2025
Conference article
Restricted
Reducing training data for indoor positioning through physics-informed neural networks
Lombardi G., Crivello A., Barsocchi P., Chessa S., Furfari F.
In this work, we propose a novel framework based on Physics-Informed Neural Networks (PINNs) for directly estimating indoor positions, a method that, to the best of our knowledge, has not been previously explored. Training is performed on a public BLE dataset that includes a variety of indoor scenarios, including Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) conditions caused by human body signal attenuation. The integration of physics-compliant synthetic data during the training phase significantly reduces dependence on large-scale real-world datasets, enabling the use of a simple Multilayer Perceptron (MLP) architecture. Our results demonstrate that combining PINNs with real-world measurements enhances model generalization without compromising accuracy.DOI: 10.1109/ipin66788.2025.11213454
Project(s): A novel public-private alliance to generate socioeconomic, biomedical and technological solutions for an inclusive Italian ageing society
Metrics:
Lombardi G., Crivello A., Barsocchi P., Chessa S., Furfari F.
In this work, we propose a novel framework based on Physics-Informed Neural Networks (PINNs) for directly estimating indoor positions, a method that, to the best of our knowledge, has not been previously explored. Training is performed on a public BLE dataset that includes a variety of indoor scenarios, including Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) conditions caused by human body signal attenuation. The integration of physics-compliant synthetic data during the training phase significantly reduces dependence on large-scale real-world datasets, enabling the use of a simple Multilayer Perceptron (MLP) architecture. Our results demonstrate that combining PINNs with real-world measurements enhances model generalization without compromising accuracy.DOI: 10.1109/ipin66788.2025.11213454
Project(s): A novel public-private alliance to generate socioeconomic, biomedical and technological solutions for an inclusive Italian ageing society
Metrics:
See at:
CNR IRIS 
| ieeexplore.ieee.org | CNR IRIS
2025
Journal article
Open Access
Comprehensive assessment of open science practices in indoor positioning: open data, code, and material
Anagnostopoulos G. G., Barsocchi P., Crivello A., Pendão C., Silva I., Torres-Sospedra J.
Transparency and verifiability have long been regarded as cornerstones of the scientific ethos and practice. However, persistent reproducibility challenges across numerous disciplines have brought renewed attention to the imperative for widespread adoption of open science practices. These considerations are particularly relevant to the research field of indoor positioning. Open data and open code sharing are gradually gaining traction in the field, but are still far from standard practice. This study comprehensively evaluates the extent of the adoption of open science practices within the community of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), by systematically analyzing all reference papers from the 2019 to 2024 editions of the IPIN. The work thoroughly examines the open data and code usage, and the use of other types of open materials while performing a particular close-up review of the open data that are leveraged in these studies. Our findings reveal that 21.7% of papers use open research data, 8.3% utilize open code, and 20.2% incorporate other open materials. However, only 6.8% of papers provide both open data and code. Moreover, emerging patterns and intuitive best practices are highlighted. The complete characterization of all reviewed publications is publicly available. This study brings to light the need for wider adoption of open science practices, to enhance the transparency, reproducibility, replicability, and reliability of research outcomes in the field of indoor positioning.Source: IEEE JOURNAL OF INDOOR AND SEAMLESS POSITIONING AND NAVIGATION, vol. 3, pp. 175-194
DOI: 10.1109/jispin.2025.3570258
DOI: 10.5281/zenodo.14931103
DOI: 10.5281/zenodo.14931104
Metrics:
Anagnostopoulos G. G., Barsocchi P., Crivello A., Pendão C., Silva I., Torres-Sospedra J.
Transparency and verifiability have long been regarded as cornerstones of the scientific ethos and practice. However, persistent reproducibility challenges across numerous disciplines have brought renewed attention to the imperative for widespread adoption of open science practices. These considerations are particularly relevant to the research field of indoor positioning. Open data and open code sharing are gradually gaining traction in the field, but are still far from standard practice. This study comprehensively evaluates the extent of the adoption of open science practices within the community of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), by systematically analyzing all reference papers from the 2019 to 2024 editions of the IPIN. The work thoroughly examines the open data and code usage, and the use of other types of open materials while performing a particular close-up review of the open data that are leveraged in these studies. Our findings reveal that 21.7% of papers use open research data, 8.3% utilize open code, and 20.2% incorporate other open materials. However, only 6.8% of papers provide both open data and code. Moreover, emerging patterns and intuitive best practices are highlighted. The complete characterization of all reviewed publications is publicly available. This study brings to light the need for wider adoption of open science practices, to enhance the transparency, reproducibility, replicability, and reliability of research outcomes in the field of indoor positioning.Source: IEEE JOURNAL OF INDOOR AND SEAMLESS POSITIONING AND NAVIGATION, vol. 3, pp. 175-194
DOI: 10.1109/jispin.2025.3570258
DOI: 10.5281/zenodo.14931103
DOI: 10.5281/zenodo.14931104
Metrics:
See at:
IEEE Journal of Indoor and Seamless Positioning and Navigation 
| CNR IRIS | ieeexplore.ieee.org | ZENODO | ZENODO | ZENODO | CNR IRIS
2025
Journal article
Open Access
Challenges in using pupil dilation responses to sounds as a reliable alternative to standard audiometric tests
Tramonti Fantozzi M. P., Crivello A., La Rosa D., Milazzo M., Danti S., De Cicco V., Orsini P., Manzoni D., Lazzerini F., Canelli R., Fiacchini G., Bruschini L.
