2023
Conference article
Open Access
Evaluating the impact of anchors deployment for an AoA-based indoor localization system
Mavilia F., Barsocchi P., Furfari F., Girolami M.
Indoor localization techniques are rapidly moving toward the combination of multiple source of information. Among these, RSS, Time of Flight (ToF), Angle of Arrival (AoA) and of Departure (AoD) represent effective solutions for indoor environments. In this work, we propose an on-going activity investigating the performance of an indoor localization system based on the AoA-Bluetooth 5.1 specification, namely Direction Finding. We evaluate the effect of two anchor deployments and we test our localization algorithm by varying the orientation of the target according to four postures: North, West, South and East. From our study, we observe that anchor nodes deployed on the ceiling provide the best performance in terms of localization error. We conclude this work with a discussion of two further lines of investigation potentially increasing the performance of AoA-based indoor localization systems.Source: WONS 2023 - 18th Wireless On-Demand Network Systems and Services Conference, pp. 20–23, Madonna di Campiglio, Italy, 30/01/2023-01/02/2023
DOI: 10.23919/wons57325.2023.10061949
Metrics:
Mavilia F., Barsocchi P., Furfari F., Girolami M.
Indoor localization techniques are rapidly moving toward the combination of multiple source of information. Among these, RSS, Time of Flight (ToF), Angle of Arrival (AoA) and of Departure (AoD) represent effective solutions for indoor environments. In this work, we propose an on-going activity investigating the performance of an indoor localization system based on the AoA-Bluetooth 5.1 specification, namely Direction Finding. We evaluate the effect of two anchor deployments and we test our localization algorithm by varying the orientation of the target according to four postures: North, West, South and East. From our study, we observe that anchor nodes deployed on the ceiling provide the best performance in terms of localization error. We conclude this work with a discussion of two further lines of investigation potentially increasing the performance of AoA-based indoor localization systems.Source: WONS 2023 - 18th Wireless On-Demand Network Systems and Services Conference, pp. 20–23, Madonna di Campiglio, Italy, 30/01/2023-01/02/2023
DOI: 10.23919/wons57325.2023.10061949
Metrics:
See at:
ISTI Repository 
| ieeexplore.ieee.org 
| CNR ExploRA
2023
Report
Unknown
THE D.3.2.1 - AA@THE User needs, technical requirements and specifications
Pratali L., Campana M. G., Delmastro F., Di Martino F., Pescosolido L., Barsocchi P., Broccia G., Ciancia V., Gennaro C., Girolami M., Lagani G., La Rosa D., Latella D., Magrini M., Manca M., Massink M., Mattioli A., Moroni D., Palumbo F., Paradisi P., Paternò F., Santoro C., Sebastiani L., Vairo C.
Deliverable D3.2.1 del progetto PNRR Ecosistemi ed innovazione - THESource: ISTI Project Report, THE, D3.2, 2023
Pratali L., Campana M. G., Delmastro F., Di Martino F., Pescosolido L., Barsocchi P., Broccia G., Ciancia V., Gennaro C., Girolami M., Lagani G., La Rosa D., Latella D., Magrini M., Manca M., Massink M., Mattioli A., Moroni D., Palumbo F., Paradisi P., Paternò F., Santoro C., Sebastiani L., Vairo C.
Deliverable D3.2.1 del progetto PNRR Ecosistemi ed innovazione - THESource: ISTI Project Report, THE, D3.2, 2023
See at: CNR ExploRA
2023
Conference article
Open Access
A TinyML-approach to detect the proximity of people based on bluetooth low energy beacons
Girolami M., Fattori F., Chessa S.
Proximity detection is the process of estimating the closeness between a target and a point of interest, and it can be estimated with different technologies and techniques. In this paper we focus on how detecting proximity between people with a TinyML-based approach. We analyze RSS values (Received Signal Strength) estimated by a micro-controller and propagated by Bluetooth's tags. To this purpose, we collect a dataset of Bluetooth RSS signals by considering different postures of the involved people. The dataset is adopted to train and test two neural networks: a fully-connected and an LSTM model that we compress to be executed directly on-board of the micro-controller. Experimental results conducted over the dataset show an average precision and recall metrics of 0.8 with both of the models, and with an inference time less than 1 ms.Source: IE 2023 - 19th International Conference on Intelligent Environments, Island of Mauritius, 29-30/06/2023
DOI: 10.1109/ie57519.2023.10179090
Metrics:
Girolami M., Fattori F., Chessa S.
