57 result(s)
Page Size: 10, 20, 50
Export: bibtex, xml, json, csv
Order by:

CNR Author operator: and / or
more
Typology operator: and / or
Language operator: and / or
Date operator: and / or
Rights operator: and / or
2021 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 | Internet of Things Restricted | Internet of Things Restricted


2021 Article Open Access OPEN

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 via OpenAIRE

See at: Array Open Access | ISTI Repository Open Access | Array Open Access | CNR ExploRA Restricted | www.sciencedirect.com Restricted


2020 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
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 Article Open Access OPEN

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
DOI: 10.1109/jiot.2020.2992069

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


2020 Conference object Open Access OPEN

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 via OpenAIRE

See at: link-springer-com-443.webvpn.fjmu.edu.cn Open Access | CNR ExploRA Open Access | Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted


2020 Conference object Restricted

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
DOI: 10.1109/percomworkshops48775.2020.9156095

See at: Unknown Repository Restricted | Unknown Repository Restricted | ieeexplore.ieee.org Restricted | CNR ExploRA Restricted | Unknown Repository Restricted


2020 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
DOI: 10.3389/fdgth.2020.545949/full
Project(s): NESTORE via OpenAIRE

See at: DOAJ-Articles Open Access | 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 Restricted | Frontiers in Digital Health Restricted | Frontiers in Digital Health Restricted | Frontiers in Digital Health Restricted


2020 Article 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 | Sensors Open Access | Europe PubMed Central Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | Sensors Open Access | Sensors Open Access


2020 Book 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 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

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


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 object 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 - Test dei servizi di monitoraggio di lungo periodo ed interazione sociale
Delmastro F., Di Martino F., Distefano E., Valerio L., Bruno R., Campana M. G., Palumbo F., Baronti P., Crivello A., Ferro E., Furfari F., Potortì F., Russo D., La Rosa D.
Questo documento ha lo scopo di presentare i risultati dei test dei sistemi di monitoraggio di lungo periodo (come specificato nelle attività dell'OO5), con particolare riferimento agli algoritmi per l'identificazione degli indicatori di salute e benessere derivati dai monitoraggi di breve periodo che hanno permesso di effettuare un'analisi su lungo periodo per i soggetti volontari coinvolti. Inoltre, si presentano i dettagli della valutazione sperimentale del servizio di monitoraggio nutrizionale e composizione corporea, dei fattori di stress e delle interazioni sociali.Source: Project report, INTESA, Deliverable D5.3, 2019

See at: CNR ExploRA Restricted


2019 Report Open Access OPEN

ISTI Young Researcher Award "Matteo Dellepiane" - Edition 2019
Barsocchi P., Candela L., Crivello A., Esuli A., Ferrari A., Girardi M., Guidotti R., Lonetti F., Malomo L., Moroni D., Nardini F. M., Pappalardo L., Rinzivillo S., Rossetti G., Robol L.
The ISTI Young Researcher Award (YRA) selects yearly the best young staff members working at Institute of Information Science and Technologies (ISTI). This award focuses on quality and quantity of the scientific production. In particular, the award is granted to the best young staff members (less than 35 years old) by assessing their scientific production in the year preceding the award. This report documents the selection procedure and the results of the 2019 YRA edition. From the 2019 edition on the award is named as "Matteo Dellepiane", being dedicated to a bright ISTI researcher who prematurely left us and who contributed a lot to the YRA initiative from its early start.Source: ISTI Technical reports, 2019