Assessing hearing in neonates and uncooperative patients can be challenging. Pupil dilation response (PDR) as an objective physiological measure may offer a solution. To test its feasibility, PDRs were averaged in response to a sequence of 60–100 audible tones (same frequency and amplitude). This was performed in subjects with normal hearing and communication abilities, who were exposed to two different lighting levels. We evaluated whether averaged post-stimulus intervals of PDRs were significantly different from randomly generated averages of pupil traces recorded in the absence of sound stimulation from the same subject. This analysis was repeated for the first, second, and third block of PDRs to account for possible adaptation phenomena. Although all the participants clearly perceived the tones, significant PDRs in response to sound were only detected in a fraction of subjects, primarily in the low luminance condition. Consequently, only in the low luminance group, the grand average of individual PDRs was significantly larger than that obtained for traces recorded in the absence of sound input. In this most favorable condition, when the three blocks of PDRs were averaged separately, significant PDRs were observed in 40 % of the subjects in at least one of the blocks. Therefore, the PDR to sound input is not a reliable indicator of hearing perception when standard audiometric stimuli of the same amplitude and frequency are used. Possible modifications to sound input and stimulation protocols for obtaining reliable PDRs in diagnosing and treating hearing impairments are discussed.Source: HELIYON, vol. 11 (issue 4)
DOI: 10.1016/j.heliyon.2025.e42666
Project(s): APURE - Audiometry with PUpil REsponse
Metrics:
Tramonti Fantozzi M. P., Crivello A., La Rosa D., Milazzo M., Danti S., De Cicco V., Orsini P., Manzoni D., Lazzerini F., Canelli R., Fiacchini G., Bruschini L.
Assessing hearing in neonates and uncooperative patients can be challenging. Pupil dilation response (PDR) as an objective physiological measure may offer a solution. To test its feasibility, PDRs were averaged in response to a sequence of 60–100 audible tones (same frequency and amplitude). This was performed in subjects with normal hearing and communication abilities, who were exposed to two different lighting levels. We evaluated whether averaged post-stimulus intervals of PDRs were significantly different from randomly generated averages of pupil traces recorded in the absence of sound stimulation from the same subject. This analysis was repeated for the first, second, and third block of PDRs to account for possible adaptation phenomena. Although all the participants clearly perceived the tones, significant PDRs in response to sound were only detected in a fraction of subjects, primarily in the low luminance condition. Consequently, only in the low luminance group, the grand average of individual PDRs was significantly larger than that obtained for traces recorded in the absence of sound input. In this most favorable condition, when the three blocks of PDRs were averaged separately, significant PDRs were observed in 40 % of the subjects in at least one of the blocks. Therefore, the PDR to sound input is not a reliable indicator of hearing perception when standard audiometric stimuli of the same amplitude and frequency are used. Possible modifications to sound input and stimulation protocols for obtaining reliable PDRs in diagnosing and treating hearing impairments are discussed.Source: HELIYON, vol. 11 (issue 4)
DOI: 10.1016/j.heliyon.2025.e42666
Project(s): APURE - Audiometry with PUpil REsponse
Metrics:
See at:
Heliyon | Archivio della Ricerca - Università di Pisa | CNR IRIS | Heliyon | www.sciencedirect.com | Archivio della Ricerca - Università di Pisa | CNR IRIS
2025
Journal article
Open Access
StepLogger and EvaalScore: the software suite of the IPIN onsite indoor localization competition
Girolami M., Baronti P., Potortì F., Crivello A., Palumbo F.
This paper illustrates the software suite developed for Track 1 of the IPIN competition, which evaluates smartphone apps for indoor localization. Competitors have one day before the trial day to survey the competition area. On the trial day, an independent “actor” carries the competing system on smartphone and walks a predefined path. Competing systems provide continuous location estimates, which are later compared to a ground truth. We describe the software suite used to gather and present the results: the StepLogger Android application for real-time logging of position estimates and the EvaalScore tool for performance evaluation. StepLogger collects location estimating data from competitors with a timestamp, while EvaalScore calculates the accuracy of the competing systems. The competition ranking is based on the third quartile of point localization error. The presented software suite ensures a standardized and fair assessment of competing systems, thus promoting reproducibility and transparency in indoor localization research.Source: SOFTWAREX, vol. 30
DOI: 10.1016/j.softx.2025.102115
Project(s): Age-IT
Metrics:
Girolami M., Baronti P., Potortì F., Crivello A., Palumbo F.
This paper illustrates the software suite developed for Track 1 of the IPIN competition, which evaluates smartphone apps for indoor localization. Competitors have one day before the trial day to survey the competition area. On the trial day, an independent “actor” carries the competing system on smartphone and walks a predefined path. Competing systems provide continuous location estimates, which are later compared to a ground truth. We describe the software suite used to gather and present the results: the StepLogger Android application for real-time logging of position estimates and the EvaalScore tool for performance evaluation. StepLogger collects location estimating data from competitors with a timestamp, while EvaalScore calculates the accuracy of the competing systems. The competition ranking is based on the third quartile of point localization error. The presented software suite ensures a standardized and fair assessment of competing systems, thus promoting reproducibility and transparency in indoor localization research.Source: SOFTWAREX, vol. 30
DOI: 10.1016/j.softx.2025.102115
Project(s): Age-IT
Metrics:
See at:
CNR IRIS | www.sciencedirect.com | CNR IRIS | CNR IRIS
2025
Journal article
Open Access
ORDIP: Principle, practice and guidelines for open research data in indoor positioning
Anagnostopoulos G. G., Barsocchi P., Crivello A., Pendão C., Silva I., Torres-Sospedra J.
The community of indoor positioning research has identified the need for a paradigm shift towards more reproducible and open research dissemination. Despite recent efforts to openly share data and code, accompanying research results with Open Research Data (ORD) is far from being the de facto standard option for publications in the indoor positioning field. The lack of recognized public benchmarks and the rather slow adoption of ORD, set a great volume of astute contributions in the field to remain irreproducible. Performance comparisons may often be made on experiments performed in different settings, hindering their consistency, and eventually slowing down progress and the evolution of knowledge in the field. In this work, we systematically review the landscape of Open Research Data in Indoor Positioning, enlisting, presenting, and analyzing the characteristic features of the relevant available open datasets of the field. As a result of our systematic review, the statistical analysis of the 119 identified open datasets, highlights the tendencies and the missing elements, such as underrepresented technologies (such as Ultra-Wideband) and measurement types (such as Angle of Arrival, Time Difference of Arrival). A result that stands out is the frequency of crucial metadata information that remains undefined, such as the size of the area of collection (50% of the datasets), the ground truth collection protocol (21%), or the environment type (13%). As a fruit of the systematic analysis, we discuss potential shortcomings, and we share lessons learned and observed good practices regarding the provision of a new ORD and the reuse of existing ones. A significant practical contribution of this work is a list of guidelines that researchers aiming to collect and share a new ORD can follow as a simple checklist. In a broader context, we consider that ORDIP can help measure the future progress of the Indoor Positioning field in the ORD front through the snapshot of the current landscape that it provides. The Open provision of our full systematic analysis of the ORDs (Anagnostopoulos et al., 2024) can serve as a look-up table for easy access to the ORDs containing the most relevant features for each interested researcher, while our guidelines aim to support the community and spark the discussion towards a consensus-based standard for ORD of the field.Source: INTERNET OF THINGS
DOI: 10.1016/j.iot.2024.101485
Project(s): European Union - Next Generation EU, in the context of The National Recovery and Resilience Plan, Investment Partenariato Esteso PE8 “Conseguenze e sfide dell’invecchiamento”, Project Age-IT, CUP: B83C22004880006
Metrics:
Anagnostopoulos G. G., Barsocchi P., Crivello A., Pendão C., Silva I., Torres-Sospedra J.
