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2007
Journal article
Restricted
Wireless sensor networks: a survey on the state of the art and the 802.15.4 and zigBee standards
Baronti P., Pillai P., Chook V., Chessa S., Gotta A., Hu Y. F.
Wireless sensor networks are an emerging technology for low-cost, unattended monitoring of a wide range of environments, and their importance has been enforced by the recent delivery of the IEEE 802.15.4 standard for the physical and MAC layers and the forthcoming Zigbee standard for the network and application layers. The fast progress of research on energy efficiency, networking, data management and security in wireless sensor networks, and the need to compare with the solutions adopted in the standards motivates the need for a survey on this field.Source: Computer communications 30 (2007): 1655–1695.
Baronti P., Pillai P., Chook V., Chessa S., Gotta A., Hu Y. F.
Wireless sensor networks are an emerging technology for low-cost, unattended monitoring of a wide range of environments, and their importance has been enforced by the recent delivery of the IEEE 802.15.4 standard for the physical and MAC layers and the forthcoming Zigbee standard for the network and application layers. The fast progress of research on energy efficiency, networking, data management and security in wireless sensor networks, and the need to compare with the solutions adopted in the standards motivates the need for a survey on this field.Source: Computer communications 30 (2007): 1655–1695.
See at:
scienceserver.cilea.it 
| CNR ExploRA
2004
Bachelor thesis
Unknown
DSDSR: A dependable secure data storage and retrieval system for mobile ad-hoc wireless networks
Baronti P.
An abstract is not available
Baronti P.
An abstract is not available
See at: CNR ExploRA
2005
Conference article
Restricted
MaD-WiSe: programming and accessing data in a wireless sensor networks
Amato G., Baronti P., Chessa S.
MaD-WiSe is a wireless sensor network database designed to perform in-network distributed query processing and to manage acquired data. This paper briefly presents the MaD-WiSe system and its query processing model based on data streams. Then, it focuses on the MaDWiSe graphical user interface, which supports query definition and injection and query results collection.Source: International Conference on Computer as a Tool. EUROCON 2005., pp. 1846–1849, Belgrado, 21-24 Nov. 2005
DOI: 10.1109/eurcon.2005.1630339
Metrics:
Amato G., Baronti P., Chessa S.
MaD-WiSe is a wireless sensor network database designed to perform in-network distributed query processing and to manage acquired data. This paper briefly presents the MaD-WiSe system and its query processing model based on data streams. Then, it focuses on the MaDWiSe graphical user interface, which supports query definition and injection and query results collection.Source: International Conference on Computer as a Tool. EUROCON 2005., pp. 1846–1849, Belgrado, 21-24 Nov. 2005
DOI: 10.1109/eurcon.2005.1630339
Metrics:
See at:
arpi.unipi.it | doi.org | ieeexplore.ieee.org | www.scopus.com | CNR ExploRA
2006
Report
Unknown
Networking JER Interim report
Chessa S., Baronti P.
This deliverable D4a reports on the different activities carried out in WP 2200. The structure and organization of WP 2200 are described. The achievements obtained since the start of the project are reported.Source: Project report, SatNex, Deliverable D4a, 2006
Chessa S., Baronti P.
This deliverable D4a reports on the different activities carried out in WP 2200. The structure and organization of WP 2200 are described. The achievements obtained since the start of the project are reported.Source: Project report, SatNex, Deliverable D4a, 2006
See at: CNR ExploRA
2007
Conference article
Unknown
Query optimization for wireless sensor network databases in the MadWise system
Amato G., Baronti P., Chessa S.
We propose a comprehensive approach to distributed query processing in wireless sensor networks. In our proposal we reinterpret the classical approach to database system design according to the wireless sensor networks context, and we redefine the aspects related to the definition of a query language, data model, query algebra, and query optimization strategies. We show that our approach en- ables optimizations of the query plan which may reduce the costs, in terms of consumed energy, of orders of magnitude.Source: XV Convegno Nazionale su Sistemi Evolutivi per Basi di Dati. SEBD 2007, pp. 124–135, Fasano, Brindisi, Italy, 17-20 June 2007
Amato G., Baronti P., Chessa S.
