-
Laura Belli
Fixed-term Assistant Professor
email:laura.belli[at]unipr.it
mailing address:
Department of Engineering and Architecture
Parco Area delle Scienze, 181/A
I-43124 ParmaLaura Belli was born in Fiorenzuola d’Arda, on April 14th, 1984 and currently is a Fixed-term Assistant Professor at the University of Parma.
She received the Dr. Ing. degree (Master) in Computer Engineering from the University of Parma in 2011.
In 2015, he received his Ph.D. at the Department of Information Engineering of the same university with a thesis entitled “Efficient Data Management with Applications to IoT”.
Since January 2013, he is a member of the Internet of Things Lab (IoTLab) (ex Wireless Ad-Hoc and Sensor Networks Laboratory – WASNLab) at the Department of Engineering and Architecture of the University of Parma. -
- Internet of Things
- Smart Systems
- Database integration
- Mobile computing
- Cloud computing
2024
Martina Galaverni; Giulia Oddi; Luca Preite; Laura Belli; Luca Davoli; Ilaria Marchioni; Margherita Rodolfi; Federico Solari; Deborah Beghè; Tommaso Ganino; Giuseppe Vignali; Gianluigi Ferrari
An IoT-based data analysis system: A case study on tomato cultivation under different irrigation regimes Journal Article
In: Computers and Electronics in Agriculture, 229 , pp. 109660, 2024, ISSN: 0168-1699.
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title = {An IoT-based data analysis system: A case study on tomato cultivation under different irrigation regimes},
author = {Martina Galaverni and Giulia Oddi and Luca Preite and Laura Belli and Luca Davoli and Ilaria Marchioni and Margherita Rodolfi and Federico Solari and Deborah Beghè and Tommaso Ganino and Giuseppe Vignali and Gianluigi Ferrari},
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abstract = {The exploitation of modern technologies in heterogeneous farming scenarios with different crops cultivation is nowadays an effective solution to implement the concept of Smart Agriculture (SA). Following this approach, in this study the tomato plants’ response to different irrigation regimes is investigated through the implementation of an Internet of Things (IoT)-oriented SA data collection and monitoring system. In particular, the experimentation is conducted on tomatoes grown at three different irrigation regimes: namely, at 100%, 60%, and 30% of the Italian irrigation recommendation service, denoted as Irriframe. The proposed platform, denoted as Agriware, is able to: (i) evaluate information from heterogeneous data sources, (ii) calculate agronomic indicators (e.g., Growing Degree Days, GDD), and (iii) monitor on-field parameters (e.g., water consumption). Different plant-related parameters have been collected to assess the response to water stress (e.g., Soil Plant Analysis Development (SPAD), chlorophyll content, fluorescence, and others), along with leaf color and final production evaluations. The obtained results show that the best irrigation regime, in terms of plant health and productivity, corresponds to 60% of Irriframe, allowing significant water savings for the cultivation.},
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The exploitation of modern technologies in heterogeneous farming scenarios with different crops cultivation is nowadays an effective solution to implement the concept of Smart Agriculture (SA). Following this approach, in this study the tomato plants’ response to different irrigation regimes is investigated through the implementation of an Internet of Things (IoT)-oriented SA data collection and monitoring system. In particular, the experimentation is conducted on tomatoes grown at three different irrigation regimes: namely, at 100%, 60%, and 30% of the Italian irrigation recommendation service, denoted as Irriframe. The proposed platform, denoted as Agriware, is able to: (i) evaluate information from heterogeneous data sources, (ii) calculate agronomic indicators (e.g., Growing Degree Days, GDD), and (iii) monitor on-field parameters (e.g., water consumption). Different plant-related parameters have been collected to assess the response to water stress (e.g., Soil Plant Analysis Development (SPAD), chlorophyll content, fluorescence, and others), along with leaf color and final production evaluations. The obtained results show that the best irrigation regime, in terms of plant health and productivity, corresponds to 60% of Irriframe, allowing significant water savings for the cultivation.Laura Belli; Luca Davoli; Gianluigi Ferrari
City2i, innovazione IoT per smart city: l’esempio Parma Miscellaneous
2024.