The community of indoor positioning research has identified the need for a paradigm shift towards more reproducible and open research dissemination. Despite recent efforts to openly share data and code, accompanying research results with Open Research Data (ORD) is far from being the de facto standard option for publications in the indoor positioning field. The lack of recognized public benchmarks and the rather slow adoption of ORD, set a great volume of astute contributions in the field to remain irreproducible. Performance comparisons may often be made on experiments performed in different settings, hindering their consistency, and eventually slowing down progress and the evolution of knowledge in the field. In this work, we systematically review the landscape of Open Research Data in Indoor Positioning, enlisting, presenting, and analyzing the characteristic features of the relevant available open datasets of the field. As a result of our systematic review, the statistical analysis of the 119 identified open datasets, highlights the tendencies and the missing elements, such as underrepresented technologies (such as Ultra-Wideband) and measurement types (such as Angle of Arrival, Time Difference of Arrival). A result that stands out is the frequency of crucial metadata information that remains undefined, such as the size of the area of collection (50% of the datasets), the ground truth collection protocol (21%), or the environment type (13%). As a fruit of the systematic analysis, we discuss potential shortcomings, and we share lessons learned and observed good practices regarding the provision of a new ORD and the reuse of existing ones. A significant practical contribution of this work is a list of guidelines that researchers aiming to collect and share a new ORD can follow as a simple checklist. In a broader context, we consider that ORDIP can help measure the future progress of the Indoor Positioning field in the ORD front through the snapshot of the current landscape that it provides. The Open provision of our full systematic analysis of the ORDs (Anagnostopoulos et al., 2024) can serve as a look-up table for easy access to the ORDs containing the most relevant features for each interested researcher, while our guidelines aim to support the community and spark the discussion towards a consensus-based standard for ORD of the field.Source: INTERNET OF THINGS
DOI: 10.1016/j.iot.2024.101485
Project(s): European Union - Next Generation EU, in the context of The National Recovery and Resilience Plan, Investment Partenariato Esteso PE8 “Conseguenze e sfide dell’invecchiamento”, Project Age-IT, CUP: B83C22004880006
Metrics:
See at:
CNR IRIS | www.sciencedirect.com | CNR IRIS
2025
Conference article
Open Access
AI-Empowered IoT data collection via UAV in rural areas
Vo P. T., Giambene G., Barsocchi P., Crivello A.
Soil monitoring is essential for smart agriculture in remote rural areas with limited connectivity. It helps forecast regional runoff, soil erosion, and weather impacts while promoting more efficient irrigation. Current artificial intelligence (AI) methods often struggle to adapt to heterogeneous environments and limited connectivity. This study presents a vertical federated architecture called multi-head split learning (MHSL), utilizing AI-powered devices onboard Unmanned Aerial Vehicles (UAVs) mission that is designed to increase awareness of in-situ soil moisture collected data to forecast environmental trends for enhanced monitoring in rural areas. Our architecture connects the local convolutional neural network (CNN) head model of multiple worker UAVs to the long-short-term memory (LSTM) tail model of a central master UAV, creating a global model. This is made possible by adopting GPUs onboard and WiFi connectivity among UAVs. To validate our approach, we have used the real datasets of the TERENO-Wüstebach network. The numerical results show that our CNN-LSTM approach can forecast the SSM data for the next days with sufficient accuracy measured in terms of mean square error (MSE). The good performance of CNN-LSTM has been supported by comparisons with other schemes in the literature.DOI: 10.1109/infocomwkshps65812.2025.11152890
Metrics:
Vo P. T., Giambene G., Barsocchi P., Crivello A.
Soil monitoring is essential for smart agriculture in remote rural areas with limited connectivity. It helps forecast regional runoff, soil erosion, and weather impacts while promoting more efficient irrigation. Current artificial intelligence (AI) methods often struggle to adapt to heterogeneous environments and limited connectivity. This study presents a vertical federated architecture called multi-head split learning (MHSL), utilizing AI-powered devices onboard Unmanned Aerial Vehicles (UAVs) mission that is designed to increase awareness of in-situ soil moisture collected data to forecast environmental trends for enhanced monitoring in rural areas. Our architecture connects the local convolutional neural network (CNN) head model of multiple worker UAVs to the long-short-term memory (LSTM) tail model of a central master UAV, creating a global model. This is made possible by adopting GPUs onboard and WiFi connectivity among UAVs. To validate our approach, we have used the real datasets of the TERENO-Wüstebach network. The numerical results show that our CNN-LSTM approach can forecast the SSM data for the next days with sufficient accuracy measured in terms of mean square error (MSE). The good performance of CNN-LSTM has been supported by comparisons with other schemes in the literature.DOI: 10.1109/infocomwkshps65812.2025.11152890
Metrics:
See at:
CNR IRIS | ieeexplore.ieee.org | CNR IRIS
2025
Journal article
Open Access
MCSim: A multi-access edge computing mobile crowdsensing simulator
Belli D., Barsocchi P., Crivello A., La Rosa D., Girolami M.