Proximity detection is the process of estimating the closeness between a target and a point of interest, and it can be estimated with different technologies and techniques. In this paper we focus on how detecting proximity between people with a TinyML-based approach. We analyze RSS values (Received Signal Strength) estimated by a micro-controller and propagated by Bluetooth's tags. To this purpose, we collect a dataset of Bluetooth RSS signals by considering different postures of the involved people. The dataset is adopted to train and test two neural networks: a fully-connected and an LSTM model that we compress to be executed directly on-board of the micro-controller. Experimental results conducted over the dataset show an average precision and recall metrics of 0.8 with both of the models, and with an inference time less than 1 ms.Source: IE 2023 - 19th International Conference on Intelligent Environments, Island of Mauritius, 29-30/06/2023
DOI: 10.1109/ie57519.2023.10179090
Metrics:
See at:
ISTI Repository | ieeexplore.ieee.org | CNR ExploRA
2023
Journal article
Open Access
A Bluetooth 5.1 dataset based on angle of arrival and RSS for indoor localization
Girolami M., Furfari F., Barsocchi P., Mavilia F.
Several Radio-Frequency technologies have been explored to evaluate the efficacy of localization algorithms in indoor environments, including Received Signal Strength (RSS), Time of Flight (ToF), and Angle of Arrival (AoA). Among these, AoA technique has been gaining interest when adopted with the Bluetooth protocol. In this work, we describe a data collection measurement campaign of AoA and RSS values collected from Bluetooth 5.1 compliant tags and a set of anchor nodes deployed in the environment. We detail the adopted methodology to collect the dataset and we report all the technical details to reproduce the data collection process. The resulting dataset and the adopted software is publicly available to the community. To collect the dataset, we deploy four anchor nodes and four Bluetooth tags and we reproduce some representative scenarios for indoor localization: calibration, static, mobility, and proximity. Each scenario is annotated with an accurate ground truth (GT). We also assess the quality of the collected data. Specifically, we compute the Mean Absolute Error (MAE) between the AoA estimated by the anchors and the corresponding GT. Additionally, we investigate the packet loss metric which measures the percentage of Bluetooth beacons lost by the anchors.Source: IEEE access 11 (2023): 81763–81776. doi:10.1109/ACCESS.2023.3301126
DOI: 10.1109/access.2023.3301126
Metrics:
Girolami M., Furfari F., Barsocchi P., Mavilia F.
Several Radio-Frequency technologies have been explored to evaluate the efficacy of localization algorithms in indoor environments, including Received Signal Strength (RSS), Time of Flight (ToF), and Angle of Arrival (AoA). Among these, AoA technique has been gaining interest when adopted with the Bluetooth protocol. In this work, we describe a data collection measurement campaign of AoA and RSS values collected from Bluetooth 5.1 compliant tags and a set of anchor nodes deployed in the environment. We detail the adopted methodology to collect the dataset and we report all the technical details to reproduce the data collection process. The resulting dataset and the adopted software is publicly available to the community. To collect the dataset, we deploy four anchor nodes and four Bluetooth tags and we reproduce some representative scenarios for indoor localization: calibration, static, mobility, and proximity. Each scenario is annotated with an accurate ground truth (GT). We also assess the quality of the collected data. Specifically, we compute the Mean Absolute Error (MAE) between the AoA estimated by the anchors and the corresponding GT. Additionally, we investigate the packet loss metric which measures the percentage of Bluetooth beacons lost by the anchors.Source: IEEE access 11 (2023): 81763–81776. doi:10.1109/ACCESS.2023.3301126
DOI: 10.1109/access.2023.3301126
Metrics:
See at:
ieeexplore.ieee.org | ISTI Repository | CNR ExploRA
2023
Conference article
Open Access
Modelling the localization error of an AoA-based localization system
Furfari F., Barsocchi P., Girolami M., Mavilia F.
Indoor localization provides important context information to develop Intelligent Environments able to understand user situations, to react and adapt to changes in the surrounding environment. Bluetooth 5.1 Direction Finding (DF) is a recent specification based on angle of departure (AoD) and arrival (AoA) of radio signals and it is addressed to localize objects or people in indoor scenarios. In this work, we study the error propagation of an indoor localization system based on AoA technique and on multiple anchor receivers.Source: IE 2023 - 19th International Conference on Intelligent Environments, Island of Mauritius, 29-30/06/2023
DOI: 10.1109/ie57519.2023.10179094
Metrics:
Furfari F., Barsocchi P., Girolami M., Mavilia F.