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


2019 Article Open Access OPEN

The Meaning of Sleep Quality: a Survey of Available Technologies
Crivello A., Barsocchi P., Girolami M., Palumbo F.
Sleep is an important part of the human daily routine. Restoring sleep is strongly related to a better physical, cognitive, and psychological well-being. By contrast, poor or disordered sleep leads to possible impairments of cognitive and psychological functioning and to a worsened general physical health. In this context, understanding changes in sleep quality becomes a research imperative that leads to the need for the definition of what restoring or quality sleep means. This understanding of what "sleep quality" means requires a cross-domain investigation. It arises the need for a comprehensive study that offers a complete taxonomy of sleep monitoring systems, with a focus on sleep quality, and that gives useful insights about which combination of metrics, signals, and sleep variables is the best in relation to different categories of users. The proposed study is focused on systematically categorizing the methods and approaches for sleep quality understanding, with an emphasis on technological approaches, including wearable, on-bed, and actigraphy devices. It offers a systematic review for researchers who are interested in sleep quality identification tasks, and highlights strengths and weaknesses of state-of-the-art metrics and solutions in order to suggest the best choice for new potential research challenges in the field. Another important outcome of the proposed work is the study of the impact on the identified signal metrics and solutions of the different target user populations with their specific user requirements.Source: IEEE access (2019): 167374–167390. doi:10.1109/ACCESS.2019.2953835
DOI: 10.1109/ACCESS.2019.2953835
DOI: 10.1109/access.2019.2953835
Project(s): NESTORE via OpenAIRE

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


2019 Conference object Open Access OPEN

What is next for Indoor Localisation? Taxonomy, protocols, and patterns for advanced Location Based Services
Furfari F., Crivello A., Barsocchi P., Palumbo F., Potortì F.
Indoor localisation systems have been studied in the literature for more than ten years and nowadays are starting to approach the market. While technology is not mature yet, we can argue that the single biggest obstacle to wide adoption is the lack of standard ways to integrate different systems together. The missing pieces are a common taxonomy, definition of services, protocols. This work is an attempt to define what is next for indoor localisation systems in order to promote market adoption. It is a first high-level attempt at defining a taxonomy of indoor positioning systems, at outlining the main phases of a protocol for the utilisation of different cooperating indoor localisation systems, and at drawing a vision of services and applications in the close future.Source: 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 30 Sept.-3 Oct. 2019
DOI: 10.1109/IPIN.2019.8911759
DOI: 10.1109/ipin.2019.8911759

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


2019 Conference object Open Access OPEN

Wi-Fi RTT based indoor positioning with dynamic weighted multidimensional scaling
Yan S., Luo H., Zhao F., Shah W., Li Z., Crivello A.
Indoor positioning methods have appeared to fulfill indoor location-based systems requirements, it is still a great challenge to obtain high precision results of indoor positioning. For example, fingerprint-based methods reach high performances but have a high cost for to survey the environment in order to collect sample and to maintain location fingerprints. Systems based on log-distance path loss model suffer from the multi-path problem and the adjustment of Wi-Fi station powers, and achieve low accuracy in complex environments. The appearance of fine time measurement protocol supported Wi-Fi access points provide a novel way to develop accurate indoor positioning algorithms. Considering the influence of the indoor multi-path effect to the fine time measurement ranging accuracy, we propose a multi-dimensional scaling based positioning algorithm to reduce the impact of ranging errors. We leverage the multidimensional scaling algorithm to estimate the rough position of positioning clients. Successively, adjusting the weight of fine time measurement ranging, we optimize the positioning results with the application of a SMACOF strategy. Through experiments conducted in a complex real-world scenario, we demonstrate that the system proposed reach an accuracy below the 2.5 meters at 80% of the cases.Source: 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Pisa, Italy, 30 Sept.-3 Oct. 2019
DOI: 10.1109/IPIN.2019.8911783
DOI: 10.1109/ipin.2019.8911783

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


2019 Report Open Access OPEN

Nestore - D3.2.2 - Environmental Wireless Sensor Network (WSN) prototypes
Palumbo F., Baronti P., Miori V., Potortì F., Crivello A., Girolami M., Furfari F., Denna E., Civiello M., Mauri M.
This document extends the deliverable D3.2.1 - Environmental Wireless Sensor Network (WSN) prototypes describing: i) the outcomes of the final iteration of the sensors selection for developing the environmental monitoring system of NESTORE; ii) the integrated system tests on the selected sensors. The selection followed the recommendations coming from the WP2 activities in terms of needed monitoring variables and unobtrusiveness. The document also presents the chosen technologies and their integration in the system using available off-the-shelf and custom devices by means of the Web of Things paradigm.Source: Project report, Nestore, Deliverable D3.2.2, 2019
Project(s): NESTORE via OpenAIRE

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