This paper introduces MCSim, a modular and extensible simulator designed to support the planning and evaluation of Mobile CrowdSensing (MCS) campaigns in urban environments. MCSim integrates a useful approximation of urban mobility patterns based on real-world street networks, as well as the simulation of task execution effectiveness within configurable data transmission ranges. Unlike other simulators, MCSim is built to accommodate future extensions, such as edge/fog computing architectures. The current version of the software offers a user-friendly interface, customizable configuration options, and robust output analysis. By combining realistic mobility modeling, configurable task logic, and architectural flexibility, MCSim provides researchers and practitioners with a powerful tool for optimizing MCS strategies while minimizing deployment costs and risks.Source: SOFTWAREX, vol. 31 (issue 102229)
DOI: 10.1016/j.softx.2025.102229
Project(s): Cyber and Human Intelligence for Physical Systems
Metrics:
Belli D., Barsocchi P., Crivello A., La Rosa D., Girolami M.
This paper introduces MCSim, a modular and extensible simulator designed to support the planning and evaluation of Mobile CrowdSensing (MCS) campaigns in urban environments. MCSim integrates a useful approximation of urban mobility patterns based on real-world street networks, as well as the simulation of task execution effectiveness within configurable data transmission ranges. Unlike other simulators, MCSim is built to accommodate future extensions, such as edge/fog computing architectures. The current version of the software offers a user-friendly interface, customizable configuration options, and robust output analysis. By combining realistic mobility modeling, configurable task logic, and architectural flexibility, MCSim provides researchers and practitioners with a powerful tool for optimizing MCS strategies while minimizing deployment costs and risks.Source: SOFTWAREX, vol. 31 (issue 102229)
DOI: 10.1016/j.softx.2025.102229
Project(s): Cyber and Human Intelligence for Physical Systems
Metrics:
See at:
SoftwareX | SoftwareX | CNR IRIS | www.sciencedirect.com | CNR IRIS | CNR IRIS
2025
Conference article
Restricted
Performing audiometry using pupillometry: state-of-the-market and sensor selection
Crivello A., La Rosa D., Belli D., Milazzo M., Palumbo F.
Hearing impairment poses a significant global health challenge, impacting millions of individuals across all age groups. Early detection and intervention are paramount, especially in infants and young children, to mitigate the adverse effects on speech, language, and cognitive development. Traditional audiometry methods, however, rely on subjective patient responses, rendering them unsuitable for non-collaborative individuals such as infants, newborns, and those with cognitive impairments. To address this limitation, the APURE (Audiometry with PUpil REsponse) project seeks to develop an objective audiometer leveraging pupillometry, the measurement of pupil size and reactivity. This paper presents a comprehensive state-of-the-market survey of eye-tracking systems, a crucial step in identifying the most suitable sensors for the APURE project.Source: LECTURE NOTES OF THE INSTITUTE FOR COMPUTER SCIENCES, SOCIAL INFORMATICS AND TELECOMMUNICATIONS ENGINEERING, vol. 612, pp. 159-169. Heraklion, Crete, Greece, 17–18/09/2024
DOI: 10.1007/978-3-031-85575-7_9
Metrics:
Crivello A., La Rosa D., Belli D., Milazzo M., Palumbo F.
Hearing impairment poses a significant global health challenge, impacting millions of individuals across all age groups. Early detection and intervention are paramount, especially in infants and young children, to mitigate the adverse effects on speech, language, and cognitive development. Traditional audiometry methods, however, rely on subjective patient responses, rendering them unsuitable for non-collaborative individuals such as infants, newborns, and those with cognitive impairments. To address this limitation, the APURE (Audiometry with PUpil REsponse) project seeks to develop an objective audiometer leveraging pupillometry, the measurement of pupil size and reactivity. This paper presents a comprehensive state-of-the-market survey of eye-tracking systems, a crucial step in identifying the most suitable sensors for the APURE project.Source: LECTURE NOTES OF THE INSTITUTE FOR COMPUTER SCIENCES, SOCIAL INFORMATICS AND TELECOMMUNICATIONS ENGINEERING, vol. 612, pp. 159-169. Heraklion, Crete, Greece, 17–18/09/2024
DOI: 10.1007/978-3-031-85575-7_9
Metrics:
See at:
CNR IRIS | CNR IRIS | CNR IRIS | link.springer.com
2024
Journal article
Open Access
Offsite evaluation of localization systems: criteria, systems and results from IPIN 2021-22 competitions
Potortì F., Crivello A.
Indoor positioning is a thriving research area which is slowly gaining market momentum. Its applications are mostly customised, ad hoc installations; ubiquitous applications analogous to GNSS for outdoors are not available because of the lack of generic platforms, widely accepted standards and interoperability protocols. In this context, the Indoor Positioning and Indoor Navigation (IPIN) competition is the only long-term, technically sound initiative to monitor the state of the art of real systems by measuring their performance in a realistic environment. Most competing systems are pedestrian-oriented and based on the use of smartphones, but several competing Tracks were set up, enabling comparison of an array of technologies. The two IPIN competitions described here include only off-site Tracks. In contrast with on-site Tracks where competitors bring their systems on site -- which were impossible to organise during 2021 and 2022 -- in off-site Tracks competitors download pre-recorded data from multiple sensors and process them using the EvaalAPI, a real-time, web-based emulation interface. As usual with IPIN competitions, Tracks were compliant with the EvAAL framework, ensuring consistency of the measurement procedure and reliability of results. The main contribution of this work is to show a compilation of possible indoor positioning scenarios and different indoor positioning solutions to the same problem.Source: IEEE JOURNAL OF INDOOR AND SEAMLESS POSITIONING AND NAVIGATION, vol. 2, pp. 92-129
DOI: 10.1109/jispin.2024.3355840
Metrics:
Potortì F., Crivello A.