@misc{bedafe:2024:agendadigcity2i,
title = {City2i, innovazione IoT per smart city: l’esempio Parma},
author = {Laura Belli and Luca Davoli and Gianluigi Ferrari},
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L’integrazione delle tecnologie IoT nelle città intelligenti migliora la qualità della vita urbana. A Parma, la piattaforma city2i® facilita la raccolta e l’analisi dei dati IoT, supportando un’architettura modulare e scalabile. Questo approccio ottimizza le risorse, garantendo sicurezza e interoperabilità per una gestione urbana efficiente.Laura Belli; Luca Davoli; Giulia Oddi; Luca Preite; Martina Galaverni; Tommaso Ganino; Gianluigi Ferrari
IoT-based Data Collection in a Tomato Cultivation Under Different Irrigation Regimes Miscellaneous
2024.
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Giulia Oddi; Laura Belli; Luca Davoli; Martina Galaverni; Ilaria Marchioni; Margherita Rodolfi; Deborah Beghé; Federico Solari; Giuseppe Vignali; Tommaso Ganino; Gianluigi Ferrari
Optimizing Tomato Production through IoT-based Smart Data Collection and Analysis Inproceedings
In: 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE), pp. 45-50, Bari, Italy, 2024.
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title = {Optimizing Tomato Production through IoT-based Smart Data Collection and Analysis},
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abstract = {The always-growing diffusion and adoption of Internet of Things (IoT) technologies is revolutionizing heterogeneous scenarios (e.g., home, industry, safety, etc.), including the agricultural/farming: this paves the way to the Smart Agriculture (SA) paradigm. In detail, this approach leverages the exploitation of IoT smart objects (e.g., sensors, actuators, ground robots, and flying drones) to optimize and improve agricultural practices, eventually improving both sustainability and efficiency. This paper presents an IoT-based data collection and analysis architecture expedient to acquire and manage IoT data streams generated from the field. The proposed approach has been applied to a real experimental use case to optimize tomato production in the Äzienda Sperimentale Stuard" farm located in Parma, Italy. The obtained results highlight the feasibility, sustainability, and gain margins (i.e., in terms of cost/benefits) returned by such a deployment in a real scenario, enabling farmers to make informed decisions based on on-field data acquisition (e.g., reducing water consumption during the growing season).},
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The always-growing diffusion and adoption of Internet of Things (IoT) technologies is revolutionizing heterogeneous scenarios (e.g., home, industry, safety, etc.), including the agricultural/farming: this paves the way to the Smart Agriculture (SA) paradigm. In detail, this approach leverages the exploitation of IoT smart objects (e.g., sensors, actuators, ground robots, and flying drones) to optimize and improve agricultural practices, eventually improving both sustainability and efficiency. This paper presents an IoT-based data collection and analysis architecture expedient to acquire and manage IoT data streams generated from the field. The proposed approach has been applied to a real experimental use case to optimize tomato production in the Äzienda Sperimentale Stuard" farm located in Parma, Italy. The obtained results highlight the feasibility, sustainability, and gain margins (i.e., in terms of cost/benefits) returned by such a deployment in a real scenario, enabling farmers to make informed decisions based on on-field data acquisition (e.g., reducing water consumption during the growing season).Luca Davoli; Hafiz Humza Mahmood Ramzan; Gianluigi Laura Ferrari Belli
CoAP-based Digital Twin Modelling of Heterogeneous IoT Scenarios Inproceedings
In: 10th International Food Operations and Processing Simulation Workshop (FoodOPS 2024), pp. 1-5, Tenerife, Spain, 2024.
