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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.Source: IPIN 2021 - International conference on Indoor Positioning and Indoor Navigation, Lloret de Mar, 29/11/2021-02/12/2021
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.Source: IPIN 2021 - International conference on Indoor Positioning and Indoor Navigation, Lloret de Mar, 29/11/2021-02/12/2021
DOI: 10.1109/ipin51156.2021.9662530
Metrics:
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ISTI Repository 
| ieeexplore.ieee.org 
| CNR ExploRA
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 (Basel) 10 (2022). doi:10.3390/technologies10020050
DOI: 10.3390/technologies10020050
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 (Basel) 10 (2022). doi:10.3390/technologies10020050
DOI: 10.3390/technologies10020050
Metrics:
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ISTI Repository | CNR ExploRA | www.mdpi.com
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) 22 (2022). doi:10.3390/s22020697
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) 22 (2022). doi:10.3390/s22020697
DOI: 10.3390/s22020697
Metrics:
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ISTI Repository | CNR ExploRA | www.mdpi.com
2022
Conference article
Open Access
A sensing platform to monitor sleep efficiency
Crivello A., La Rosa D., Wilhelm E., Palumbo F.
Sleep plays a fundamental role in the human life. Sleep research is mainly focused on the understanding of the sleep patterns, stages and duration. An accurate sleep monitoring can detect early signs of sleep deprivation and insomnia consequentially implementing mechanisms for preventing and overcoming these problems. Recently, sleep monitoring has been achieved using wearable technologies, able to analyse also the body movements, but old people can encounter some difficulties in using and maintaining these devices. In this paper, we propose an unobtrusive sensing platform able to analyze body movements, infer sleep duration and awakenings occurred along the night, and evaluating the sleep efficiency index. To prove the feasibility of the suggested method we did a pilot trial in which several healthy users have been involved. The sensors were installed within the bed and, on each day, each user was administered with the Groningen Sleep Quality Scale questionnaire to evaluate the user's perceived sleep quality. Finally, we show potential correlation between a perceived evaluation with an objective index as the sleep efficiency.Source: ForItAAL 2020 - Italian Forum of Ambient Assisted Living, pp. 335–345, 01/12/2020
DOI: 10.1007/978-3-031-08838-4_23
Metrics:
Crivello A., La Rosa D., Wilhelm E., Palumbo F.
Sleep plays a fundamental role in the human life. Sleep research is mainly focused on the understanding of the sleep patterns, stages and duration. An accurate sleep monitoring can detect early signs of sleep deprivation and insomnia consequentially implementing mechanisms for preventing and overcoming these problems. Recently, sleep monitoring has been achieved using wearable technologies, able to analyse also the body movements, but old people can encounter some difficulties in using and maintaining these devices. In this paper, we propose an unobtrusive sensing platform able to analyze body movements, infer sleep duration and awakenings occurred along the night, and evaluating the sleep efficiency index. To prove the feasibility of the suggested method we did a pilot trial in which several healthy users have been involved. The sensors were installed within the bed and, on each day, each user was administered with the Groningen Sleep Quality Scale questionnaire to evaluate the user's perceived sleep quality. Finally, we show potential correlation between a perceived evaluation with an objective index as the sleep efficiency.Source: ForItAAL 2020 - Italian Forum of Ambient Assisted Living, pp. 335–345, 01/12/2020
DOI: 10.1007/978-3-031-08838-4_23
Metrics:
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ISTI Repository | doi.org | link.springer.com | CNR ExploRA
2022
Journal article
Open Access
Sensing devices for detecting and processing acoustic signals in healthcare
Mallegni N., Molinari G., Ricci C., Lazzeri A., La Rosa D., Crivello A., Milazzo M.
Acoustic signals are important markers to monitor physiological and pathological conditions, e.g., heart and respiratory sounds. The employment of traditional devices, such as stethoscopes, has been progressively superseded by new miniaturized devices, usually identified as microelectromechanical systems (MEMS). These tools are able to better detect the vibrational content of acoustic signals in order to provide a more reliable description of their features (e.g., amplitude, frequency bandwidth). Starting from the description of the structure and working principles of MEMS, we provide a review of their emerging applications in the healthcare field, discussing the advantages and limitations of each framework. Finally, we deliver a discussion on the lessons learned from the literature, and the open questions and challenges in the field that the scientific community must address in the near future.Source: Biosensors (Basel) 12 (2022). doi:10.3390/bios12100835
DOI: 10.3390/bios12100835
Metrics:
Mallegni N., Molinari G., Ricci C., Lazzeri A., La Rosa D., Crivello A., Milazzo M.
Acoustic signals are important markers to monitor physiological and pathological conditions, e.g., heart and respiratory sounds. The employment of traditional devices, such as stethoscopes, has been progressively superseded by new miniaturized devices, usually identified as microelectromechanical systems (MEMS). These tools are able to better detect the vibrational content of acoustic signals in order to provide a more reliable description of their features (e.g., amplitude, frequency bandwidth). Starting from the description of the structure and working principles of MEMS, we provide a review of their emerging applications in the healthcare field, discussing the advantages and limitations of each framework. Finally, we deliver a discussion on the lessons learned from the literature, and the open questions and challenges in the field that the scientific community must address in the near future.Source: Biosensors (Basel) 12 (2022). doi:10.3390/bios12100835
DOI: 10.3390/bios12100835
Metrics:
See at:
ISTI Repository | CNR ExploRA | www.mdpi.com
2022
Conference article
Open Access
Best practices for model calibration in smartphone-based indoor positioning systems
Furfari F., Crivello A., Baronti P., Girolami M., Barsocchi P.