Indoor positioning is a thriving research area which is slowly gaining market momentum. Its applications are mostly customised, ad hoc installations; ubiquitous applications analogous to GNSS for outdoors are not available because of the lack of generic platforms, widely accepted standards and interoperability protocols. In this context, the Indoor Positioning and Indoor Navigation (IPIN) competition is the only long-term, technically sound initiative to monitor the state of the art of real systems by measuring their performance in a realistic environment. Most competing systems are pedestrian-oriented and based on the use of smartphones, but several competing Tracks were set up, enabling comparison of an array of technologies. The two IPIN competitions described here include only off-site Tracks. In contrast with on-site Tracks where competitors bring their systems on site -- which were impossible to organise during 2021 and 2022 -- in off-site Tracks competitors download pre-recorded data from multiple sensors and process them using the EvaalAPI, a real-time, web-based emulation interface. As usual with IPIN competitions, Tracks were compliant with the EvAAL framework, ensuring consistency of the measurement procedure and reliability of results. The main contribution of this work is to show a compilation of possible indoor positioning scenarios and different indoor positioning solutions to the same problem.Source: IEEE JOURNAL OF INDOOR AND SEAMLESS POSITIONING AND NAVIGATION, vol. 2, pp. 92-129
DOI: 10.1109/jispin.2024.3355840
Metrics:
See at:
CNR IRIS | ieeexplore.ieee.org | CNR IRIS
2024
Journal article
Open Access
MOC: wi-fi FTM with motion observation chain for pervasive indoor positioning
Wenhua Shao, Haiyong Luo, Fang Zhao, Yunhan Hong, Yaqi Li, Chen Zhang, Bingzheng Sun, Antonino Crivello
The IEEE 802.11-2016 standard enables devices to gather precise ranging information through the time-of-flight evaluation, facilitating the development of accurate indoor location-based services. Researchers have indicated that the protocol’s most effective performance is in scenarios with direct line-of-sight, despite providing meter-level ranging accuracy. In real indoor environments, the accuracy diminishes considerably due to random errors caused by interference such as multipath effects and non-line-of-sight signal propagation. Therefore, it is essential to accurately evaluate the reliability of each ranging measurement and effectively leverage neighboring highquality observations to improve positioning accuracy. This study presents a novel optimization algorithm that relies on the motion observation series by incorporating adjacent ranging observations and a priori motion knowledge into a factor graph model, resulting in a unified optimization objective. Consequently, our system can dynamically estimate the confidence of fine time measurements ranging measurements. It optimizes the position estimation of the current user by maximizing the probability of not only the current ranging measurements but also the adjacent historical measurements and a priori motion. Additionally, to enable real-time positioning, a fast-solving procedure employing an adaptive gradient is proposed, capable of providing evaluations in under 10ms. The system has been tested in real indoor environments, showing improved performance compared to existing methods. It achieves meter-level realtime positioning accuracy at 1 sigma without requiring a specific device pose, additional sensor, or expensive site survey. This makes our proposal highly applicable for wide adoption and readiness for the market.Source: IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
DOI: 10.1109/tii.2024.3413342
Metrics:
Wenhua Shao, Haiyong Luo, Fang Zhao, Yunhan Hong, Yaqi Li, Chen Zhang, Bingzheng Sun, Antonino Crivello
The IEEE 802.11-2016 standard enables devices to gather precise ranging information through the time-of-flight evaluation, facilitating the development of accurate indoor location-based services. Researchers have indicated that the protocol’s most effective performance is in scenarios with direct line-of-sight, despite providing meter-level ranging accuracy. In real indoor environments, the accuracy diminishes considerably due to random errors caused by interference such as multipath effects and non-line-of-sight signal propagation. Therefore, it is essential to accurately evaluate the reliability of each ranging measurement and effectively leverage neighboring highquality observations to improve positioning accuracy. This study presents a novel optimization algorithm that relies on the motion observation series by incorporating adjacent ranging observations and a priori motion knowledge into a factor graph model, resulting in a unified optimization objective. Consequently, our system can dynamically estimate the confidence of fine time measurements ranging measurements. It optimizes the position estimation of the current user by maximizing the probability of not only the current ranging measurements but also the adjacent historical measurements and a priori motion. Additionally, to enable real-time positioning, a fast-solving procedure employing an adaptive gradient is proposed, capable of providing evaluations in under 10ms. The system has been tested in real indoor environments, showing improved performance compared to existing methods. It achieves meter-level realtime positioning accuracy at 1 sigma without requiring a specific device pose, additional sensor, or expensive site survey. This makes our proposal highly applicable for wide adoption and readiness for the market.Source: IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
DOI: 10.1109/tii.2024.3413342
Metrics:
See at:
IRIS Cnr | IRIS Cnr | IRIS Cnr | IEEE Transactions on Industrial Informatics | CNR IRIS
2024
Journal article
Open Access
What are data spaces? Systematic survey and future outlook
Bacco M., Kocian A., Chessa S., Crivello A., Barsocchi P.
Data spaces, a novel concept pushing data sharing and exchange, are experi- encing momentum because of recent developments motivated by the increas- ing need for interoperability and data sovereignty. After an initial phase, dating back to approximately twenty years ago, in which this concept has been tentatively explored in different scenarios, it is presently going through a consolidation phase in which both specifications and implementations con- verge towards a common reference for standardisation. In this context, we offer our view on data spaces by presenting a systematic literature survey, a description of the components needed to build them, how they work, and of existing mature software implementations. We thoroughly present the architectural vision behind the concept and we analyse the Reference Archi- tectural Model by IDS. We provide practical pointers to readers interested in experimenting with software components used in data spaces, and we con- clude by highlighting open challenges for their success.Source: DATA IN BRIEF
DOI: 10.1016/j.dib.2024.110969
Project(s): CODECS
Metrics:
Bacco M., Kocian A., Chessa S., Crivello A., Barsocchi P.
Data spaces, a novel concept pushing data sharing and exchange, are experi- encing momentum because of recent developments motivated by the increas- ing need for interoperability and data sovereignty. After an initial phase, dating back to approximately twenty years ago, in which this concept has been tentatively explored in different scenarios, it is presently going through a consolidation phase in which both specifications and implementations con- verge towards a common reference for standardisation. In this context, we offer our view on data spaces by presenting a systematic literature survey, a description of the components needed to build them, how they work, and of existing mature software implementations. We thoroughly present the architectural vision behind the concept and we analyse the Reference Archi- tectural Model by IDS. We provide practical pointers to readers interested in experimenting with software components used in data spaces, and we con- clude by highlighting open challenges for their success.Source: DATA IN BRIEF
DOI: 10.1016/j.dib.2024.110969
Project(s): CODECS
Metrics:
See at:
Data in Brief | IRIS Cnr | IRIS Cnr | Archivio della Ricerca - Università di Pisa | Archivio della Ricerca - Università di Pisa | CNR IRIS
2024
Journal article
Open Access
Public irrigation decision support systems (IDSS) in Italy: description, evaluation and national context overview
Sportelli M., Crivello A., Bacco M., Rallo G., Brunori G.
