente le attività in stazioni, treni, autobus e altri luoghi di interesse. In questo lavoro, presentiamo il sottosistema distribuito di visione artificiale, lo stato dell'arte delle tecniche adottate e le funzionalità avanzate che questo sistema di sorveglianza intelligente offre ai livelli superiori di SPaCe. Tutto è sviluppato seguendo il paradigma della privacy-by-design: nessuna immagine viene registrata o trasmessa, ma tutte le elaborazioni avvengono sui nodi periferici del sistema.
See at:
CNR IRIS | ISTI Repository | ISTI Repository | www.ital-ia2022.it | CNR IRIS | CNR IRIS
2022
Conference article
Open Access
Toward pervasive computer vision for intelligent transport system
Leone Gr, Carboni A, Nardi S, Moroni D
The Smart Passenger Center (SPaCe) is a fully integrated platform that aims to overcome the complexity of centralized management of public transport infrastructure and vehicles. The SPaCe artificial intelligence engine predicts threats and critical events and proposes countermeasures by examining the daily flows of people and correlating different data and events, thanks to machine learning and big data analytics. All this massive data comes from a pervasive smart cameras network that constantly monitors activities in stations, trains, buses and other places of interest. In this work, we present the idea of this computer vision distributed sub-system, the state of the art of the techniques involved and the advanced functionalities that this intelligent surveillance system offers to the upper layers. Everything is developed following the privacy-by-design paradigm; namely, no real image is recorded or transmitted, but all the elaborations take place on the edge nodes of the system.DOI: 10.1109/percomworkshops53856.2022.9767376
Metrics:
Leone Gr, Carboni A, Nardi S, Moroni D
The Smart Passenger Center (SPaCe) is a fully integrated platform that aims to overcome the complexity of centralized management of public transport infrastructure and vehicles. The SPaCe artificial intelligence engine predicts threats and critical events and proposes countermeasures by examining the daily flows of people and correlating different data and events, thanks to machine learning and big data analytics. All this massive data comes from a pervasive smart cameras network that constantly monitors activities in stations, trains, buses and other places of interest. In this work, we present the idea of this computer vision distributed sub-system, the state of the art of the techniques involved and the advanced functionalities that this intelligent surveillance system offers to the upper layers. Everything is developed following the privacy-by-design paradigm; namely, no real image is recorded or transmitted, but all the elaborations take place on the edge nodes of the system.DOI: 10.1109/percomworkshops53856.2022.9767376
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
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
Metrics:
See at:
CNR IRIS | ISTI Repository | CNR IRIS