We propose a comprehensive approach to distributed query processing in wireless sensor networks. In our proposal we reinterpret the classical approach to database system design according to the wireless sensor networks context, and we redefine the aspects related to the definition of a query language, data model, query algebra, and query optimization strategies. We show that our approach en- ables optimizations of the query plan which may reduce the costs, in terms of consumed energy, of orders of magnitude.Source: XV Convegno Nazionale su Sistemi Evolutivi per Basi di Dati. SEBD 2007, pp. 124–135, Fasano, Brindisi, Italy, 17-20 June 2007
See at: CNR ExploRA
2005
Report
Open Access
Connection-oriented communication protocol in wireless sensor networks
Amato G., Baronti P., Chessa S.
Several sensor network applications based on data diffusion and data management can determine the communication transfer rate between two sensors beforehand. In this framework, we consider the problem of energy efficient communication among nodes of a wireless sensor network and propose an application-driven approach that minimizes radio activity intervals and prolongs network lifetime. On the basis of possible communication delays we estimate packet arrival intervals at any intermediate hop of a fixed-rate data path. We propose two different strategies of radio activity minimization that maintain the radio switched on just in the expected packet arrival intervals and guarantee low communication latency. We define a probabilistic model that allows the evaluation of the packet loss probability that results from the reduced radio activity. The model is used to optimally choose the radio activity intervals that achieve a certain probability of successful packet delivery. Relying on the probabilistic model we also define a cost model that estimates the energy consumption of the proposed strategies, under specific settings. We finally validate our work with a simulation made with Tossim (the Berkeley motes' simulator). The simulation results confirm the validity of the approach and the accuracy of the analytic models.Source: ISTI Technical reports, 2005
Amato G., Baronti P., Chessa S.
Several sensor network applications based on data diffusion and data management can determine the communication transfer rate between two sensors beforehand. In this framework, we consider the problem of energy efficient communication among nodes of a wireless sensor network and propose an application-driven approach that minimizes radio activity intervals and prolongs network lifetime. On the basis of possible communication delays we estimate packet arrival intervals at any intermediate hop of a fixed-rate data path. We propose two different strategies of radio activity minimization that maintain the radio switched on just in the expected packet arrival intervals and guarantee low communication latency. We define a probabilistic model that allows the evaluation of the packet loss probability that results from the reduced radio activity. The model is used to optimally choose the radio activity intervals that achieve a certain probability of successful packet delivery. Relying on the probabilistic model we also define a cost model that estimates the energy consumption of the proposed strategies, under specific settings. We finally validate our work with a simulation made with Tossim (the Berkeley motes' simulator). The simulation results confirm the validity of the approach and the accuracy of the analytic models.Source: ISTI Technical reports, 2005
See at:
ISTI Repository 
| CNR ExploRA
2005
Report
Open Access
MaD-WiSe: programming and accessing data in a wireless sensor networks
Amato G., Baronti P., Chessa S.
MaD-WiSe is a wireless sensor network database designed to perform in-network distributed query processing and to manage acquired data. This paper briefly presents the MaD-WiSe system and its query processing model based on data streams. Then, it focuses on the MaD-WiSe graphical user interface, which supports query definition and injection and query results collection.Source: ISTI Technical reports, 2005
Amato G., Baronti P., Chessa S.
MaD-WiSe is a wireless sensor network database designed to perform in-network distributed query processing and to manage acquired data. This paper briefly presents the MaD-WiSe system and its query processing model based on data streams. Then, it focuses on the MaD-WiSe graphical user interface, which supports query definition and injection and query results collection.Source: ISTI Technical reports, 2005
See at:
ISTI Repository | CNR ExploRA
2005
Report
Open Access
The stream system: a data collection and communication abstraction for sensor networks
Amato G., Baronti P., Chessa S., Masi V.