Indoor localization provides important context information to develop Intelligent Environments able to understand user situations, to react and adapt to changes in the surrounding environment. Bluetooth 5.1 Direction Finding (DF) is a recent specification based on angle of departure (AoD) and arrival (AoA) of radio signals and it is addressed to localize objects or people in indoor scenarios. In this work, we study the error propagation of an indoor localization system based on AoA technique and on multiple anchor receivers.Source: IE 2023 - 19th International Conference on Intelligent Environments, Island of Mauritius, 29-30/06/2023
DOI: 10.1109/ie57519.2023.10179094
Metrics:
See at:
ISTI Repository | ieeexplore.ieee.org | CNR ExploRA
2023
Contribution to book
Open Access
Welcome from the demo chairs
Girolami M., Yasumoto K.
This year we had 33 demo proposals submitted and 23 of them have been accepted by the committee. These papers address important problems in several application domains ranging from IoT, wearable and mobile devices, security/privacy, and real-life applications in pervasive computing. During PerCom, one of the selected demos receives the "Best Demo Award" based on its research value, originality, and presentation. We thank all the authors who submitted their innovative demo papers to PerCom this year, and the committee members for volunteering their time and hard to benefit the PerCom community by providing high-quality reviews.Source: 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), 2023
DOI: 10.1109/percomworkshops56833.2023.10150290
Metrics:
Girolami M., Yasumoto K.
This year we had 33 demo proposals submitted and 23 of them have been accepted by the committee. These papers address important problems in several application domains ranging from IoT, wearable and mobile devices, security/privacy, and real-life applications in pervasive computing. During PerCom, one of the selected demos receives the "Best Demo Award" based on its research value, originality, and presentation. We thank all the authors who submitted their innovative demo papers to PerCom this year, and the committee members for volunteering their time and hard to benefit the PerCom community by providing high-quality reviews.Source: 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), 2023
DOI: 10.1109/percomworkshops56833.2023.10150290
Metrics:
See at:
ieeexplore.ieee.org | ISTI Repository | CNR ExploRA
2023
Conference article
Open Access
A VNF-chaining approach for enhancing ground network with UAVs in a crowd-based environment
Bozzone Montagno D., Chessa S., Girolami M., Paganelli F.
In the context of a 5G and beyond network operating in a smart city, in which the fixed network infrastructure is supported by a flock of unmanned aerial vehicles (UAV) operating as carriers of Virtual Network Functions (VNF), we propose a Mixed Integer Linear Programming (MILP) model to place chains of VNFs on a hybrid UAV-terrestrial infrastructure so to maximize the UAV lifetime while considering resource constraints and by taking into account the network traffic originated by crowds of people assembling in the city at given hotpoints. We formalize the UAV deployment problem and we test our solution with a practical scenario based on DoS detection system. The experimental results assess the deployment in a practical scenario of a DoS detection system and show that the proposed solution can effectively enhance the capability of the system to process the input flows under a DoS attack.Source: ISCC 2023 - 28th IEEE Symposium on Computers and Communications, Gammarth, Tunisia, 9-12/07/2023
DOI: 10.1109/iscc58397.2023.10217879
Metrics:
Bozzone Montagno D., Chessa S., Girolami M., Paganelli F.
In the context of a 5G and beyond network operating in a smart city, in which the fixed network infrastructure is supported by a flock of unmanned aerial vehicles (UAV) operating as carriers of Virtual Network Functions (VNF), we propose a Mixed Integer Linear Programming (MILP) model to place chains of VNFs on a hybrid UAV-terrestrial infrastructure so to maximize the UAV lifetime while considering resource constraints and by taking into account the network traffic originated by crowds of people assembling in the city at given hotpoints. We formalize the UAV deployment problem and we test our solution with a practical scenario based on DoS detection system. The experimental results assess the deployment in a practical scenario of a DoS detection system and show that the proposed solution can effectively enhance the capability of the system to process the input flows under a DoS attack.Source: ISCC 2023 - 28th IEEE Symposium on Computers and Communications, Gammarth, Tunisia, 9-12/07/2023
DOI: 10.1109/iscc58397.2023.10217879
Metrics:
See at:
ISTI Repository | ieeexplore.ieee.org | CNR ExploRA
2023
Conference article
Open Access
On the analysis of body orientation for indoor positioning with BLE 5.1 direction finding
Mavilia F., Barsocchi P., Furfari F., La Rosa D., Girolami M.