This survey comprehensively examines the public irrigation decision support systems (IDSS) in Italy, offering a detailed description, analysis and evaluation of their features. The study investigates the agrometeorological networks and infrastructures that support Italian IDSS, providing a clearer understanding of the national context. The evaluation criteria include relevant factors such as soil moisture monitoring, crop water requirements (CWR) estimation models, biophysical parameters along with their spatial and temporal resolutions, irrigation planning and decision support visualization. Additionally, the assessment covers accessibility, scalability and interoperability of these systems. The survey also highlights the strengths and weaknesses of various IDSS, such as IRRIFRAME, IRRISIAS and IRTO, discussing their operational methodologies, data integration and regional coverage. The aim is to provide insights that facilitate advancements in sustainable irrigation management practices and address key challenges for future developments at both regional and national levels. This comprehensive evaluation seeks to enhance the effectiveness of IDSS in promoting sustainable water management in agriculture across Italy.Source: SMART AGRICULTURAL TECHNOLOGY, vol. 9
DOI: 10.1016/j.atech.2024.100564
Metrics:
Sportelli M., Crivello A., Bacco M., Rallo G., Brunori G.
This survey comprehensively examines the public irrigation decision support systems (IDSS) in Italy, offering a detailed description, analysis and evaluation of their features. The study investigates the agrometeorological networks and infrastructures that support Italian IDSS, providing a clearer understanding of the national context. The evaluation criteria include relevant factors such as soil moisture monitoring, crop water requirements (CWR) estimation models, biophysical parameters along with their spatial and temporal resolutions, irrigation planning and decision support visualization. Additionally, the assessment covers accessibility, scalability and interoperability of these systems. The survey also highlights the strengths and weaknesses of various IDSS, such as IRRIFRAME, IRRISIAS and IRTO, discussing their operational methodologies, data integration and regional coverage. The aim is to provide insights that facilitate advancements in sustainable irrigation management practices and address key challenges for future developments at both regional and national levels. This comprehensive evaluation seeks to enhance the effectiveness of IDSS in promoting sustainable water management in agriculture across Italy.Source: SMART AGRICULTURAL TECHNOLOGY, vol. 9
DOI: 10.1016/j.atech.2024.100564
Metrics:
See at:
Smart Agricultural Technology | Smart Agricultural Technology | IRIS Cnr | IRIS Cnr | Archivio della Ricerca - Università di Pisa | Archivio della Ricerca - Università di Pisa | CNR IRIS
2024
Conference article
Open Access
Agricultural Data Space: the METRIQA platform and a case study in the CODECS project
Bacco M., Dimitri G. M., Kocian A., Barsocchi P., Crivello A., Brunori G., Gori M., Chessa S.
This work describes the ongoing design and devel- opment of the METRIQA platform, hosting the Italian agrifood data space. Both are key components that the Italian National Research Centre for Agricultural Technologies is putting forward in its activities. We present a high-level description of the platform, which is designed to provide web-like access to digital resources and services following an approach called Web of Agri-Food, to support the digital transformation of the sector in Italy. To show its potential, we also present a real case study demonstrating both the benefits and impacts of the proposed architecture, connecting stakeholders and authorities at different levels.Source: ANNALS OF COMPUTER SCIENCE AND INFORMATION SYSTEMS, vol. 39, pp. 543-548. Belgrade, Serbia, 8-11/09/2024
DOI: 10.15439/2024f5291
Metrics:
Bacco M., Dimitri G. M., Kocian A., Barsocchi P., Crivello A., Brunori G., Gori M., Chessa S.
This work describes the ongoing design and devel- opment of the METRIQA platform, hosting the Italian agrifood data space. Both are key components that the Italian National Research Centre for Agricultural Technologies is putting forward in its activities. We present a high-level description of the platform, which is designed to provide web-like access to digital resources and services following an approach called Web of Agri-Food, to support the digital transformation of the sector in Italy. To show its potential, we also present a real case study demonstrating both the benefits and impacts of the proposed architecture, connecting stakeholders and authorities at different levels.Source: ANNALS OF COMPUTER SCIENCE AND INFORMATION SYSTEMS, vol. 39, pp. 543-548. Belgrade, Serbia, 8-11/09/2024
DOI: 10.15439/2024f5291
Metrics:
See at:
annals-csis.org | Annals of computer science and information systems | CNR IRIS | CNR IRIS
2024
Conference article
Open Access
Inclusive navigation systems: perspectives and challenges for the visually-impaired
Belli D., Barsocchi P., Crivello A., Furfari F., Leporini B., Paratore M. T.
Despite significant advances in technology, the area of mobility and orientation for visually impaired persons continues to present significant challenges. Digital maps have become essential for navigation, but their usability is often compromised for users who rely on assistive technologies, especially when accessed on small touch screens. This calls for innovative approaches to making digital maps more accessible and usable, as these tools are crucial for creating mental maps of navigational spaces. This paper explores the need for inclusive localization and positioning systems that accommodate a wide range of users, including those with visual impairments. It highlights the critical role of user context, such as device experience and positional awareness, in improving the usability of these systems. The integration of haptic and audio feedback may offer promising new interaction methods, although further development is needed. In addition, user interface design and system characteristics such as security, robustness and usability need to be aligned with user acceptance, with a focus on low cost and simplicity. Our analysis identifies key requirements for the design of inclusive systems and proposes steps for the scientific community to take to advance the field, with the aim of bridging the gap between technological capabilities and practical usability, and promoting inclusive design principles for future innovation.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3919. Hong Kong, China, 14-15/102024
Belli D., Barsocchi P., Crivello A., Furfari F., Leporini B., Paratore M. T.