Sensor network software is still in its youth. Due to sensor hardware limitations and the highly specific nature of application domains, existing software is generally poorly structured. It mixes data collection activities with data management, data storage/retrieval and intra/inter-sensor data communication with the actual data processing required by the application. We identify data collection, intra-sensor and inter-sensor communication as recurring activities in sensor network applications and propose a software module that abstracts these activities: the Stream System. Applications developed on top of if can be organized as a set of computational entities that are provided with a uniform view of such activities through the concept of streams. Streams represent a flow of data records that either (i) originate from a local transducer and can be read by a local entity, (ii) originate from a local entity and can be read by another local entity or (iii) originate from a local entity and can be read by a remote entity i.e., one running on a different sensor. Applications disregard the actual implementation details of collecting transducer readings and passing such data to other local or remote computational entities and rely on the Stream System to provide a record oriented data service in this respect.Source: ISTI Technical reports, 2005
Amato G., Baronti P., Chessa S., Masi V.
Sensor network software is still in its youth. Due to sensor hardware limitations and the highly specific nature of application domains, existing software is generally poorly structured. It mixes data collection activities with data management, data storage/retrieval and intra/inter-sensor data communication with the actual data processing required by the application. We identify data collection, intra-sensor and inter-sensor communication as recurring activities in sensor network applications and propose a software module that abstracts these activities: the Stream System. Applications developed on top of if can be organized as a set of computational entities that are provided with a uniform view of such activities through the concept of streams. Streams represent a flow of data records that either (i) originate from a local transducer and can be read by a local entity, (ii) originate from a local entity and can be read by another local entity or (iii) originate from a local entity and can be read by a remote entity i.e., one running on a different sensor. Applications disregard the actual implementation details of collecting transducer readings and passing such data to other local or remote computational entities and rely on the Stream System to provide a record oriented data service in this respect.Source: ISTI Technical reports, 2005
See at:
ISTI Repository | CNR ExploRA
2006
Report
Open Access
Wireless Sensor Networks: a Survey on the State of the Art and the 802.15.4 and ZigBee Standards
Baronti P., Pillai P., Chook V., Chessa S., Gotta A., Hu Y. F.
Wireless sensor networks are an emerging technology for low-cost, unattended monitoring of a wide range of environments, and their importance has been enforced by the recent delivery of the IEEE 802.15.4 standard for the physical and MAC layers and the forthcoming Zigbee standard for the network and application layers. The fast progress of research on energy efficiency, networking, data management and security in wireless sensor networks, and the need to compare with the solutions adopted in the standards motivates the need for a survey on this field.Source: ISTI Technical reports, 2006
Baronti P., Pillai P., Chook V., Chessa S., Gotta A., Hu Y. F.
Wireless sensor networks are an emerging technology for low-cost, unattended monitoring of a wide range of environments, and their importance has been enforced by the recent delivery of the IEEE 802.15.4 standard for the physical and MAC layers and the forthcoming Zigbee standard for the network and application layers. The fast progress of research on energy efficiency, networking, data management and security in wireless sensor networks, and the need to compare with the solutions adopted in the standards motivates the need for a survey on this field.Source: ISTI Technical reports, 2006
See at:
ISTI Repository | CNR ExploRA
2018
Report
Open Access
NESTORE - The NESTORE specific ontology
Cândea C., Staicu M., Cândea G., Zgripcea C., Orte S., Palumbo F., Baronti P., Gotta A.