User location and tracking information are increasingly used for contact tracing and social community detection. In-door positioning and indoor navigation systems are reaching good performances in several realistic scenarios. After an evaluation exclusively done through simulations, nowadays, these systems are trying to reach robust performances and good accuracy in heterogeneous environments. Problems are manifold as each environment presents a structure that strongly affects inertial sensors and radio signal propagation. Generally, systems showing the best performances rely on an extended knowledge of the indoor map. Moreover, they implement a model for pedestrian dynamics in terms of e.g step length, stride and the behaviour of the target users. Experimental results obtained during realistic indoor competitions, clearly show that performances drop when such systems are used in unseen scenarios in which an external user test the proposed solution. In fact, many parameters that are generally calibrated and set to maximize the performances might not work as expected. In this paper, we highlight which best practices should be applied for model calibration in smartphone-based indoor positioning systems. We describe a reference system based on a particle filter, and we show the most relevant parameters and the main factors that are generally in common with all similar systems in the literature. We also present the Run-Once tool for reaching optimal parameters, highlighting those best practices that should be applied to indoor positioning systems to maximize their performances and improve their robustness.Source: WiMob 2022 - 18th International Conference on Wireless and Mobile Computing, Networking and Communications, pp. 443–448, Thessaloniki, Greece, 10-12/10/2022
DOI: 10.1109/wimob55322.2022.9941681
Metrics:
Furfari F., Crivello A., Baronti P., Girolami M., Barsocchi P.
User location and tracking information are increasingly used for contact tracing and social community detection. In-door positioning and indoor navigation systems are reaching good performances in several realistic scenarios. After an evaluation exclusively done through simulations, nowadays, these systems are trying to reach robust performances and good accuracy in heterogeneous environments. Problems are manifold as each environment presents a structure that strongly affects inertial sensors and radio signal propagation. Generally, systems showing the best performances rely on an extended knowledge of the indoor map. Moreover, they implement a model for pedestrian dynamics in terms of e.g step length, stride and the behaviour of the target users. Experimental results obtained during realistic indoor competitions, clearly show that performances drop when such systems are used in unseen scenarios in which an external user test the proposed solution. In fact, many parameters that are generally calibrated and set to maximize the performances might not work as expected. In this paper, we highlight which best practices should be applied for model calibration in smartphone-based indoor positioning systems. We describe a reference system based on a particle filter, and we show the most relevant parameters and the main factors that are generally in common with all similar systems in the literature. We also present the Run-Once tool for reaching optimal parameters, highlighting those best practices that should be applied to indoor positioning systems to maximize their performances and improve their robustness.Source: WiMob 2022 - 18th International Conference on Wireless and Mobile Computing, Networking and Communications, pp. 443–448, Thessaloniki, Greece, 10-12/10/2022
DOI: 10.1109/wimob55322.2022.9941681
Metrics:
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ISTI Repository | ieeexplore.ieee.org | CNR ExploRA
2021
Journal article
Open Access
Discovering location based services: a unified approach for heterogeneous indoor localization systems
Furfari F., Crivello A., Baronti P., Barsocchi P., Girolami M., Palumbo F., Quezada-Gaibor D., Mendoza Silva G. M., Torres-Sospedra J.
The technological solutions and communication capabilities offered by the Internet of Things paradigm, in terms of raising availability of wearable devices, the ubiquitous internet connection, and the presence on the market of service-oriented solutions, have allowed a wide proposal of Location Based Services (LBS). In a close future, we foresee that companies and service providers will have developed reliable solutions to address indoor positioning, as basis for useful location based services. These solutions will be different from each other and they will adopt different hardware and processing techniques. This paper describes the proposal of a unified approach for Indoor Localization Systems that enables the cooperation between heterogeneous solutions and their functional modules. To this end, we designed an integrated architecture that, abstracting its main components, allows a seamless interaction among them. Finally, we present a working prototype of such architecture, which is based on the popular Telegram application for Android, as an integration demonstrator. The integration of the three main phases -namely the discovery phase, the User Agent self-configuration, and the indoor map retrieval/rendering- demonstrates the feasibility of the proposed integrated architecture.Source: Internet of Things 13 (2021): 1–14. doi:10.1016/j.iot.2020.100334
DOI: 10.1016/j.iot.2020.100334
Project(s): A-WEAR
Metrics:
Furfari F., Crivello A., Baronti P., Barsocchi P., Girolami M., Palumbo F., Quezada-Gaibor D., Mendoza Silva G. M., Torres-Sospedra J.
