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2021 Journal article Open Access OPEN

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 via OpenAIRE

See at: CNR ExploRA Open Access | www.sciencedirect.com Open Access


2021 Journal article Open Access OPEN

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

See at: ieeexplore.ieee.org Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2021 Contribution to book Embargo

System interoperability for next gen services at home. A challenge/opportunity for integration
Candea C., Palumbo F., Girolami M., Segato D., Candea G. S.
Interoperability is complex non-functional requirement of any today' system, and it refers the exchanged information. Two systems must offer the possibility to exchange and use the data in order to be named "interoperable", meaning that the message sent must contain data (in a standard coded format) that can be interpreted by the system that will receive it. The next section describes the challenges encounter during the integration activities from the interoperability point of view for the next gen of systems that offer services at home.Source: Digital Health Technology for Better Aging. A multidisciplinary approach, edited by G. Andreoni, C. Mambretti, pp. 129–144, 2021
DOI: 10.1007/978-3-030-72663-8_8
Project(s): NESTORE via OpenAIRE

See at: link.springer.com Restricted | CNR ExploRA Restricted


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 via OpenAIRE

See at: link.springer.com Restricted | CNR ExploRA Restricted


2021 Conference article Open Access OPEN

Inclusion design and functionalities of a personalized virtual coach for wellbeing to facilitate a universal access for older adults
El Kamali M., Angelini L., Caon M., Carrino F., Standoli C. E., Perego P., Andreoni G., Palumbo F., Mastropietro A., Khaled O. A., Mugellini E.
The current research proposes a technological system "NESTORE" designed for and with older adults in four different countries in order to improve and sustain their wellbeing. The system personalized activities and architecture, co-designed interfaces, and its multilingual aspect aim to establish an 'inclusion' criterion based on the user's sociocultural profile and health condition.Source: IEA 2021 - 21st Congress of the International Ergonomics Association, pp. 239–246, Online conference, 13-18/06/2021
DOI: 10.1007/978-3-030-74605-6_30
Project(s): NESTORE via OpenAIRE

See at: ISTI Repository Open Access | link.springer.com Restricted | CNR ExploRA Restricted


2020 Journal article Restricted

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 via OpenAIRE

See at: Journal of Ambient Intelligence and Smart Environments Restricted | Journal of Ambient Intelligence and Smart Environments Restricted | Journal of Ambient Intelligence and Smart Environments Restricted | Journal of Ambient Intelligence and Smart Environments Restricted | Journal of Ambient Intelligence and Smart Environments Restricted | CNR ExploRA Restricted


2020 Master thesis Restricted

A survey on the use of 802.11 Channel State Information in device-free applications: indoor localization and human activity and gesture recognition
Uccheddu M. C.
It presents a survey on device-free applications using 802.11n Channel State Information (CSI). The survey analyzed device-free indoor localization works, human activity recognition works and gesture recognition works. For each work are described the system setting, the experimental environments and finally the evaluation. There is also the description of my personal implementation of a device-free indoor signal-based system setting, that was deployed at Consiglio Nazionale delle Ricerche (CNR) in Pisa.

See at: etd.adm.unipi.it Restricted | CNR ExploRA Restricted


2020 Journal article Open Access OPEN

"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 via OpenAIRE

See at: Hes-so: ArODES Open Archive (University of Applied Sciences and Arts Western Switzerland Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | DOAJ-Articles Open Access | www.frontiersin.org Open Access | Frontiers in Digital Health Open Access | Frontiers in Digital Health Restricted | Frontiers in Digital Health Restricted | Frontiers in Digital Health Restricted | Frontiers in Digital Health Restricted | Frontiers in Digital Health Restricted


2020 Contribution to journal Open Access OPEN

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

See at: Sensors Open Access | Sensors Open Access | Europe PubMed Central Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | Sensors Open Access | Sensors Open Access | Sensors Open Access