The deliverable D2.3 The NESTORE specific ontology is the results of the work from task 2.5 Conversion of the knowledge into ontology, and provides a formal description of the integrated knowledge provided by Task 2.4 in order to guarantee interoperability and integration of NESTORE data model to the UniversAAL platform. The ontology has been developed utilizing the uAAL definitions and using the uAAL eclipse ontology tool editor. The ontology covers the knowledge domain concerning the defintions from D2.1 - Models for Healthy Older People: - Physiological status and Physical Activity Behaviour - Nutrition - Cognitive and Mental Status and Social Behaviour Within the ontology, different types of hierarchies, taxonomies and relationships with respect to the aforementioned areas are defined. The formal languages used to represent knowledge are: Unified Modeling Language and then it will be translated in Java language (in order to be complied with universAAL platform). The modularization and ontology structure are specified by graphical representation. The selected tool editor, uAAL eclipse plugin covers the defined requirements, described in D6.1 Nestore Platform Requirements[], with respect to the architecture, the knowledge model and the browsing capabilities. The developed ontology will be the basic structure for the development of the uAAL Bridge that it will be implemented within the context of Task 6.6. The NESTORE uAAL ontology , will utilize a semantics repository technology that will permit the extended exploitation of the ontology offered capabilities. NESTORE is increasing the uAAL ontologies collection with 40% and expand the uAAL domain usage for Physiological Status and Physical Activity Behaviour (8 ontologies), Nutrition (3 ontologies) and Cognitive and Mental Status and Social Behaviour (4 ontologies). The ontology is available as sources code and documentation on the https://git.nestore-coach.eu/uaal/ontologySource: Project report, NESTORE, Deliverable D2.3, 2018
Project(s): NESTORE
Cândea C., Staicu M., Cândea G., Zgripcea C., Orte S., Palumbo F., Baronti P., Gotta A.
The deliverable D2.3 The NESTORE specific ontology is the results of the work from task 2.5 Conversion of the knowledge into ontology, and provides a formal description of the integrated knowledge provided by Task 2.4 in order to guarantee interoperability and integration of NESTORE data model to the UniversAAL platform. The ontology has been developed utilizing the uAAL definitions and using the uAAL eclipse ontology tool editor. The ontology covers the knowledge domain concerning the defintions from D2.1 - Models for Healthy Older People: - Physiological status and Physical Activity Behaviour - Nutrition - Cognitive and Mental Status and Social Behaviour Within the ontology, different types of hierarchies, taxonomies and relationships with respect to the aforementioned areas are defined. The formal languages used to represent knowledge are: Unified Modeling Language and then it will be translated in Java language (in order to be complied with universAAL platform). The modularization and ontology structure are specified by graphical representation. The selected tool editor, uAAL eclipse plugin covers the defined requirements, described in D6.1 Nestore Platform Requirements[], with respect to the architecture, the knowledge model and the browsing capabilities. The developed ontology will be the basic structure for the development of the uAAL Bridge that it will be implemented within the context of Task 6.6. The NESTORE uAAL ontology , will utilize a semantics repository technology that will permit the extended exploitation of the ontology offered capabilities. NESTORE is increasing the uAAL ontologies collection with 40% and expand the uAAL domain usage for Physiological Status and Physical Activity Behaviour (8 ontologies), Nutrition (3 ontologies) and Cognitive and Mental Status and Social Behaviour (4 ontologies). The ontology is available as sources code and documentation on the https://git.nestore-coach.eu/uaal/ontologySource: Project report, NESTORE, Deliverable D2.3, 2018
Project(s): NESTORE
See at:
ISTI Repository | CNR ExploRA
2019
Report
Open Access
Nestore - D4.4 - Dynamic DSS for an Intelligent Coach
Orte S., Subías P., Palumbo F., Girolami M., Baronti P., Sykora M.