The technological solutions and communication capabilities offered by the Internet of Things paradigm, in terms of raising availability of wearable devices, the ubiquitous internet connection, and the presence on the market of service-oriented solutions, have allowed a wide proposal of Location Based Services (LBS). In a close future, we foresee that companies and service providers will have developed reliable solutions to address indoor positioning, as basis for useful location based services. These solutions will be different from each other and they will adopt different hardware and processing techniques. This paper describes the proposal of a unified approach for Indoor Localization Systems that enables the cooperation between heterogeneous solutions and their functional modules. To this end, we designed an integrated architecture that, abstracting its main components, allows a seamless interaction among them. Finally, we present a working prototype of such architecture, which is based on the popular Telegram application for Android, as an integration demonstrator. The integration of the three main phases -namely the discovery phase, the User Agent self-configuration, and the indoor map retrieval/rendering- demonstrates the feasibility of the proposed integrated architecture.Source: Internet of Things 13 (2021): 1–14. doi:10.1016/j.iot.2020.100334
DOI: 10.1016/j.iot.2020.100334
Project(s): A-WEAR
Metrics:
See at:
Internet of Things | Recolector de Ciencia Abierta, RECOLECTA | CNR ExploRA | www.sciencedirect.com | ZENODO
2021
Journal article
Open Access
COVID-19 & privacy: Enhancing of indoor localization architectures towards effective social distancing
Barsocchi P., Calabrò A., Crivello A., Daoudagh S., Furfari F., Girolami M., Marchetti E.
The way people access services in indoor environments has dramatically changed in the last year. The countermeasures to the COVID-19 pandemic imposed a disruptive requirement, namely preserving social distance among people in indoor environments. We explore in this work the possibility of adopting the indoor localization technologies to measure the distance among users in indoor environments. We discuss how information about people's contacts collected can be exploited during three stages: before, during, and after people access a service. We present a reference architecture for an Indoor Localization System (ILS), and we illustrate three representative use-cases. We derive some architectural requirements, and we discuss some issues that concretely cope with the real installation of an ILS in real-world settings. In particular, we explore the privacy and trust reputation of an ILS, the discovery phase, and the deployment of the ILS in real-world settings. We finally present an evaluation framework for assessing the performance of the architecture proposed.Source: Array 9 (2021). doi:10.1016/j.array.2020.100051
DOI: 10.1016/j.array.2020.100051
Project(s): CyberSec4Europe
Metrics:
Barsocchi P., Calabrò A., Crivello A., Daoudagh S., Furfari F., Girolami M., Marchetti E.
The way people access services in indoor environments has dramatically changed in the last year. The countermeasures to the COVID-19 pandemic imposed a disruptive requirement, namely preserving social distance among people in indoor environments. We explore in this work the possibility of adopting the indoor localization technologies to measure the distance among users in indoor environments. We discuss how information about people's contacts collected can be exploited during three stages: before, during, and after people access a service. We present a reference architecture for an Indoor Localization System (ILS), and we illustrate three representative use-cases. We derive some architectural requirements, and we discuss some issues that concretely cope with the real installation of an ILS in real-world settings. In particular, we explore the privacy and trust reputation of an ILS, the discovery phase, and the deployment of the ILS in real-world settings. We finally present an evaluation framework for assessing the performance of the architecture proposed.Source: Array 9 (2021). doi:10.1016/j.array.2020.100051
DOI: 10.1016/j.array.2020.100051
Project(s): CyberSec4Europe
Metrics:
See at:
Array | ISTI Repository | Array | CNR ExploRA | www.sciencedirect.com
2021
Journal article
Open Access
Off-line Evaluation of Indoor Positioning Systems in Different Scenarios: The Experiences from IPIN 2020 Competition
Potortì F., Torres-Sospedra J., Quezada-Gaibor D., Jiménez A. R., Seco F., Pérez-Navarro A., Ortiz M., Zhu N., Renaudin V., Ichikari R., Shimomura R., Ohta N., Nagae S., Kurata T., Wei D., Ji X., Zhang W., Kram S., Stahlke M., Mutschler C., Crivello A., Barsocchi P., Girolami M., Palumbo F., Chen R., Wu Y., Li W., Yu Y., Xu S., Huang L., Liu T., Kuang J., Niu X., Yoshida T., Nagata Y., Fukushima Y., Fukatani N., Hayashida N., Asai Y., Urano K., Ge W., Lee N. T., Fang S. H., Jie Y. C., Young S. R., Chien Y. R., Yua C. C., Ma C., Wub B., Zhangc W., Wang Y., Fan Y., Poslad S., Selviah D. R., Wangd W., Yuan H., Yonamoto Y., Yamaguchi M., Kaichi T., Zhou B., Liue X., Gu Z., Yang C., Wu Z., Xie D., Huang C., Zheng L., Peng A., Jin G., Wangh Q., Luo H., Xiong H., Bao L., Zhangi P., Zhao F., Yuj C. A., Hung C. H., Antsfeld L., Chidlovskii B., Jiang H., Xia M., Yan D., Li Y., Dong Y., Silva I., Pendão C., Meneses F., Nicolau M. J., Costa A., Moreira A., De Cock C., Plets D., Opiela M., Dzama J., Zhang L., Li H., Chen B., Liu Y., Yean S., Lim B. Z., Teo W. J., Leep B. S., Oh H. L.
Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1m for the Smartphone Track and 0.5m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Source: IEEE sensors journal (Online) (2021): 1–44. doi:10.1109/JSEN.2021.3083149
DOI: 10.1109/jsen.2021.3083149
Metrics:
Potortì F., Torres-Sospedra J., Quezada-Gaibor D., Jiménez A. R., Seco F., Pérez-Navarro A., Ortiz M., Zhu N., Renaudin V., Ichikari R., Shimomura R., Ohta N., Nagae S., Kurata T., Wei D., Ji X., Zhang W., Kram S., Stahlke M., Mutschler C., Crivello A., Barsocchi P., Girolami M., Palumbo F., Chen R., Wu Y., Li W., Yu Y., Xu S., Huang L., Liu T., Kuang J., Niu X., Yoshida T., Nagata Y., Fukushima Y., Fukatani N., Hayashida N., Asai Y., Urano K., Ge W., Lee N. T., Fang S. H., Jie Y. C., Young S. R., Chien Y. R., Yua C. C., Ma C., Wub B., Zhangc W., Wang Y., Fan Y., Poslad S., Selviah D. R., Wangd W., Yuan H., Yonamoto Y., Yamaguchi M., Kaichi T., Zhou B., Liue X., Gu Z., Yang C., Wu Z., Xie D., Huang C., Zheng L., Peng A., Jin G., Wangh Q., Luo H., Xiong H., Bao L., Zhangi P., Zhao F., Yuj C. A., Hung C. H., Antsfeld L., Chidlovskii B., Jiang H., Xia M., Yan D., Li Y., Dong Y., Silva I., Pendão C., Meneses F., Nicolau M. J., Costa A., Moreira A., De Cock C., Plets D., Opiela M., Dzama J., Zhang L., Li H., Chen B., Liu Y., Yean S., Lim B. Z., Teo W. J., Leep B. S., Oh H. L.
Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1m for the Smartphone Track and 0.5m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Source: IEEE sensors journal (Online) (2021): 1–44. doi:10.1109/JSEN.2021.3083149
DOI: 10.1109/jsen.2021.3083149
Metrics:
See at:
ieeexplore.ieee.org | ISTI Repository | CNR ExploRA
2021
Contribution to book
Embargo
Monitoring in the physical domain to support active ageing
Denna E., Civiello M., Porcelli S., Crivello A., Mavilia F., Palumbo F.
Monitoring system have been customized to collect data and to analyse several aspects of the users' life, the reason of this custom solution came from the needs to join physical activity of the user, life usage, social interaction and mind activities, all these features are not present in standard devices all together, so we arrived to a new system architecture where the monitoring system is the first front end versus the user. This chapter describes the general monitoring system architecture and provides insight into the contribution and role of sensors. Such sensing solutions are not only designed to match the needs and requirements of the user but also to reduce intrusiveness and usage complexity. By doing so the system is designed around the life of its users and maximizes the effectiveness of data collection. Example from NESTORE project are taken as reference.Source: Digital Health Technology for Better Aging. A multidisciplinary approach, edited by G. Andreoni, C. Mambretti, pp. 55–76, 2021
DOI: 10.1007/978-3-030-72663-8_4
Project(s): NESTORE
Metrics:
Denna E., Civiello M., Porcelli S., Crivello A., Mavilia F., Palumbo F.
Monitoring system have been customized to collect data and to analyse several aspects of the users' life, the reason of this custom solution came from the needs to join physical activity of the user, life usage, social interaction and mind activities, all these features are not present in standard devices all together, so we arrived to a new system architecture where the monitoring system is the first front end versus the user. This chapter describes the general monitoring system architecture and provides insight into the contribution and role of sensors. Such sensing solutions are not only designed to match the needs and requirements of the user but also to reduce intrusiveness and usage complexity. By doing so the system is designed around the life of its users and maximizes the effectiveness of data collection. Example from NESTORE project are taken as reference.Source: Digital Health Technology for Better Aging. A multidisciplinary approach, edited by G. Andreoni, C. Mambretti, pp. 55–76, 2021
DOI: 10.1007/978-3-030-72663-8_4
Project(s): NESTORE
Metrics:
See at:
link.springer.com | CNR ExploRA
2021
Journal article
Open Access
Particle filter reinforcement via context-sensing for smartphone-based pedestrian dead reckoning
Shao W., Zhao F., Luo H., Tian H., Li J., Crivello A.
Pedestrian dead reckoning based on particle filter is commonly used for enabling seamless smartphone-based indoor positioning. However, compass directions indoor are heavily distorted due to the presence of ferromagnetic materials. Conventional particle filters convert the raw compass direction to a distribution adding a constant variance noise and leveraging a particle swarm to simulate the distribution. Finally, the selection of eligible directions is performed applying external constraints mainly imposed from the indoor map. However, the choice of a constant parameter decreases the positioning performances because the variance of nearby context, including topography, ferromagnetic materials, and particle distribution, is not represented. Therefore, we propose the particle filter reinforcement able to adaptively learn and adjust the variance of the direction observing the context in real-time. Experiments in real-world scenarios show that the proposed method improves the positioning accuracy by more than 20% at the 80% probability compared with state-of-the-art methods.Source: IEEE communications letters (Print) 25 (2021): 3144–3148. doi:10.1109/LCOMM.2021.3090300
DOI: 10.1109/lcomm.2021.3090300
Metrics:
Shao W., Zhao F., Luo H., Tian H., Li J., Crivello A.