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abstract = {Modern societies nowadays require more and more abstraction efforts to hide the complexity of underlying systems and infrastructures. To this end, the concept of Digital Twin (DT) has recently emerged as a key enabler for the digital transformation of well-established architectures toward their virtual representation, opening to intelligent processing capabilities (e.g., monitoring, simulation, prediction, optimization). Aside from defining DTs to enhance these services, another key paradigm that is noteworthy of attention is the Internet of Things (IoT), enabling data and information collection through heterogeneous textitsmart devices (often equipped with sensors and actuators). Thus, combining DTs and IoT together with the Constrained Application Protocol (CoAP) as communication protocol (with its native features), will allow to define scalable and lightweight replicas of real systems, and exploit key features (e.g., service and resource discovery) to provide end users with smart solutions. In this paper, a modelling paradigm for heterogeneous IoT scenarios, based on the definition of a DT for each entity involved in a specific context to be mapped, is detailed. This will allow to textita-priori estimate the behaviour of an IoT ecosystem and provide well-known interaction endpoints to request data from/pushing information to the hidden lower layers of the same ecosystem.},
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Modern societies nowadays require more and more abstraction efforts to hide the complexity of underlying systems and infrastructures. To this end, the concept of Digital Twin (DT) has recently emerged as a key enabler for the digital transformation of well-established architectures toward their virtual representation, opening to intelligent processing capabilities (e.g., monitoring, simulation, prediction, optimization). Aside from defining DTs to enhance these services, another key paradigm that is noteworthy of attention is the Internet of Things (IoT), enabling data and information collection through heterogeneous textitsmart devices (often equipped with sensors and actuators). Thus, combining DTs and IoT together with the Constrained Application Protocol (CoAP) as communication protocol (with its native features), will allow to define scalable and lightweight replicas of real systems, and exploit key features (e.g., service and resource discovery) to provide end users with smart solutions. In this paper, a modelling paradigm for heterogeneous IoT scenarios, based on the definition of a DT for each entity involved in a specific context to be mapped, is detailed. This will allow to textita-priori estimate the behaviour of an IoT ecosystem and provide well-known interaction endpoints to request data from/pushing information to the hidden lower layers of the same ecosystem.Veronica Mattioli; Luca Davoli; Laura Belli; Sara Gambetta; Luca Carnevali; Andrea Sgoifo; Riccardo Raheli; Gianluigi Ferrari
IoT-Based Assessment of a Driver’s Stress Level Journal Article
In: Sensors, 24 (17), 2024, ISSN: 1424-8220.
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abstract = {Driver Monitoring Systems (DMSs) play a key role in preventing hazardous events (e.g., road accidents) by providing prompt assistance when anomalies are detected while driving. Different factors, such as traffic and road conditions, might alter the psycho-physiological status of a driver by increasing stress and workload levels. This motivates the development of advanced monitoring architectures taking into account psycho-physiological aspects. In this work, we propose a novel in-vehicle Internet of Things (IoT)-oriented monitoring system to assess the stress status of the driver. In detail, the system leverages heterogeneous components and techniques to collect driver (and, possibly, vehicle) data, aiming at estimating the driver’s arousal level, i.e., their psycho-physiological response to driving tasks. In particular, a wearable sensorized bodice and a thermal camera are employed to extract physiological parameters of interest (namely, the heart rate and skin temperature of the subject), which are processed and analyzed with innovative algorithms. Finally, experimental results are obtained both in simulated and real driving scenarios, demonstrating the adaptability and efficacy of the proposed system.},
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Driver Monitoring Systems (DMSs) play a key role in preventing hazardous events (e.g., road accidents) by providing prompt assistance when anomalies are detected while driving. Different factors, such as traffic and road conditions, might alter the psycho-physiological status of a driver by increasing stress and workload levels. This motivates the development of advanced monitoring architectures taking into account psycho-physiological aspects. In this work, we propose a novel in-vehicle Internet of Things (IoT)-oriented monitoring system to assess the stress status of the driver. In detail, the system leverages heterogeneous components and techniques to collect driver (and, possibly, vehicle) data, aiming at estimating the driver’s arousal level, i.e., their psycho-physiological response to driving tasks. In particular, a wearable sensorized bodice and a thermal camera are employed to extract physiological parameters of interest (namely, the heart rate and skin temperature of the subject), which are processed and analyzed with innovative algorithms. Finally, experimental results are obtained both in simulated and real driving scenarios, demonstrating the adaptability and efficacy of the proposed system.Laura Belli; Luca Davoli; Gianluigi Ferrari; Giulia Oddi
IoT in agricoltura: vantaggi e casi d’uso reali Miscellaneous
2024.