This document represents the deliverable D4.4 ("Dynamic DSS for an Intelligent Coach"). It shows the advances in the implementation of the DSS concerning the results already shown in D4.2, where the basics of the DSS, its workflows and algorithms of the first prototype were explained. In Chapter 1, we introduce the architecture of the Decision Support System (DSS) and its modules. In Chapter 2, we present the DSS as a system encompassing multiple workflows, which are explained in detail in Chapter 3. Chapter 4 contains a brief explanation of the modules that form the DSS. Last but not least, Chapter 5 addresses the code generated. In order to preserve the Intellectual Property generated in these tasks, we have split this document in two parts: a public and a private document. We encourage the reader to ask for the private version of D4.4. to get the complete understanding of the technical development carried out in WP4; this public version only outlines what has been realised in terms of workflows, but does not go in depth into algorithms and actual implementation of the different modules.Source: Project report, Nestore, Deliverable D4.4, 2019
Project(s): NESTORE
Orte S., Subías P., Palumbo F., Girolami M., Baronti P., Sykora M.
This document represents the deliverable D4.4 ("Dynamic DSS for an Intelligent Coach"). It shows the advances in the implementation of the DSS concerning the results already shown in D4.2, where the basics of the DSS, its workflows and algorithms of the first prototype were explained. In Chapter 1, we introduce the architecture of the Decision Support System (DSS) and its modules. In Chapter 2, we present the DSS as a system encompassing multiple workflows, which are explained in detail in Chapter 3. Chapter 4 contains a brief explanation of the modules that form the DSS. Last but not least, Chapter 5 addresses the code generated. In order to preserve the Intellectual Property generated in these tasks, we have split this document in two parts: a public and a private document. We encourage the reader to ask for the private version of D4.4. to get the complete understanding of the technical development carried out in WP4; this public version only outlines what has been realised in terms of workflows, but does not go in depth into algorithms and actual implementation of the different modules.Source: Project report, Nestore, Deliverable D4.4, 2019
Project(s): NESTORE
See at:
ISTI Repository | CNR ExploRA
2020
Conference article
Open Access
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
Metrics:
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
Metrics:
See at:
ISTI Repository | doi.org | ieeexplore.ieee.org | ZENODO | CNR ExploRA
2018
Journal article
Open Access
Indoor bluetooth low energy dataset for localization, tracking, occupancy, and social interaction
Baronti P., Barsocchi P., Chessa S., Mavilia F., Palumbo F.
Indoor localization has become a mature research area, but further scientific developments are limited due to the lack of open datasets and corresponding frameworks suitable to compare and evaluate specialized localization solutions. Although several competitions provide datasets and environments for comparing different solutions, they hardly consider novel technologies such as Bluetooth Low Energy (BLE), which is gaining more and more importance in indoor localization due to its wide availability in personal and environmental devices and to its low costs and flexibility. This paper contributes to cover this gap by: (i) presenting a new indoor BLE dataset; (ii) reviewing several, meaningful use cases in different application scenarios; and (iii) discussing alternative uses of the dataset in the evaluation of different positioning and navigation applications, namely localization, tracking, occupancy and social interaction.Source: Sensors (Basel) 18 (2018). doi:10.3390/s18124462
DOI: 10.3390/s18124462
Project(s): NESTORE
Metrics:
Baronti P., Barsocchi P., Chessa S., Mavilia F., Palumbo F.
Indoor localization has become a mature research area, but further scientific developments are limited due to the lack of open datasets and corresponding frameworks suitable to compare and evaluate specialized localization solutions. Although several competitions provide datasets and environments for comparing different solutions, they hardly consider novel technologies such as Bluetooth Low Energy (BLE), which is gaining more and more importance in indoor localization due to its wide availability in personal and environmental devices and to its low costs and flexibility. This paper contributes to cover this gap by: (i) presenting a new indoor BLE dataset; (ii) reviewing several, meaningful use cases in different application scenarios; and (iii) discussing alternative uses of the dataset in the evaluation of different positioning and navigation applications, namely localization, tracking, occupancy and social interaction.Source: Sensors (Basel) 18 (2018). doi:10.3390/s18124462
DOI: 10.3390/s18124462
Project(s): NESTORE
Metrics:
See at:
Sensors | Sensors | ISTI Repository | Sensors | Sensors | CNR ExploRA
2018
Report
Open Access
NESTORE - D3.2.1 - Environmental Wireless Sensor Network (WSN) prototypes
Palumbo F., Baronti P., Miori V., Potortì F., Crivello A.