Pedestrian dead reckoning based on particle filter is commonly used for enabling seamless smartphone-based indoor positioning. However, compass directions indoor are heavily distorted due to the presence of ferromagnetic materials. Conventional particle filters convert the raw compass direction to a distribution adding a constant variance noise and leveraging a particle swarm to simulate the distribution. Finally, the selection of eligible directions is performed applying external constraints mainly imposed from the indoor map. However, the choice of a constant parameter decreases the positioning performances because the variance of nearby context, including topography, ferromagnetic materials, and particle distribution, is not represented. Therefore, we propose the particle filter reinforcement able to adaptively learn and adjust the variance of the direction observing the context in real-time. Experiments in real-world scenarios show that the proposed method improves the positioning accuracy by more than 20% at the 80% probability compared with state-of-the-art methods.Source: IEEE communications letters (Print) 25 (2021): 3144–3148. doi:10.1109/LCOMM.2021.3090300
DOI: 10.1109/lcomm.2021.3090300
Metrics:
See at:
ISTI Repository | ieeexplore.ieee.org | CNR ExploRA | IEEE Communications Letters
2021
Journal article
Embargo
Floor identification in large-scale environments with wi-fi autonomous block models
Shao W., Luo H., Zhao F., Tian H., Huang J., Crivello A.
Traditional Wi-Fi-based floor identification methods mainly have been tested in small experimental scenarios, and generally, their accuracies drop significantly when applied in real large and multistorey environments. The main challenge emerges when the complexity of Wi-Fi signals on the same floor exceeds the complexity between the floors along the vertical direction, leading to a reduced floor distinguishability. A second challenge regards the complexity of Wi-Fi features in environments with atrium, hollow areas, mezzanines, intermediate floors, and crowded signal channels. In this article, we propose an adaptive Wi-Fi-based floor identification algorithm to achieve accurate floor identification also in these environments. Our algorithm, based on the Wi-Fi received signal strength indicator and spatial similarity, first identifies autonomous blocks parcelling the whole environment. Then, local floor identification is performed through the proposed Wi-Fi models to fully harness the Wi-Fi features. Finally, floors are estimated through the joint optimization of the autonomous blocks and the local floor models. We have conducted extensive experiments in three real large and multistorey buildings greater than 140 000 m 2 using 19 different devices. Finally, we show a comparison between our proposal and other state-of-the-art algorithms. Experimental results confirm that our proposal performs better than other methods, and it exhibits an average accuracy of 97.24%.Source: IEEE transactions on industrial informatics 18 (2021): 847–858. doi:10.1109/TII.2021.3074153
DOI: 10.1109/tii.2021.3074153
Metrics:
Shao W., Luo H., Zhao F., Tian H., Huang J., Crivello A.
Traditional Wi-Fi-based floor identification methods mainly have been tested in small experimental scenarios, and generally, their accuracies drop significantly when applied in real large and multistorey environments. The main challenge emerges when the complexity of Wi-Fi signals on the same floor exceeds the complexity between the floors along the vertical direction, leading to a reduced floor distinguishability. A second challenge regards the complexity of Wi-Fi features in environments with atrium, hollow areas, mezzanines, intermediate floors, and crowded signal channels. In this article, we propose an adaptive Wi-Fi-based floor identification algorithm to achieve accurate floor identification also in these environments. Our algorithm, based on the Wi-Fi received signal strength indicator and spatial similarity, first identifies autonomous blocks parcelling the whole environment. Then, local floor identification is performed through the proposed Wi-Fi models to fully harness the Wi-Fi features. Finally, floors are estimated through the joint optimization of the autonomous blocks and the local floor models. We have conducted extensive experiments in three real large and multistorey buildings greater than 140 000 m 2 using 19 different devices. Finally, we show a comparison between our proposal and other state-of-the-art algorithms. Experimental results confirm that our proposal performs better than other methods, and it exhibits an average accuracy of 97.24%.Source: IEEE transactions on industrial informatics 18 (2021): 847–858. doi:10.1109/TII.2021.3074153
DOI: 10.1109/tii.2021.3074153
Metrics:
See at:
ieeexplore.ieee.org | CNR ExploRA | IEEE Transactions on Industrial Informatics
2021
Conference article
Open Access
Towards ubiquitous indoor positioning: comparing systems across heterogeneous datasets
Torres-Sospedra J., Silva I., Klus L., Quezada-Gaibor D., Crivello A., Barsocchi P., Pendao C., Lohan E. S., Nurmi J., Moreira A.
The evaluation of Indoor Positioning Systems (IPSs) mostly relies on local deployments in the researchers' or partners' facilities. The complexity of preparing comprehensive experiments, collecting data, and considering multiple scenarios usually limits the evaluation area and, therefore, the assessment of the proposed systems. The requirements and features of controlled experiments cannot be generalized since the use of the same sensors or anchors density cannot be guaranteed. The dawn of datasets is pushing IPS evaluation to a similar level as machine-learning models, where new proposals are evaluated over many heterogeneous datasets. This paper proposes a way to evaluate IPSs in multiple scenarios, that is validated with three use cases. The results prove that the proposed aggregation of the evaluation metric values is a useful tool for high-level comparison of IPSs.Source: IPIN 2021 - 2021 International Conference on Indoor Positioning and Indoor Navigation, Lloret de Mar, Spain, 29/11/2021
DOI: 10.1109/ipin51156.2021.9662560
Metrics:
Torres-Sospedra J., Silva I., Klus L., Quezada-Gaibor D., Crivello A., Barsocchi P., Pendao C., Lohan E. S., Nurmi J., Moreira A.