The last decade showed a clear technological trend toward the adoption of heterogeneous source of information, combined with data-fusion strategies to increase the performance of indoor localization systems. In this respect, the adoption of short-range network protocols such as WiFi and Bluetooth represent a common approach. We investigate, in this work, the use of Bluetooth 5.1 Direction Finding specification to test an indoor localization system solely based on the estimated Angle of Arrival (AoA) between an anchor and a receiver. We first detail our experimental data collection campaign and the adopted hardware. Then, we study not only the accuracy of the estimated angles on two reference planes but also the localization error introduced with the proposed algorithm by varying the body orientation of the target user, namely North, South, West, Est. Experimental results in a real-world indoor environment show an average localization error of 2.08m with only 1 anchor node and 5° of AoA' error for all 28 monitored locations. We also identify regions in which the AoA estimation rapidly decreases, giving rise to the possibility of identifying the boundaries of the adopted technology.Source: ICC 2023 - IEEE International Conference on Communications, pp. 204–209, Roma, Italy, 28/05-01/06/2023
DOI: 10.1109/icc45041.2023.10279029
Metrics:
Mavilia F., Barsocchi P., Furfari F., La Rosa D., Girolami M.
The last decade showed a clear technological trend toward the adoption of heterogeneous source of information, combined with data-fusion strategies to increase the performance of indoor localization systems. In this respect, the adoption of short-range network protocols such as WiFi and Bluetooth represent a common approach. We investigate, in this work, the use of Bluetooth 5.1 Direction Finding specification to test an indoor localization system solely based on the estimated Angle of Arrival (AoA) between an anchor and a receiver. We first detail our experimental data collection campaign and the adopted hardware. Then, we study not only the accuracy of the estimated angles on two reference planes but also the localization error introduced with the proposed algorithm by varying the body orientation of the target user, namely North, South, West, Est. Experimental results in a real-world indoor environment show an average localization error of 2.08m with only 1 anchor node and 5° of AoA' error for all 28 monitored locations. We also identify regions in which the AoA estimation rapidly decreases, giving rise to the possibility of identifying the boundaries of the adopted technology.Source: ICC 2023 - IEEE International Conference on Communications, pp. 204–209, Roma, Italy, 28/05-01/06/2023
DOI: 10.1109/icc45041.2023.10279029
Metrics:
See at:
ISTI Repository | ieeexplore.ieee.org | CNR ExploRA
2023
Journal article
Open Access
A CrowdSensing-based approach for proximity detection in indoor museums with bluetooth tags
Girolami M., La Rosa D., Barsocchi P.
In this work, we investigate the performance of a proximity detection system for visitors in an indoor museum exploiting data collected from the crowd. More specifically, we propose a CrowdSensing-based technique for proximity detection. Users' smartphones can collect and upload RSS (Received Signal Strength) values of nearby Bluetooth tags to a backend server, together with some context-information. In turn, the collected data are elaborated with the goal of calibrating two proximity detection algorithms: a range-based and a learning-based algorithm. We embed the algorithms with R-app, a visiting museum application tested in the Monumental Cemetery's museum located in Piazza dei Miracoli, Pisa (IT). We detail in this work an experimental campaign to measure the performance improvements of the CrowdSensing approach with respect to state-of-the-art algorithms widely adopted in the field of proximity detection. Experimental results show a clear improvement of the performance when data from the crowd are exploited with the proposed architecture.Source: Ad hoc networks 154 (2023). doi:10.1016/j.adhoc.2023.103367
DOI: 10.1016/j.adhoc.2023.103367
Metrics:
Girolami M., La Rosa D., Barsocchi P.