@misc{bedafeod:2024:agri,
title = {IoT in agricoltura: vantaggi e casi d’uso reali},
author = {Laura Belli and Luca Davoli and Gianluigi Ferrari and Giulia Oddi},
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L’integrazione di tecnologie IoT in agricoltura permette un monitoraggio preciso delle coltivazioni, ottimizzando l’uso delle risorse idriche e prevedendo informazioni agronomiche fondamentali. Uno studio dell’Università di Parma esplora i benefici di tali tecnologie, presentando due casi d’uso reali: l’ottimizzazione dell’irrigazione del pomodoro e la predizione del periodo di raccolta del luppolo.Anum Nawaz; Laura Belli; Luca Davoli; Gianluigi Ferrari
Hyperledger Fabric in Precision Agriculture: A Study on Data Integrity and Availability Inproceedings
In: 2024 International Conference on Computer, Information and Telecommunication Systems (CITS), pp. 1-8, Girona, Spain, 2024.
@inproceedings{nabedafe:2024:cits,
title = {Hyperledger Fabric in Precision Agriculture: A Study on Data Integrity and Availability},
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abstract = {The increasing severity of weather events and growing demands for food pose significant challenges to farming and agricultural activities. Over the past decades, the deployment of data acquisition and Internet of Things (IoT)-oriented technologies has emerged as a relevant solution to face these issues, with a primary reason behind this digital agricultural revolution being the cost-effectiveness of data collection in various areas (e.g., soil conditions, crop development, weather patterns). On the basis of these technological advancements, in this paper we discuss on a fully-distributed blockchain-based IoT-oriented agricultural monitoring system based on an integrated Hyperledger Fabric framework. The proposed platform is designed to maximize the efficiency of the approach, to analyze several potential benefits (including, as an example, possible increased food production on reduced land areas, with lower input requirements and a diminished environmental impact), and to effectively aggregate and interpret data into actionable insights for farmers and policymakers. We then propose a preliminary system's deployment, which is instrumental to reflect on platform's scalability, inclusiveness, and modularity. The obtained results highlight its suitability to enhance precision agriculture with secure tracking features.},
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The increasing severity of weather events and growing demands for food pose significant challenges to farming and agricultural activities. Over the past decades, the deployment of data acquisition and Internet of Things (IoT)-oriented technologies has emerged as a relevant solution to face these issues, with a primary reason behind this digital agricultural revolution being the cost-effectiveness of data collection in various areas (e.g., soil conditions, crop development, weather patterns). On the basis of these technological advancements, in this paper we discuss on a fully-distributed blockchain-based IoT-oriented agricultural monitoring system based on an integrated Hyperledger Fabric framework. The proposed platform is designed to maximize the efficiency of the approach, to analyze several potential benefits (including, as an example, possible increased food production on reduced land areas, with lower input requirements and a diminished environmental impact), and to effectively aggregate and interpret data into actionable insights for farmers and policymakers. We then propose a preliminary system's deployment, which is instrumental to reflect on platform's scalability, inclusiveness, and modularity. The obtained results highlight its suitability to enhance precision agriculture with secure tracking features.Martina Galaverni; Ilaria Marchioni; Laura Belli; Tommaso Ganino; Giulia Oddi; Deborah Beghé; Margherita Rodolfi; Luca Davoli; Gianluigi Ferrari
Poster: Evaluation of Hop Cone Maturation through Internet of Things (IoT) and Smart Farming Technologies. A Preliminary Study Inproceedings
In: 39th EBC Congress, pp. 1-1, Lille, France, 2024.