The evaluation of Indoor Positioning Systems (IPSs) mostly relies on local deployments in the researchers' or partners' facilities. The complexity of preparing comprehensive experiments, collecting data, and considering multiple scenarios usually limits the evaluation area and, therefore, the assessment of the proposed systems. The requirements and features of controlled experiments cannot be generalized since the use of the same sensors or anchors density cannot be guaranteed. The dawn of datasets is pushing IPS evaluation to a similar level as machine-learning models, where new proposals are evaluated over many heterogeneous datasets. This paper proposes a way to evaluate IPSs in multiple scenarios, that is validated with three use cases. The results prove that the proposed aggregation of the evaluation metric values is a useful tool for high-level comparison of IPSs.Source: IPIN 2021 - 2021 International Conference on Indoor Positioning and Indoor Navigation, Lloret de Mar, Spain, 29/11/2021
DOI: 10.1109/ipin51156.2021.9662560
Metrics:
See at:
ISTI Repository | ieeexplore.ieee.org | CNR ExploRA
2020
Journal article
Closed Access
Remote detection of social interactions in indoor environments through bluetooth low energy beacons
Baronti P., Barsocchi P., Chessa S., Crivello A., Girolami M., Mavilia F., Palumbo F.
The way people interact in daily life is a challenging phenomenon to be captured and studied without altering the natural rhythm of the interactions. We investigate the development of automated tools that may provide information to the researchers that analyse interactions among humans. One important requirement of these tools is that should not interfere with the subjects under observation, in order to avoid any alteration in the subject's normal behaviour. Our approach is based on the detection of proximity among groups of people that is obtained using commercial wearable wireless tags based on Bluetooth Low Energy (BLE) and a novel algorithm called Remote Detection of Human Proximity (ReD-HuP) that analyses the wireless signal of tags and produce the proximity information. The algorithm, which has been validated against the ground truth of an experimental dataset, achieves an accuracy of 95.91% and an F-Score of 95.79%.Source: Journal of ambient intelligence and smart environments (Print) 12 (2020): 203–217. doi:10.3233/AIS-200560
DOI: 10.3233/ais-200560
Project(s): NESTORE
Metrics:
Baronti P., Barsocchi P., Chessa S., Crivello A., Girolami M., Mavilia F., Palumbo F.
The way people interact in daily life is a challenging phenomenon to be captured and studied without altering the natural rhythm of the interactions. We investigate the development of automated tools that may provide information to the researchers that analyse interactions among humans. One important requirement of these tools is that should not interfere with the subjects under observation, in order to avoid any alteration in the subject's normal behaviour. Our approach is based on the detection of proximity among groups of people that is obtained using commercial wearable wireless tags based on Bluetooth Low Energy (BLE) and a novel algorithm called Remote Detection of Human Proximity (ReD-HuP) that analyses the wireless signal of tags and produce the proximity information. The algorithm, which has been validated against the ground truth of an experimental dataset, achieves an accuracy of 95.91% and an F-Score of 95.79%.Source: Journal of ambient intelligence and smart environments (Print) 12 (2020): 203–217. doi:10.3233/AIS-200560
DOI: 10.3233/ais-200560
Project(s): NESTORE
Metrics:
See at:
content.iospress.com | Journal of Ambient Intelligence and Smart Environments | CNR ExploRA
2020
Journal article
Open Access
Accurate Indoor Positioning Using Temporal-Spatial Constraints Based on Wi-Fi Fine Time Measurements
Shao W., Luo H., Zhao F., Tian H., Yan S. ., Crivello A.
The IEEE 802.11mc-2016 protocol enables certified devices to obtain precise ranging information using time-of-flight based techniques. The ranging error increases in indoor environments due to the multipath effect. Traditional methods utilize only the ranging measurements of the current location, thus limiting the abilities to reduce the influence of multi-path problems. This paper introduces a robust positioning method that leverages the constraints of multiple positioning nodes at different positions. We transfer a sequence of temporal ranging measurements into multiple virtual positioning clients in the spatial domain by considering their spatial constraints. Defining an objective function and the spatial constraints of the virtual positioning clients as Karush-Kuhn-Tucker conditions, we solve the positioning estimation with non-convex optimization. We propose an iterative weight estimation method for the time of flight ranging and the virtual positioning client to optimize the positioning model. An extensive experimental campaign demonstrates that our proposal is able to remarkably improve the positioning accuracy in complex indoor environments.Source: IEEE Internet of Things Journal 7 (2020): 11006–11019. doi:10.1109/JIOT.2020.2992069
DOI: 10.1109/jiot.2020.2992069
Metrics:
Shao W., Luo H., Zhao F., Tian H., Yan S. ., Crivello A.