In this work, we investigate the performance of a proximity detection system for visitors in an indoor museum exploiting data collected from the crowd. More specifically, we propose a CrowdSensing-based technique for proximity detection. Users' smartphones can collect and upload RSS (Received Signal Strength) values of nearby Bluetooth tags to a backend server, together with some context-information. In turn, the collected data are elaborated with the goal of calibrating two proximity detection algorithms: a range-based and a learning-based algorithm. We embed the algorithms with R-app, a visiting museum application tested in the Monumental Cemetery's museum located in Piazza dei Miracoli, Pisa (IT). We detail in this work an experimental campaign to measure the performance improvements of the CrowdSensing approach with respect to state-of-the-art algorithms widely adopted in the field of proximity detection. Experimental results show a clear improvement of the performance when data from the crowd are exploited with the proposed architecture.Source: Ad hoc networks 154 (2023). doi:10.1016/j.adhoc.2023.103367
DOI: 10.1016/j.adhoc.2023.103367
Metrics:
See at:
Ad Hoc Networks | ISTI Repository | ISTI Repository | www.sciencedirect.com | CNR ExploRA
2023
Conference article
Open Access
Radio-frequency handoff strategies to seamlessly integrate indoor localization systems
Furfari F., Girolami M., Barsocchi P.
The widespread use of Location Based Services (LBS) drives the pervasive adoption of localization systems available anywhere. Environments equipped with multiple indoor localization systems (ILSs), require managing the transition from one ILS to another in order to continue localizing the user's device even when moving indoors or outdoor-to-indoor environments. In this paper, we focus on the handoff procedure, whose goal is enabling a device to trigger the transition between ILSs when specific conditions are verified. We describe the activation of handoff procedures by considering three types of ILS design and deployment, each with increasing complexity. Moreover, this work defines three handoff algorithms based on the proximity detection, and we test them in a realistic environment characterized by two contiguous ILSs.Source: IPIN 2023 - 13th International Conference on Indoor Positioning and Indoor Navigation, Nuremberg, Germany, 25-28/09/2023
DOI: 10.1109/ipin57070.2023.10332479
Metrics:
Furfari F., Girolami M., Barsocchi P.
The widespread use of Location Based Services (LBS) drives the pervasive adoption of localization systems available anywhere. Environments equipped with multiple indoor localization systems (ILSs), require managing the transition from one ILS to another in order to continue localizing the user's device even when moving indoors or outdoor-to-indoor environments. In this paper, we focus on the handoff procedure, whose goal is enabling a device to trigger the transition between ILSs when specific conditions are verified. We describe the activation of handoff procedures by considering three types of ILS design and deployment, each with increasing complexity. Moreover, this work defines three handoff algorithms based on the proximity detection, and we test them in a realistic environment characterized by two contiguous ILSs.Source: IPIN 2023 - 13th International Conference on Indoor Positioning and Indoor Navigation, Nuremberg, Germany, 25-28/09/2023
DOI: 10.1109/ipin57070.2023.10332479
Metrics:
See at:
ISTI Repository | ieeexplore.ieee.org | CNR ExploRA
2023
Journal article
Open Access
An experimental evaluation based on direction finding specification for indoor localization and proximity detection
Girolami M., Mavilia F., Furfari F., Barsocchi P.
Radio-frequency technologies have been largely explored to deliver reliable indoor localization systems. However, at the current stage, none of the proposed technologies represent a de-facto standard. Although RSS-based (Received Signal Strength) techniques have been extensively studied, they suffer of a number of side-effects mainly caused by the complexity of radio propagation in indoor environments. A possible solution is designing systems exploiting multiple techniques, so that to compensate weaknesses of a specific source of information. Under this respect, Bluetooth represents an interesting technology, combining multiple techniques for indoor localization. In particular, the BT5.1 direction finding specification includes the possibility of estimating the angle between an emitting device and an antenna array. The Angle of Arrival (AoA) provides interesting features for the localization purpose, as it allows estimating the direction from which a signal is propagated. In this work, we detail our experimental setting based on a BT5.1-compliant kit to quantitatively measure the performance in three scenarios: static positioning, mobility and proximity detection. Scenarios provide a robust benchmark allowing us to identify and discuss features of AoA values also in comparison with respect to traditional RSS-based approaches.Source: IEEE journal of indoor and seamless positioning and navigation 2 (2023): 36–50. doi:10.1109/JISPIN.2023.3345268
DOI: 10.1109/jispin.2023.3345268
Metrics:
Girolami M., Mavilia F., Furfari F., Barsocchi P.