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

See at: CNR ExploRA | www.mdpi.com


2020 Report Restricted

KI-FOOT - Report sui dispositivi sensoristici e analisi dei risultati dei test
Tognetti A., Carbonaro N., Palumbo F., La Rosa D., Barsocchi P., Furfari F., Potortì F., Cassarà P.
Lo scopo di questo documento è riportare la descrizione delle attività progettuali svolte al fine di identificare e validare le soluzioni sensoristiche da integrare nella calzatura. In particolare, tenendo in considerazione le specifiche fornite nel precedente documento D1.1, sono stati considerati due tipologie di sensori: 1) sensori piezoresistivi per la rilevazione della forza di contatto piede-suolo; 2) sensori inerziali per l'analisi dinamica dei movimenti effettuati dal piede durante la camminata. Di queste due categorie di sensori vengono mostrate le principali caratteristiche, il loro principio di funzionamento e i risultati dei test effettuati.Source: KI-FOOT, Deliverable D2.2, 2020

See at: CNR ExploRA Restricted


2020 Report Restricted

KI-FOOT - Integrazione del sistema nella calzatura
Carlos Srl, Adatec Srl, Palumbo F., La Rosa D., Cassarà P.
Il documento descrive l'integrazione finale del sistema di acquisizione dei dati nella calzatura e degli algoritmi di estrazione delle features con il database e l'interfaccia web di visualizzazione delle informazioni.Source: KI-FOOT, Deliverable D5.1, 2020

See at: CNR ExploRA Restricted


2020 Report Restricted

KI-FOOT - Risultati dei test in laboratorio ed in condizioni reali
Ortopedia Michelotti, Carlos Srl, Adatec Srl, Unipi, Palumbo F., La Rosa D., Cassarà P.
Il documento descrive i risultati dell'attività di test delle calzature sensorizzate durante l'utilizzo in condizioni reali. I test si sono svolti sia all'interno di uno studio di analisi medica podologica (con utenti che non presentavano delle difficoltà di deambulazione), sia lasciando il sistema in comodato d'uso ad un utente che ha potuto utilizzarlo per 10 gg durante le attività di vita quotidiana.Source: KI-FOOT, Deliverable D5.2, 2020

See at: CNR ExploRA Restricted


2020 Journal article Open Access OPEN

The IPIN 2019 indoor localisation competition - Description and results
Potortì F.
IPIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of \SI{1000}{m^2} outdoors and and \SI{6000}{m^2} indoors over three floors, with a total path length exceeding \SI{500}{m}. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks.Source: IEEE access 8 (2020): 206674–206718. doi:10.1109/ACCESS.2020.3037221
DOI: 10.1109/access.2020.3037221
DOI: 10.5445/ir/1000130123

See at: IEEE Access Open Access | IEEE Access Open Access | IEEE Access Open Access | IEEE Access Open Access | IEEE Access Open Access | IEEE Access Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | KITopen Open Access | IEEE Access Open Access


2020 Conference article Open Access OPEN

On the analysis of human posture for detecting social interactions with wearable devices
Baronti P., Girolami M., Mavilia F., Palumbo F., Luisetto G.
Detecting the dynamics of the social interaction represents a difficult task also with the adoption of sensing devices able to collect data with a high-Temporal resolution. Under this context, this work focuses on the effect of the body posture for the purpose of detecting a face-To-face interactions between individuals. To this purpose, we describe the NESTORE sensing kit that we used to collect a significant dataset that mimics some common postures of subjects while interacting. Our experimental results distinguish clearly those postures that negatively affect the quality of the signals used for detecting an interactions, from those postures that do not have such a negative impact. We also show the performance of the SID (Social Interaction Detector) algorithm with different settings, and we present its performance in terms of accuracy during the classification of interaction and non-interaction events.Source: ICHMS 2020 - IEEE International Conference on Human-Machine Systems, Online Conference, September 07-09, 2020
DOI: 10.1109/ichms49158.2020.9209510
Project(s): NESTORE via OpenAIRE

See at: ISTI Repository Open Access | ieeexplore.ieee.org Restricted | CNR ExploRA Restricted


2019 Report Open Access OPEN

NESTORE - Definition of the indicators and metrics
Palumbo F., Crivello A., Mavilia F., Girolami M., Furfari F., Porcelli S., Manferdelli G., Mastropietro A., Rizzo G., Orte S., Subías P., Boquè N., Perego P., Mauri M., Röcke C., Guye S.
This report contains the description of the metrics and indicators used by the Decision Support System (DSS) for recommending and stimulating the user during the use of the NESTORE coaching system used to make healthier lifestyle choices. This document collects the outcomes of Task 4.1 - Algorithms for Short-term post-processing and extraction of indicators, whose objective is to extract knowledge from data streams generated by the NESTORE sensors and software applications. This kind of data is continuously mined to extract indicators about the NESTORE target domains identified in the WP2 activities, namely physiological, nutritional, cognitive and mental status and social behaviour of the user.Source: Project report, NESTORE, Deliverable D4.1, 2019
Project(s): NESTORE via OpenAIRE