The IEEE 802.11mc-2016 protocol enables certified devices to obtain precise ranging information using time-of-flight based techniques. The ranging error increases in indoor environments due to the multipath effect. Traditional methods utilize only the ranging measurements of the current location, thus limiting the abilities to reduce the influence of multi-path problems. This paper introduces a robust positioning method that leverages the constraints of multiple positioning nodes at different positions. We transfer a sequence of temporal ranging measurements into multiple virtual positioning clients in the spatial domain by considering their spatial constraints. Defining an objective function and the spatial constraints of the virtual positioning clients as Karush-Kuhn-Tucker conditions, we solve the positioning estimation with non-convex optimization. We propose an iterative weight estimation method for the time of flight ranging and the virtual positioning client to optimize the positioning model. An extensive experimental campaign demonstrates that our proposal is able to remarkably improve the positioning accuracy in complex indoor environments.Source: IEEE Internet of Things Journal 7 (2020): 11006–11019. doi:10.1109/JIOT.2020.2992069
DOI: 10.1109/jiot.2020.2992069
Metrics:
See at:
ISTI Repository | doi.org | ieeexplore.ieee.org | CNR ExploRA
2020
Conference article
Open Access
A privacy-by-design architecture for indoor localization systems
Barsocchi P., Calabro A., Crivello A., Daoudagh S., Furfari F., Girolami M., Marchetti E.
The availability of mobile devices has led to an arising development of indoor location services collecting a large amount of sensitive information. However, without accurate and verified management, such information could become severe back-doors for security and privacy issues. We propose in this paper a novel Location-Based Service (LBS) architecture in line with the GDPR's provisions. For feasibility purposes and considering a representative use-case, a reference implementation, based on the popular Telegram app, is also presented.Source: 13th International Conference on the Quality of Information and Communications Technology (QUATIC 2020), pp. 358–366, Faro, Portugal, September 9-11, 2020
DOI: 10.1007/978-3-030-58793-2_29
Project(s): CyberSec4Europe
Metrics:
Barsocchi P., Calabro A., Crivello A., Daoudagh S., Furfari F., Girolami M., Marchetti E.
The availability of mobile devices has led to an arising development of indoor location services collecting a large amount of sensitive information. However, without accurate and verified management, such information could become severe back-doors for security and privacy issues. We propose in this paper a novel Location-Based Service (LBS) architecture in line with the GDPR's provisions. For feasibility purposes and considering a representative use-case, a reference implementation, based on the popular Telegram app, is also presented.Source: 13th International Conference on the Quality of Information and Communications Technology (QUATIC 2020), pp. 358–366, Faro, Portugal, September 9-11, 2020
DOI: 10.1007/978-3-030-58793-2_29
Project(s): CyberSec4Europe
Metrics:
See at:
link-springer-com-443.webvpn.fjmu.edu.cn | CNR ExploRA | Communications in Computer and Information Science
2020
Conference article
Closed Access
Detecting Social Interactions in Indoor Environments with the Red-HuP Algorithm
Barsocchi P., Crivello A., Girolami M., Mavilia F.
Detecting social interactions among people represents a challenging task. In this study we evaluate the performance of the ReD-HuP algorithm. We study a real-world and useful experimental dataset and we provide a comparison with some classification methods. Interactions are inferred from co-location of people by exploiting Bluetooth Low Energy (BLE) beacons. Our analysis investigates how the different transmission powers affect the overall performance, we also analyze the results by varying the width of the time window used to analyze BLE beacons. Results obtained with the ReD-HuP algorithm have been compared against two well known and wide adopted machine learning classification methods.Source: 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Austin, TX, USA, USA, 23-27 March 2020
DOI: 10.1109/percomworkshops48775.2020.9156095
Metrics:
Barsocchi P., Crivello A., Girolami M., Mavilia F.
Detecting social interactions among people represents a challenging task. In this study we evaluate the performance of the ReD-HuP algorithm. We study a real-world and useful experimental dataset and we provide a comparison with some classification methods. Interactions are inferred from co-location of people by exploiting Bluetooth Low Energy (BLE) beacons. Our analysis investigates how the different transmission powers affect the overall performance, we also analyze the results by varying the width of the time window used to analyze BLE beacons. Results obtained with the ReD-HuP algorithm have been compared against two well known and wide adopted machine learning classification methods.Source: 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Austin, TX, USA, USA, 23-27 March 2020
DOI: 10.1109/percomworkshops48775.2020.9156095
Metrics:
See at:
doi.org | ieeexplore.ieee.org | CNR ExploRA
2020
Journal article
Open Access
"Hi This Is NESTORE, Your Personal Assistant": Design of an Integrated IoT System for a Personalized Coach for Healthy Aging
Palumbo F., Crivello A., Furfari F., Girolami M., Mastropietro A., Manferdelli G., Röcke C., Guye S., Salvá Casanovas A., Caon M., Carrino F., Khaled O. A., Mugellini E., Denna E., Mauri M., Ward D., Subías-Beltrán P., Orte S., Candea C., Candea G., Rizzo G.