Radio-frequency technologies have been largely explored to deliver reliable indoor localization systems. However, at the current stage, none of the proposed technologies represent a de-facto standard. Although RSS-based (Received Signal Strength) techniques have been extensively studied, they suffer of a number of side-effects mainly caused by the complexity of radio propagation in indoor environments. A possible solution is designing systems exploiting multiple techniques, so that to compensate weaknesses of a specific source of information. Under this respect, Bluetooth represents an interesting technology, combining multiple techniques for indoor localization. In particular, the BT5.1 direction finding specification includes the possibility of estimating the angle between an emitting device and an antenna array. The Angle of Arrival (AoA) provides interesting features for the localization purpose, as it allows estimating the direction from which a signal is propagated. In this work, we detail our experimental setting based on a BT5.1-compliant kit to quantitatively measure the performance in three scenarios: static positioning, mobility and proximity detection. Scenarios provide a robust benchmark allowing us to identify and discuss features of AoA values also in comparison with respect to traditional RSS-based approaches.Source: IEEE journal of indoor and seamless positioning and navigation 2 (2023): 36–50. doi:10.1109/JISPIN.2023.3345268
DOI: 10.1109/jispin.2023.3345268
Metrics:
See at:
ieeexplore.ieee.org | ISTI Repository | ISTI Repository | CNR ExploRA
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:
See at:
ISTI Repository | ieeexplore.ieee.org | CNR ExploRA
2022
Journal article
Open Access
A mobility-based deployment strategy for edge data centers
Girolami M., Vitello P., Capponi A., Fiandrino C., Foschini L., Bellavista P.
The main objective of Multi-access Edge Computing (MEC) is to bring computational capabilities at the edge of the network to better support low-latency applications. Such capabilities are typically offered by Edge Data Centers (EDC). The MEC paradigm is not tied to a single radio technology, rather it embraces both cellular and other radio access technologies such as WiFi. Distributed intelligence at the edge for AI purposes requires careful spatial planning of computing and storage resources. The problem of EDC deployment in urban environments is challenging and, to the best of our knowledge, it has been explored only for cellular connectivity so far. In this paper, we study the possibility of deploying EDC without analyzing the expected data traffic load of the cellular network, a kind of information rarely shared by network operators. To this purpose, we propose in this work CLUB, CLUstering-Based strategy tailored on the analysis of urban mobility. We analyze two experimental mobility data sets, and we analyze some mobility features in order to characterize their properties. Finally, we compare the performance of CLUB against state-of-the-art techniques in terms of the outage probability, namely the probability an EDC is not able to serve a request. Our results show that the CLUB strategy is always comparable with respect to our benchmarks, but without using any information related to network traffic.Source: Journal of parallel and distributed computing (Print) 164 (2022): 133–141. doi:10.1016/j.jpdc.2022.03.007
DOI: 10.1016/j.jpdc.2022.03.007
Metrics:
Girolami M., Vitello P., Capponi A., Fiandrino C., Foschini L., Bellavista P.
The main objective of Multi-access Edge Computing (MEC) is to bring computational capabilities at the edge of the network to better support low-latency applications. Such capabilities are typically offered by Edge Data Centers (EDC). The MEC paradigm is not tied to a single radio technology, rather it embraces both cellular and other radio access technologies such as WiFi. Distributed intelligence at the edge for AI purposes requires careful spatial planning of computing and storage resources. The problem of EDC deployment in urban environments is challenging and, to the best of our knowledge, it has been explored only for cellular connectivity so far. In this paper, we study the possibility of deploying EDC without analyzing the expected data traffic load of the cellular network, a kind of information rarely shared by network operators. To this purpose, we propose in this work CLUB, CLUstering-Based strategy tailored on the analysis of urban mobility. We analyze two experimental mobility data sets, and we analyze some mobility features in order to characterize their properties. Finally, we compare the performance of CLUB against state-of-the-art techniques in terms of the outage probability, namely the probability an EDC is not able to serve a request. Our results show that the CLUB strategy is always comparable with respect to our benchmarks, but without using any information related to network traffic.Source: Journal of parallel and distributed computing (Print) 164 (2022): 133–141. doi:10.1016/j.jpdc.2022.03.007
DOI: 10.1016/j.jpdc.2022.03.007
Metrics:
See at:
ISTI Repository | www.sciencedirect.com | 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:
See at:
ISTI Repository | www.mdpi.com | CNR ExploRA
2022
Conference article
Open Access
Encrypted data aggregation in mobile crowdsensing based on differential privacy
Girolami M., Urselli E., Chessa S.