This document describes the outcomes of the first iteration of the sensors selection for developing the environmental monitoring system of NESTORE. The selection followed the recommendations coming from the WP2 activities in terms of needed monitoring variables and tries to address the requirements coming from the WP6 co-design approach. The document also presents an overview of the chosen technologies and their integration in the system using available off-the-shelf devices by means of the Web of Things paradigm.Source: Project report, NESTORE, Deliverable D3.2.1, 2018
Project(s): NESTORE
Palumbo F., Baronti P., Miori V., Potortì F., Crivello A.
This document describes the outcomes of the first iteration of the sensors selection for developing the environmental monitoring system of NESTORE. The selection followed the recommendations coming from the WP2 activities in terms of needed monitoring variables and tries to address the requirements coming from the WP6 co-design approach. The document also presents an overview of the chosen technologies and their integration in the system using available off-the-shelf devices by means of the Web of Things paradigm.Source: Project report, NESTORE, Deliverable D3.2.1, 2018
Project(s): NESTORE
See at:
ISTI Repository | CNR ExploRA
2020
Contribution to book
Closed Access
Smart sensors in smart cities collaborate for indoor air quality
Baronti P., Barsocchi P., Ferro E., Mavilia F., Piotto M., Strambini L.
This paper presents an example of collaboration between two different air quality monitoring systems, one developed for indoor usage, the other one used in some regions of Italy as an example of citizens' collaborative work for monitoring the air quality in smart cities. The exchange of information between the two systems (the inner one and the external one) allows making a weighted decision for improving the inner air quality. By evaluating both indoor and outdoor air quality levels, a reasoner decides the best policy to be automatically adopted to improve, or at least not worsen, the indoor air quality.Source: ELECTRIMACS 2019, edited by Walter Zamboni, Giovanni Petrone, pp. 339–348. London: Springer, 2020
DOI: 10.1007/978-3-030-37161-6_25
Metrics:
Baronti P., Barsocchi P., Ferro E., Mavilia F., Piotto M., Strambini L.
This paper presents an example of collaboration between two different air quality monitoring systems, one developed for indoor usage, the other one used in some regions of Italy as an example of citizens' collaborative work for monitoring the air quality in smart cities. The exchange of information between the two systems (the inner one and the external one) allows making a weighted decision for improving the inner air quality. By evaluating both indoor and outdoor air quality levels, a reasoner decides the best policy to be automatically adopted to improve, or at least not worsen, the indoor air quality.Source: ELECTRIMACS 2019, edited by Walter Zamboni, Giovanni Petrone, pp. 339–348. London: Springer, 2020
DOI: 10.1007/978-3-030-37161-6_25
Metrics:
See at:
doi.org | link.springer.com | 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
2018
Report
Open Access
NESTORE - Evaluation of universAAL solution (Rev.1)
Candea G., Staicu M., Candea C., Palumbo F., Baronti P., Furfari F., Gotta A., Miori V., Pillitteri L., Portortì F.
This document is the results of work in task T6.2 Evaluation of universAAL solution. Within this task the technological partners from NESTORE reviewed and analyses the official universAAL sources and documentation, realized a Proof-of-Concept. Based on learned lessons and intersecting them with NESTORE requirements are presented conclusions and NESTORE approach relating universAAL support.Source: Project report, NESTORE, Deliverable D6.2, 2018
Project(s): NESTORE
Candea G., Staicu M., Candea C., Palumbo F., Baronti P., Furfari F., Gotta A., Miori V., Pillitteri L., Portortì F.