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2019 Conference article Open Access OPEN

Dynamic decision support system for personalised coaching to support active ageing
Orte S., Subías P., Fernández L., Mastropietro A., Porcelli S., Rizzo G., Boqué N., Guye S., Röcke C., Andreoni G., Crivello A., Palumbo F.
Physiological status and physical activity, social interaction, cognitive and emotional status, and nutrition in older people are the key target areas addressed by the NESTORE project. It is aimed at developing a multi-domain solution for users, able to prolong their functional, social, and cognitive capacity by empowering, stimulating, and unobtrusively monitoring, in other words, "coaching" the user's daily activities according to a well-defined "Active and Healthy Ageing" life-style protocol. Besides the key features of NESTORE in terms of technological solutions, this work focus on the preliminary research carried out in the context of algorithms for modelling and profiling target individuals with the aim of developing an effective dynamic Decision Support System.Source: AI*AAL.it 2018 - Artificial Intelligence for Ambient Assisted Living, pp. 16–36, Trento, Italy, 20-23 November 2018
Project(s): NESTORE via OpenAIRE

See at: ceur-ws.org Open Access | CNR ExploRA Open Access


2019 Report Restricted

INTESA - Test ed integrazione del sistema per il monitoraggio della qualità e durata del sonno
Palumbo F., Baronti P., Crivello A., Ferro E., Furfari F., Potortì F., Russo D., La Rosa D.
In questo documento sono riportate le attività svolte nell'ambito dell'OO4 durante il secondo anno del progetto INTESA, mirate alla finalizzazione del sistema integrato di monitoraggio della qualità e durata del sonno. Durante questo periodo, partendo dall'architettura del sistema definita nel precedente documento D4.1.1, si è conclusa l'attività di sviluppo e sono stati effettuati i test per la verifica delle funzionalità del sistema e l'integrazione con gli altri componenti della piattaforma INTESA.Source: Project report, INTESA, Deliverable D4.1.2, 2019

See at: CNR ExploRA Restricted


2019 Report Restricted

INTESA - Test ed integrazione del sistema per l'analisi stabilometrica
Palumbo F., Baronti P., Crivello A., Ferro E., Furfari F., Potortì F., Russo D., La Rosa D.
In questo documento sono riportate le attività svolte nell'ambito dell'OO4 durante il secondo anno del progetto INTESA. In questo periodo, partendo dall'architettura del sistema definita nel precedente documento D4.4.1, si è conclusa l'attività di sviluppo e sono stati effettuati i test per la verifica delle funzionalità del sistema e l'integrazione con gli altri componenti della piattaforma INTESA. Il sistema è stato installato con successo presso la RSA ed è rimasto attivo durante tutto il periodo di sperimentazione permettendo agli operatori ed al personale medico di attuare gli esercizi proposti dal protocollo INTESA con i soggetti partecipanti e fornendo ai servizi di monitoraggio di lungo periodo le informazioni raffinate previste.Source: Project report, INTESA, Deliverable D4.4.2, 2019

See at: CNR ExploRA Restricted


2019 Report Restricted

INTESA - Risultati della validazione e sperimentazione del dimostratore
Magrini M., Coscetti S., Palumbo F., La Rosa D., Delmastro F., Di Martino F., Distefano E., Valerio L., Bruno R., Campana M. G., Dolciotti C., Esa Systems S. R. L., Kell S. R. L.
In questo documento si descrive la fase di validazione e sperimentazione del dimostratore su utenti reali. ln particolare, si descrivono le varie fasi della sperimentazione e le performance ottenute dai vari sistemi di monitoraggio ed analisi di lungo periodo sui dati raccolti nel periodo di sperimentazione, che include la assistenza agli utenti primari reali e l'interazione con utenti secondari (caregiver).Source: Project report, INTESA, Deliverable D6.1, 2019

See at: CNR ExploRA Restricted