The increasing sensing capabilities of mobile devices enable the collection of sensing-based data sets, by exploiting the active participation of the crowd. Often, it is not required to disclose the identity of the owners of the data, as the sensing information are analyzed only on an aggregated form. In this work we propose a privacy-preserving schema based on differential privacy which offers data integrity and fault tolerance properties. In our schema, data providers firstly add a noise component to the sensed data and, secondly, they encrypt and send the cryptogram to the aggregator. The data aggregator is in charge of only decrypting the cryptograms, by preserving the identify of the data owners. We extend such schema by enabling data providers to submit multiple cryptograms in a time window, by using time-varying encryption keys. We evaluate the impact of the noise component to the generated cryptograms so that to evaluate the data loss during the encryption process.Source: PerCom Workshops 2022 - IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, pp. 22–25, Pisa, Italy, 21-25/03/2022
DOI: 10.1109/percomworkshops53856.2022.9767356
Metrics:
Girolami M., Urselli E., Chessa S.
The increasing sensing capabilities of mobile devices enable the collection of sensing-based data sets, by exploiting the active participation of the crowd. Often, it is not required to disclose the identity of the owners of the data, as the sensing information are analyzed only on an aggregated form. In this work we propose a privacy-preserving schema based on differential privacy which offers data integrity and fault tolerance properties. In our schema, data providers firstly add a noise component to the sensed data and, secondly, they encrypt and send the cryptogram to the aggregator. The data aggregator is in charge of only decrypting the cryptograms, by preserving the identify of the data owners. We extend such schema by enabling data providers to submit multiple cryptograms in a time window, by using time-varying encryption keys. We evaluate the impact of the noise component to the generated cryptograms so that to evaluate the data loss during the encryption process.Source: PerCom Workshops 2022 - IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, pp. 22–25, Pisa, Italy, 21-25/03/2022
DOI: 10.1109/percomworkshops53856.2022.9767356
Metrics:
See at:
ISTI Repository | ieeexplore.ieee.org | CNR ExploRA
2022
Contribution to book
Open Access
Welcome from the Demo Chairs
Girolami M., Peltonen E.
Welcome Message Demo Session IEEE PerCom 2022Source: 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), 2022
DOI: 10.1109/percomworkshops53856.2022.9767348
Metrics:
Girolami M., Peltonen E.
Welcome Message Demo Session IEEE PerCom 2022Source: 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), 2022
DOI: 10.1109/percomworkshops53856.2022.9767348
Metrics:
See at:
ieeexplore.ieee.org | ISTI Repository | CNR ExploRA
2022
Conference article
Open Access
Evaluation of a location coverage model for mobile edge computing
Girolami M., Pacini T., Chessa S.
The Mobile Edge Computing paradigm shifts the computation back to places where it is required. A traditional MEC architecture comprises a number of Edge Data Centers (EDC) in charge of seamlessly providing services to users with wireless network technologies. In this scenario, it becomes crucial to deploy the EDCs in strategic locations, such as highly visited places. In this paper we focus on the deployment phase of an EDC. In particular, we propose a probabilistic model designed to measure the location converge, namely the probability that a candidate location for an EDC is visited by users. Our model is based on the analysis of user's trajectories and on the probability of detouring towards the target locations for the EDS. The information returned by our model offers the possibility of implementing mobility-aware deployment strategies in urban environments. We test the model with two real-world mobility data sets, evaluating its applicability of realistic settings.Source: ICC 2022 - IEEE International Conference on Communications, pp. 5011–5016, Seoul, Republic of Korea, 16-20/05/2022
DOI: 10.1109/icc45855.2022.9838963
Metrics:
Girolami M., Pacini T., Chessa S.
The Mobile Edge Computing paradigm shifts the computation back to places where it is required. A traditional MEC architecture comprises a number of Edge Data Centers (EDC) in charge of seamlessly providing services to users with wireless network technologies. In this scenario, it becomes crucial to deploy the EDCs in strategic locations, such as highly visited places. In this paper we focus on the deployment phase of an EDC. In particular, we propose a probabilistic model designed to measure the location converge, namely the probability that a candidate location for an EDC is visited by users. Our model is based on the analysis of user's trajectories and on the probability of detouring towards the target locations for the EDS. The information returned by our model offers the possibility of implementing mobility-aware deployment strategies in urban environments. We test the model with two real-world mobility data sets, evaluating its applicability of realistic settings.Source: ICC 2022 - IEEE International Conference on Communications, pp. 5011–5016, Seoul, Republic of Korea, 16-20/05/2022
DOI: 10.1109/icc45855.2022.9838963
Metrics:
See at:
ISTI Repository | ieeexplore.ieee.org | CNR ExploRA
2022
Conference article
Open Access
Evaluation of angle of arrival in indoor environments with bluetooth 5.1 direction finding
Girolami M., Barsocchi P., Furfari F., La Rosa D., Mavilia F.