This document is the results of work in task T6.2 Evaluation of universAAL solution. Within this task the technological partners from NESTORE reviewed and analyses the official universAAL sources and documentation, realized a Proof-of-Concept. Based on learned lessons and intersecting them with NESTORE requirements are presented conclusions and NESTORE approach relating universAAL support.Source: Project report, NESTORE, Deliverable D6.2, 2018
Project(s): NESTORE
See at:
ISTI Repository | CNR ExploRA
2019
Report
Open Access
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
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
See at:
ISTI Repository | CNR ExploRA
2018
Report
Unknown
E-Cabin - Sviluppo del middleware di comunicazione per la raccolta dati e del sistema di backend
Ferro E., Barsocchi P., La Rosa D., Baronti P., Bruno R., Piscione P., Nolich M., Ferrari P., Carciotti S., Buqi R., Camilotti L.
In questo documento sono illustrati i risultati dell'attivita? di sviluppo della piattaforma di raccolta dati di e-Cabin, insieme al sistema di back-end che comprende i servizi di reasoning, storage e visualizzazione dei dati.Source: Project report, E-CABIN, Deliverable D3.4, 2018
Ferro E., Barsocchi P., La Rosa D., Baronti P., Bruno R., Piscione P., Nolich M., Ferrari P., Carciotti S., Buqi R., Camilotti L.
In questo documento sono illustrati i risultati dell'attivita? di sviluppo della piattaforma di raccolta dati di e-Cabin, insieme al sistema di back-end che comprende i servizi di reasoning, storage e visualizzazione dei dati.Source: Project report, E-CABIN, Deliverable D3.4, 2018
See at: CNR ExploRA
2020
Journal article
Open Access
Remote detection of social interactions in indoor environments through bluetooth low energy beacons
Baronti P., Barsocchi P., Chessa S., Crivello A., Girolami M., Mavilia F., Palumbo F.
The way people interact in daily life is a challenging phenomenon to be captured and studied without altering the natural rhythm of the interactions. We investigate the development of automated tools that may provide information to the researchers that analyse interactions among humans. One important requirement of these tools is that should not interfere with the subjects under observation, in order to avoid any alteration in the subject's normal behaviour. Our approach is based on the detection of proximity among groups of people that is obtained using commercial wearable wireless tags based on Bluetooth Low Energy (BLE) and a novel algorithm called Remote Detection of Human Proximity (ReD-HuP) that analyses the wireless signal of tags and produce the proximity information. The algorithm, which has been validated against the ground truth of an experimental dataset, achieves an accuracy of 95.91% and an F-Score of 95.79%.Source: Journal of ambient intelligence and smart environments (Print) 12 (2020): 203–217. doi:10.3233/AIS-200560
DOI: 10.3233/ais-200560
Project(s): NESTORE
Metrics:
Baronti P., Barsocchi P., Chessa S., Crivello A., Girolami M., Mavilia F., Palumbo F.
The way people interact in daily life is a challenging phenomenon to be captured and studied without altering the natural rhythm of the interactions. We investigate the development of automated tools that may provide information to the researchers that analyse interactions among humans. One important requirement of these tools is that should not interfere with the subjects under observation, in order to avoid any alteration in the subject's normal behaviour. Our approach is based on the detection of proximity among groups of people that is obtained using commercial wearable wireless tags based on Bluetooth Low Energy (BLE) and a novel algorithm called Remote Detection of Human Proximity (ReD-HuP) that analyses the wireless signal of tags and produce the proximity information. The algorithm, which has been validated against the ground truth of an experimental dataset, achieves an accuracy of 95.91% and an F-Score of 95.79%.Source: Journal of ambient intelligence and smart environments (Print) 12 (2020): 203–217. doi:10.3233/AIS-200560
DOI: 10.3233/ais-200560
Project(s): NESTORE
Metrics:
See at:
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