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Laura Belli; Luca Davoli; Gianluigi Ferrari
A Cloud-Oriented Indoor-Outdoor Real-Time Localization IoT Architecture for Industrial Environments Inproceedings
In: 2024 IEEE 21st Consumer Communications & Networking Conference (CCNC), pp. 1-6, Las Vegas, NV, USA, 2024, ISSN: 2331-9860.
@inproceedings{bedafe:2024:iiwot,
title = {A Cloud-Oriented Indoor-Outdoor Real-Time Localization IoT Architecture for Industrial Environments},
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abstract = {Localization services for precise and continuous monitoring of the locations of both humans and vehicles in industrial environments are among the most relevant applications in Industrial Internet of Things (IIoT) contexts, to maximize safety and optimize operational activities. Unfortunately, localization in industrial scenarios is particularly challenging because targets can generally move freely in both indoor and outdoor areas. In this paper, we propose a localization monitoring architecture based on a prototypical wearable IoT device equipped with Ultra-Wide Band (UWB), inertial, and GNSS/RTK technologies for seamless localization in heterogeneous environments. We focus on a Web of Things (WoT) approach, verifying suitability and limitations in a real use case scenario. Our approach shows that the proposed architecture can effectively enhance the safety of workers, detecting potentially dangerous events and triggering alarms (e.g., via smart buzzers or gas concentration warning devices) based on a cloud WoT architecture.},
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Localization services for precise and continuous monitoring of the locations of both humans and vehicles in industrial environments are among the most relevant applications in Industrial Internet of Things (IIoT) contexts, to maximize safety and optimize operational activities. Unfortunately, localization in industrial scenarios is particularly challenging because targets can generally move freely in both indoor and outdoor areas. In this paper, we propose a localization monitoring architecture based on a prototypical wearable IoT device equipped with Ultra-Wide Band (UWB), inertial, and GNSS/RTK technologies for seamless localization in heterogeneous environments. We focus on a Web of Things (WoT) approach, verifying suitability and limitations in a real use case scenario. Our approach shows that the proposed architecture can effectively enhance the safety of workers, detecting potentially dangerous events and triggering alarms (e.g., via smart buzzers or gas concentration warning devices) based on a cloud WoT architecture.Luca Davoli; Laura Belli; Gianluigi Ferrari; Elisa Londero; Paolo Azzoni
An Edge Computing-Oriented WoT Architecture for Air Quality Monitoring in Mobile Vehicular Scenarios Inproceedings
In: 2024 IEEE 21st Consumer Communications & Networking Conference (CCNC), pp. 1-7, Las Vegas, NV, USA, 2024, ISSN: 2331-9860.
@inproceedings{dabefeloaz:2024:iiwot,
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abstract = {Nowadays, the need to efficiently process information in Internet of Things (IoT)-oriented heterogeneous scenarios has increased significantly, e.g., in all scenarios where unobtrusive environmental monitoring is beneficial for the involved people (e.g., inside public transport vehicles, indoor workplaces and offices, large public infrastructures, etc.). This objective typically requires the combination of heterogeneous IoT systems, which need to efficiently share information, e.g., through the Web of Things (WoT) paradigm. In this paper, we propose an edge computing-oriented flexible WoT architecture, with distributed intelligence, for air quality monitoring and prediction inside a public transport bus. Our results show that the proposed architecture allows seamless integration of heterogeneous IoT systems according to a WoT perspective, exploiting the device/edge/fog computing continuum and using containerized and secure processing modules.},
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Nowadays, the need to efficiently process information in Internet of Things (IoT)-oriented heterogeneous scenarios has increased significantly, e.g., in all scenarios where unobtrusive environmental monitoring is beneficial for the involved people (e.g., inside public transport vehicles, indoor workplaces and offices, large public infrastructures, etc.). This objective typically requires the combination of heterogeneous IoT systems, which need to efficiently share information, e.g., through the Web of Things (WoT) paradigm. In this paper, we propose an edge computing-oriented flexible WoT architecture, with distributed intelligence, for air quality monitoring and prediction inside a public transport bus. Our results show that the proposed architecture allows seamless integration of heterogeneous IoT systems according to a WoT perspective, exploiting the device/edge/fog computing continuum and using containerized and secure processing modules.Luca Davoli; Laura Belli; Alessandro Dall'Olio; Francesco Di Nocera; Paolo Adorni; Alessandro Cantelli; Gianluigi Ferrari
Data Integration in a Smart City: A Real Case Book Chapter
In: Information and Communications Technologies for Smart Cities and Societies, 5 , Chapter 2, pp. 11-24, Springer Nature Switzerland, 2024.