The Bluetooth 5.1. Direction Finding (DF) specification opens to the possibility of estimating the angle between an emitting and a receiving device. Such angle is generally measured estimating the Angle of Arrival (AoA) or the Angle of Departure (AoD). In particular, knowledge about AoA between a set of anchor nodes and a moving target could be used to localize the target, with greater accuracy with respect to traditional approaches based on the Received Signal Strength of the received messages. In this work, we rigorously evaluate the performance of a commercial kit implementing the DF specification, with the purpose of understanding how the AoA measure varies with respect to the angles' ground truth. We describe two real-world experimental scenarios and we compute the errors between the estimated and actual angles. We also discuss three key aspects for the purpose of adopting BT 5.1 in indoor localization applications.Source: WiMob 2022 - 18th International Conference on Wireless and Mobile Computing, Networking and Communications, pp. 284–289, Thessaloniki, Greece, 10-12/10/2022
DOI: 10.1109/wimob55322.2022.9941619
Metrics:
Girolami M., Barsocchi P., Furfari F., La Rosa D., Mavilia F.
The Bluetooth 5.1. Direction Finding (DF) specification opens to the possibility of estimating the angle between an emitting and a receiving device. Such angle is generally measured estimating the Angle of Arrival (AoA) or the Angle of Departure (AoD). In particular, knowledge about AoA between a set of anchor nodes and a moving target could be used to localize the target, with greater accuracy with respect to traditional approaches based on the Received Signal Strength of the received messages. In this work, we rigorously evaluate the performance of a commercial kit implementing the DF specification, with the purpose of understanding how the AoA measure varies with respect to the angles' ground truth. We describe two real-world experimental scenarios and we compute the errors between the estimated and actual angles. We also discuss three key aspects for the purpose of adopting BT 5.1 in indoor localization applications.Source: WiMob 2022 - 18th International Conference on Wireless and Mobile Computing, Networking and Communications, pp. 284–289, Thessaloniki, Greece, 10-12/10/2022
DOI: 10.1109/wimob55322.2022.9941619
Metrics:
See at:
ISTI Repository | ieeexplore.ieee.org | CNR ExploRA
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:
See at:
ISTI Repository | ieeexplore.ieee.org | CNR ExploRA
2022
Report
Unknown
ChAALenge - D6.1: Analisi delle peculiarità di salute della popolazione anziana e definizione requisiti tecnici
Miori V., Belli D., Bacco M F., Baronti P., Barsocchi P., Crivello A., Furfari F., Girolami M., La Rosa D., Mavilia F., Palumbo F., Pillitteri L., Potortì F., Russo D.
In questo documento viene posta particolare attenzione alla malattia dello scompenso cardiaco che è una delle maggiori cause di mortalità e disabilità nella popolazione anziana oltre ad essere la prima causa di ricovero. Sono analizzate le soluzioni di monitoraggio domestico attualmente disponibili e i requisiti tecnici da soddisfare per poter raccogliere e analizzare i dati fisiologici nell'ambiente di vita e riconoscere situazioni di insorgenza o peggioramento di patologie nell'anziano.Source: ISTI Project Report, ChAALenge, D6.1, 2022
Miori V., Belli D., Bacco M F., Baronti P., Barsocchi P., Crivello A., Furfari F., Girolami M., La Rosa D., Mavilia F., Palumbo F., Pillitteri L., Potortì F., Russo D.
In questo documento viene posta particolare attenzione alla malattia dello scompenso cardiaco che è una delle maggiori cause di mortalità e disabilità nella popolazione anziana oltre ad essere la prima causa di ricovero. Sono analizzate le soluzioni di monitoraggio domestico attualmente disponibili e i requisiti tecnici da soddisfare per poter raccogliere e analizzare i dati fisiologici nell'ambiente di vita e riconoscere situazioni di insorgenza o peggioramento di patologie nell'anziano.Source: ISTI Project Report, ChAALenge, D6.1, 2022
See at: CNR ExploRA