In the context of the fourth revolution in healthcare technologies, leveraging monitoring and personalization across different domains becomes a key factor for providing useful services to maintain and promote well-being. This is even more crucial for older people, with aging being a complex multi-dimensional and multi-factorial process which can lead to frailty. The NESTORE project was recently funded by the EU Commission with the aim of supporting healthy older people to sustain their well-being and capacity to live independently. It is based on a multi-dimensional model of the healthy aging process that covers physical activity, nutrition, cognition, and social activity. NESTORE is based on the paradigm of the human-in-the-loop cyber-physical system that, exploiting the availability of Internet of Things technologies combined with analytics in the cloud, provides a virtual coaching system to support healthy aging. This work describes the design of the NESTORE methodology and its IoT architecture. We first model the end-user under several domains, then we present the NESTORE system that, analyzing relevant key-markers, provides coaching activities and personalized feedback to the user. Finally, we describe the validation strategy to assess the effectiveness of NESTORE as a coaching platform for healthy aging.Source: Frontiers in digital health (2020). doi:10.3389/fdgth.2020.545949
DOI: 10.3389/fdgth.2020.545949
Project(s): NESTORE
Metrics:
Palumbo F., Crivello A., Furfari F., Girolami M., Mastropietro A., Manferdelli G., Röcke C., Guye S., Salvá Casanovas A., Caon M., Carrino F., Khaled O. A., Mugellini E., Denna E., Mauri M., Ward D., Subías-Beltrán P., Orte S., Candea C., Candea G., Rizzo G.
In the context of the fourth revolution in healthcare technologies, leveraging monitoring and personalization across different domains becomes a key factor for providing useful services to maintain and promote well-being. This is even more crucial for older people, with aging being a complex multi-dimensional and multi-factorial process which can lead to frailty. The NESTORE project was recently funded by the EU Commission with the aim of supporting healthy older people to sustain their well-being and capacity to live independently. It is based on a multi-dimensional model of the healthy aging process that covers physical activity, nutrition, cognition, and social activity. NESTORE is based on the paradigm of the human-in-the-loop cyber-physical system that, exploiting the availability of Internet of Things technologies combined with analytics in the cloud, provides a virtual coaching system to support healthy aging. This work describes the design of the NESTORE methodology and its IoT architecture. We first model the end-user under several domains, then we present the NESTORE system that, analyzing relevant key-markers, provides coaching activities and personalized feedback to the user. Finally, we describe the validation strategy to assess the effectiveness of NESTORE as a coaching platform for healthy aging.Source: Frontiers in digital health (2020). doi:10.3389/fdgth.2020.545949
DOI: 10.3389/fdgth.2020.545949
Project(s): NESTORE
Metrics:
See at:
Diposit Digital de Documents de la UAB | Frontiers in Digital Health | Frontiers in Digital Health | ISTI Repository | CNR ExploRA | DOAJ-Articles | www.frontiersin.org | Frontiers in Digital Health | Zurich Open Repository and Archive
2020
Contribution to journal
Open Access
Editorial of Sensors and Sensing Technologies for Indoor Positioning and Indoor Navigation
Potortì F., Palumbo F., Crivello A.
Source: Sensors (Basel) 20 (2020). doi:10.3390/s20205924
DOI: 10.3390/s20205924
Metrics:
Potortì F., Palumbo F., Crivello A.
Source: Sensors (Basel) 20 (2020). doi:10.3390/s20205924
DOI: 10.3390/s20205924
Metrics:
See at:
Sensors | Sensors | ISTI Repository | CNR ExploRA | Sensors | Sensors
2020
Contribution to journal
Unknown
Sensors and sensing technologies for indoor positioning and indoor navigation
Potortì F., Palumbo F., Crivello A.
The last ten years have seen enormous technical progress in the field of indoor positioning and indoor navigation; yet, in contrast with outdoor well-established GNSS solutions, no technology exists that is cheap and accurate enough for the general market. The potential applications of indoor localization are all-encompassing, from home to wide public areas, from IoT and personal devices to surveillance and crowd behavior applications, and from casual use to mission-critical systems. This Special Issue encourages authors, from academia and industry, to submit new research results about innovations for indoor positioning and navigation. The Special Issue topics include but are not limited to: Location-based services and applications; Benchmarking, assessment, evaluation, standards; User requirements; UI, indoor maps, and 3D building models; Human motion monitoring and modeling; Robotics and UAV; Indoor navigation and tracking methods; Self-contained sensors; Wearable and multisensor systems; Privacy and security for ILS.Source: Basel: MDPI AG, 2020
Potortì F., Palumbo F., Crivello A.
The last ten years have seen enormous technical progress in the field of indoor positioning and indoor navigation; yet, in contrast with outdoor well-established GNSS solutions, no technology exists that is cheap and accurate enough for the general market. The potential applications of indoor localization are all-encompassing, from home to wide public areas, from IoT and personal devices to surveillance and crowd behavior applications, and from casual use to mission-critical systems. This Special Issue encourages authors, from academia and industry, to submit new research results about innovations for indoor positioning and navigation. The Special Issue topics include but are not limited to: Location-based services and applications; Benchmarking, assessment, evaluation, standards; User requirements; UI, indoor maps, and 3D building models; Human motion monitoring and modeling; Robotics and UAV; Indoor navigation and tracking methods; Self-contained sensors; Wearable and multisensor systems; Privacy and security for ILS.Source: Basel: MDPI AG, 2020
See at: CNR ExploRA | www.mdpi.com