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abstract = {The introduction and continuous integration of Internet of Things (IoT)-oriented technologies in urban environments leads to enhanced solutions in several domains (such as mobility, health, energy management, environmental monitoring, etc.), thus making a city “smart” and ultimately benefiting the everyday life of its citizens. As IoT systems are widely known to be producers of (often a very large amount of) heterogeneous data, in this chapter we discuss a modular and scalable approach to handle IoT-based data collection and management in a real smart city case, namely, that of the city of Parma, Italy. The proposed IoT infrastructure, the core component of which is a logical processing entity, acting as middleware and denoted as “city2i®,” in charge of "digesting" the heterogeneous information generated by multiple data sources, allows the municipality to monitor the city status (from multiple perspectives) and to highlight “hidden” correlations among collected data.},
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The introduction and continuous integration of Internet of Things (IoT)-oriented technologies in urban environments leads to enhanced solutions in several domains (such as mobility, health, energy management, environmental monitoring, etc.), thus making a city “smart” and ultimately benefiting the everyday life of its citizens. As IoT systems are widely known to be producers of (often a very large amount of) heterogeneous data, in this chapter we discuss a modular and scalable approach to handle IoT-based data collection and management in a real smart city case, namely, that of the city of Parma, Italy. The proposed IoT infrastructure, the core component of which is a logical processing entity, acting as middleware and denoted as “city2i®,” in charge of "digesting" the heterogeneous information generated by multiple data sources, allows the municipality to monitor the city status (from multiple perspectives) and to highlight “hidden” correlations among collected data.2023
Luca Davoli; Laura Belli; Gianluigi Ferrari
Air quality dataset from an indoor airport travelers transit area Journal Article
In: Data in Brief, 52 , pp. 109821, 2023, ISSN: 2352-3409.
@article{dabefe:2023:dib,
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abstract = {The experimental dataset (organized in a semicolon-separated text format) is composed by air quality records collected over a 1-year period (October 2022-October 2023) in an indoor travelers’ transit area in the Brindisi airport, Italy. In detail, the dataset consists of three CSV files (ranging from 7M records to 11M records) resulting from the on-field data collection performed by three prototypical Internet of Things (IoT) sensing nodes, designed and implemented at the IoTLab of the University of Parma, Italy, featuring a Raspberry Pi 4 (as processing unit) which three low-cost commercial sensors (namely: Adafruit MiCS5524, Sensirion SCD30, Sensirion SPS30) are connected to. The sensors sample the air in the monitored static indoor environment every 2 s. Each collected record composing the experimental dataset contains (i) the identifier of the IoT node that sampled the air parameters; (ii) the presence of gases (as a unified value concentration); (iii) the concentration of carbon dioxide (CO2) in the travelers’ transit area, together with air temperature and humidity; and (iv) the concentration of particulate matter (PM) in the indoor monitored environment – in terms of particles’ mass concentration (µg/m3), number of particles (#/cm3), and typical particle size (µm) – for particles with a diameter up to 0.5 µm (PM0.5), 1 µm (PM1), 2.5 µm (PM2.5), 4 µm (PM4), and 10 µm (PM10). Therefore, on the basis of the monitored air parameters in the indoor travelers’ transit area, the experimental dataset might be expedient for further analyses – e.g., for calculating Air Quality Indexes (AQIs) taking into account the collected information – and for comparison with information sampled in different contexts and scenarios – examples could be indoor domestic environments, as well as outdoor monitoring in smart cities or public transports.},