Despite significant advances in technology, the area of mobility and orientation for visually impaired persons continues to present significant challenges. Digital maps have become essential for navigation, but their usability is often compromised for users who rely on assistive technologies, especially when accessed on small touch screens. This calls for innovative approaches to making digital maps more accessible and usable, as these tools are crucial for creating mental maps of navigational spaces. This paper explores the need for inclusive localization and positioning systems that accommodate a wide range of users, including those with visual impairments. It highlights the critical role of user context, such as device experience and positional awareness, in improving the usability of these systems. The integration of haptic and audio feedback may offer promising new interaction methods, although further development is needed. In addition, user interface design and system characteristics such as security, robustness and usability need to be aligned with user acceptance, with a focus on low cost and simplicity. Our analysis identifies key requirements for the design of inclusive systems and proposes steps for the scientific community to take to advance the field, with the aim of bridging the gap between technological capabilities and practical usability, and promoting inclusive design principles for future innovation.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3919. Hong Kong, China, 14-15/102024
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2024
Journal article
Open Access
Pupil data upon stimulation by auditory stimuli
Davide La Rosa, Luca Bruschini, Maria Paola Tramonti Fantozzi, Paolo Orsini, Mario Milazzo, Antonino Crivello
Source: DATA, vol. 9 (issue 3)
DOI: 10.3390/data9030043
Project(s): Apure - Audiometry with pupil response
Metrics:
Davide La Rosa, Luca Bruschini, Maria Paola Tramonti Fantozzi, Paolo Orsini, Mario Milazzo, Antonino Crivello
Source: DATA, vol. 9 (issue 3)
DOI: 10.3390/data9030043
Project(s): Apure - Audiometry with pupil response
Metrics:
See at:
Data | IRIS Cnr | IRIS Cnr | IRIS Cnr | Archivio della Ricerca - Università di Pisa | Archivio della Ricerca - Università di Pisa | CNR IRIS
2023
Conference article
Open Access
Let's talk about k-NN for indoor positioning: myths and facts in RF-based fingerprinting
Torressospedra J, Pendão C, Silva I, Meneses F, Quezadagaibor D, Montoliu R, Crivello A, Barsocchi P, Péreznavarro A, Moreira A
Microsoft proposed RADAR in 2000, the first indoor positioning system based on Wi-Fi fingerprinting. Since then, the indoor research community has worked not only to improve the base estimator but also on finding an optimal RSS data representation. The long-term objective is to find a positioning system that minimises the mean positioning error. Despite the relevant advances in the last 23 years, a disruptive solution has not been reached yet. The evaluation with non-open datasets and comparisons with non-optimized baselines make the analysis of the current status of fingerprinting for indoor positioning difficult. In addition, the lack of implementation details or data used for evaluation in several works make results reproducibility impossible. This paper focuses on providing a comprehensive analysis of fingerprinting with k-NN and settling the basement for replicability and reproducibility in further works, targeting to bring relevant information about k-NN when it is used as a baseline comparison of advanced fingerprint-based methods.DOI: 10.1109/ipin57070.2023.10332535
Metrics:
Torressospedra J, Pendão C, Silva I, Meneses F, Quezadagaibor D, Montoliu R, Crivello A, Barsocchi P, Péreznavarro A, Moreira A
Microsoft proposed RADAR in 2000, the first indoor positioning system based on Wi-Fi fingerprinting. Since then, the indoor research community has worked not only to improve the base estimator but also on finding an optimal RSS data representation. The long-term objective is to find a positioning system that minimises the mean positioning error. Despite the relevant advances in the last 23 years, a disruptive solution has not been reached yet. The evaluation with non-open datasets and comparisons with non-optimized baselines make the analysis of the current status of fingerprinting for indoor positioning difficult. In addition, the lack of implementation details or data used for evaluation in several works make results reproducibility impossible. This paper focuses on providing a comprehensive analysis of fingerprinting with k-NN and settling the basement for replicability and reproducibility in further works, targeting to bring relevant information about k-NN when it is used as a baseline comparison of advanced fingerprint-based methods.DOI: 10.1109/ipin57070.2023.10332535
Metrics:
See at:
CNR IRIS | ieeexplore.ieee.org | ISTI Repository | CNR IRIS | CNR IRIS
2023
Other
Restricted
ChAALenge D6.3 - Integrazione in laboratorio e analisi delle prestazioni
Bacco F. M., Baronti P., Barsocchi P., Belli D., Crivello A., Furfari F., Girolami M., La Rosa D., Mavilia F., Miori V., Palumbo F., Potortì F., Russo D.
Report di laboratorio di analisi dei risultati dell’integrazione e indagine prestazionale sul framework integrato contenente: (i) Risultati attinenti alla validità dei dati acquisiti dal framework, al fine del loro efficiente utilizzo da parte degli algoritmi sviluppati; (ii) Risultati riguardanti la correttezza, completezza e affidabilità dell’esito della sperimentazione sia in laboratorio sia sul campo e relativi alla valutazione prestazionale del software di sistema.Project(s): ChAALenge
Bacco F. M., Baronti P., Barsocchi P., Belli D., Crivello A., Furfari F., Girolami M., La Rosa D., Mavilia F., Miori V., Palumbo F., Potortì F., Russo D.
Report di laboratorio di analisi dei risultati dell’integrazione e indagine prestazionale sul framework integrato contenente: (i) Risultati attinenti alla validità dei dati acquisiti dal framework, al fine del loro efficiente utilizzo da parte degli algoritmi sviluppati; (ii) Risultati riguardanti la correttezza, completezza e affidabilità dell’esito della sperimentazione sia in laboratorio sia sul campo e relativi alla valutazione prestazionale del software di sistema.Project(s): ChAALenge
2022
Conference article
Open Access
Trends in smartphone-based indoor localisation
Potortì F., Crivello A., Palumbo F., Girolami M., Barsocchi P.
Indoor localisation is a thriving field, whose progresses are mainly led by innovations in sensor technology, both hardware and software. With a focus on smartphone-based personal navigation, we examine the evolution of sensing technologies in eleven leading applications. In order to select applications we choose among independently-tested prototypes, as opposed to simulation or laboratory-only experiments. To this end, we look at the best performers in the smartphone-based Tracks of IPIN competitions. This selection is particularly severe and significant, as this competition Track is performed live, without an opportunity for competitors to instrument or prepare the site or to know the path in advance and with only two attempts allowed, of which the best result is taken. An independent actor holds in hand the smartphone running the competing system, and results are downloaded from the phone immediately after the competition path is completed, without any post-processing. We show how sensing technologies have evolved from 2014 to 2019 and show a trend towards improving accuracy performance. Last, we provide insight in the role that sensors and algorithms play in the evolution of smartphone-based indoor localisation solutions.DOI: 10.1109/ipin51156.2021.9662530
Metrics:
Potortì F., Crivello A., Palumbo F., Girolami M., Barsocchi P.
Indoor localisation is a thriving field, whose progresses are mainly led by innovations in sensor technology, both hardware and software. With a focus on smartphone-based personal navigation, we examine the evolution of sensing technologies in eleven leading applications. In order to select applications we choose among independently-tested prototypes, as opposed to simulation or laboratory-only experiments. To this end, we look at the best performers in the smartphone-based Tracks of IPIN competitions. This selection is particularly severe and significant, as this competition Track is performed live, without an opportunity for competitors to instrument or prepare the site or to know the path in advance and with only two attempts allowed, of which the best result is taken. An independent actor holds in hand the smartphone running the competing system, and results are downloaded from the phone immediately after the competition path is completed, without any post-processing. We show how sensing technologies have evolved from 2014 to 2019 and show a trend towards improving accuracy performance. Last, we provide insight in the role that sensors and algorithms play in the evolution of smartphone-based indoor localisation solutions.DOI: 10.1109/ipin51156.2021.9662530
Metrics:
See at:
CNR IRIS | ieeexplore.ieee.org | ISTI Repository | CNR IRIS | CNR IRIS
2022
Journal article
Open Access
The NESTORE e-coach: designing a multi-domain pathway to well-being in older age
Angelini L., El Kamali M., Mugellini E., Abou Khaled O., Roecke C., Porcelli S., Mastropietro A., Rizzo G., Boque N., Del Bas J. M., Palumbo F., Girolami M., Crivello A., Ziylan C., Subias-Beltran P., Orte S., Standoli C. E., Fernandez Maldonado L., Caon M., Sykora M., Elayan S., Guye S., Andreoni G.
This article describes the coaching strategies of the NESTORE e-coach, a virtual coach for promoting healthier lifestyles in older age. The novelty of the NESTORE project is the definition of a multi-domain personalized pathway where the e-coach accompanies the user throughout different structured and non-structured coaching activities and recommendations. The article also presents the design process of the coaching strategies, carried out including older adults from four European countries and experts from the different health domains, and the results of the tests carried out with 60 older adults in Italy, Spain and The Netherlands.Source: TECHNOLOGIES, vol. 10 (issue 2)
DOI: 10.3390/technologies10020050
Project(s): NESTORE
Metrics:
Angelini L., El Kamali M., Mugellini E., Abou Khaled O., Roecke C., Porcelli S., Mastropietro A., Rizzo G., Boque N., Del Bas J. M., Palumbo F., Girolami M., Crivello A., Ziylan C., Subias-Beltran P., Orte S., Standoli C. E., Fernandez Maldonado L., Caon M., Sykora M., Elayan S., Guye S., Andreoni G.
This article describes the coaching strategies of the NESTORE e-coach, a virtual coach for promoting healthier lifestyles in older age. The novelty of the NESTORE project is the definition of a multi-domain personalized pathway where the e-coach accompanies the user throughout different structured and non-structured coaching activities and recommendations. The article also presents the design process of the coaching strategies, carried out including older adults from four European countries and experts from the different health domains, and the results of the tests carried out with 60 older adults in Italy, Spain and The Netherlands.Source: TECHNOLOGIES, vol. 10 (issue 2)
DOI: 10.3390/technologies10020050
Project(s): NESTORE
Metrics:
See at:
CNR IRIS | ISTI Repository | www.mdpi.com | CNR IRIS
2022
Journal article
Open Access
Experimental assessment of cuff pressures on the walls of a trachea-like model using force sensing resistors: insights for patient management in intensive care unit settings
Crivello A., Milazzo M., La Rosa D., Fiacchini G., Danti S., Guarracino F., Berrettini S., Bruschini L.
The COVID-19 outbreak has increased the incidence of tracheal lesions in patients who underwent invasive mechanical ventilation. We measured the pressure exerted by the cuff on the walls of a test bench mimicking the laryngotracheal tract. The test bench was designed to acquire the pressure exerted by endotracheal tube cuffs inflated inside an artificial model of a human trachea. The experimental protocol consisted of measuring pressure values before and after applying a maneuver on two types of endotracheal tubes placed in two mock-ups resembling two different sized tracheal tracts. Increasing pressure values were used to inflate the cuff and the pressures were recorded in two different body positions. The recorded pressure increased proportionally to the input pressure. Moreover, the pressure values measured when using the non-armored (NA) tube were usually higher than those recorded when using the armored (A) tube. A periodic check of the cuff pressure upon changing the body position and/or when performing maneuvers on the tube appears to be necessary to prevent a pressure increase on the tracheal wall. In addition, in our model, the cuff of the A tube gave a more stable output pressure on the tracheal wall than that of the NA tube.Source: SENSORS (BASEL), vol. 22 (issue 2)
DOI: 10.3390/s22020697
Metrics:
Crivello A., Milazzo M., La Rosa D., Fiacchini G., Danti S., Guarracino F., Berrettini S., Bruschini L.
The COVID-19 outbreak has increased the incidence of tracheal lesions in patients who underwent invasive mechanical ventilation. We measured the pressure exerted by the cuff on the walls of a test bench mimicking the laryngotracheal tract. The test bench was designed to acquire the pressure exerted by endotracheal tube cuffs inflated inside an artificial model of a human trachea. The experimental protocol consisted of measuring pressure values before and after applying a maneuver on two types of endotracheal tubes placed in two mock-ups resembling two different sized tracheal tracts. Increasing pressure values were used to inflate the cuff and the pressures were recorded in two different body positions. The recorded pressure increased proportionally to the input pressure. Moreover, the pressure values measured when using the non-armored (NA) tube were usually higher than those recorded when using the armored (A) tube. A periodic check of the cuff pressure upon changing the body position and/or when performing maneuvers on the tube appears to be necessary to prevent a pressure increase on the tracheal wall. In addition, in our model, the cuff of the A tube gave a more stable output pressure on the tracheal wall than that of the NA tube.Source: SENSORS (BASEL), vol. 22 (issue 2)
DOI: 10.3390/s22020697
Metrics:
See at:
CNR IRIS | ISTI Repository | www.mdpi.com | CNR IRIS