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The experimental dataset (organized in a semicolon-separated text format) is composed by air quality records collected over a 1-year period (October 2022-October 2023) in an indoor travelers’ transit area in the Brindisi airport, Italy. In detail, the dataset consists of three CSV files (ranging from 7M records to 11M records) resulting from the on-field data collection performed by three prototypical Internet of Things (IoT) sensing nodes, designed and implemented at the IoTLab of the University of Parma, Italy, featuring a Raspberry Pi 4 (as processing unit) which three low-cost commercial sensors (namely: Adafruit MiCS5524, Sensirion SCD30, Sensirion SPS30) are connected to. The sensors sample the air in the monitored static indoor environment every 2 s. Each collected record composing the experimental dataset contains (i) the identifier of the IoT node that sampled the air parameters; (ii) the presence of gases (as a unified value concentration); (iii) the concentration of carbon dioxide (CO2) in the travelers’ transit area, together with air temperature and humidity; and (iv) the concentration of particulate matter (PM) in the indoor monitored environment – in terms of particles’ mass concentration (µg/m3), number of particles (#/cm3), and typical particle size (µm) – for particles with a diameter up to 0.5 µm (PM0.5), 1 µm (PM1), 2.5 µm (PM2.5), 4 µm (PM4), and 10 µm (PM10). Therefore, on the basis of the monitored air parameters in the indoor travelers’ transit area, the experimental dataset might be expedient for further analyses – e.g., for calculating Air Quality Indexes (AQIs) taking into account the collected information – and for comparison with information sampled in different contexts and scenarios – examples could be indoor domestic environments, as well as outdoor monitoring in smart cities or public transports.Luca Davoli; Laura Belli; Gianluigi Ferrari
Indoor Air Quality Monitoring @ Brindisi Airport Miscellaneous
2023.
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title = {Indoor Air Quality Monitoring @ Brindisi Airport},
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abstract = {The experimental dataset here represented is composed by 3 CSV files (ranging from 7M records to 11M records), each corresponding to air quality records -- related to the presence of gases (as a unified value concentration); the concentration of carbon dioxide (CO2), together with air temperature and humidity; and the concentration of particulate matter (PM) in the monitored environment (PM0.5, PM1, PM2.5, PM4, PM10) -- sampled (every 2 sec) over a 1-year period (October 2022-October 2023) in an indoor travelers’ transit area in the Brindisi airport, Italy, in the aim of the European project InSecTT (https://www.insectt.eu/, https://cordis.europa.eu/project/id/876038/).
In particular, each CSV file has been generated by a prototypical Internet of Things (IoT) sensing node, designed at the IoTLab (https://iotlab.unipr.it/) of the University of Parma, Italy, exploiting a Raspberry Pi 4 (as processing unit) and three low-cost commercial sensors (namely: Adafruit MiCS5524, Sensirion SCD30, Sensirion SPS30). Then, as a time reference, each record contains the Unix-like data collection timestamp and the identity of the IoT node sampling the air parameters (for safety purposes, the association with a generic color name in the CSV file name has been a consequence of an anonymization naming process for the IoT nodes, in order to hide their precise positions inside the airside transit area).},
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The experimental dataset here represented is composed by 3 CSV files (ranging from 7M records to 11M records), each corresponding to air quality records -- related to the presence of gases (as a unified value concentration); the concentration of carbon dioxide (CO2), together with air temperature and humidity; and the concentration of particulate matter (PM) in the monitored environment (PM0.5, PM1, PM2.5, PM4, PM10) -- sampled (every 2 sec) over a 1-year period (October 2022-October 2023) in an indoor travelers’ transit area in the Brindisi airport, Italy, in the aim of the European project InSecTT (https://www.insectt.eu/, https://cordis.europa.eu/project/id/876038/).
In particular, each CSV file has been generated by a prototypical Internet of Things (IoT) sensing node, designed at the IoTLab (https://iotlab.unipr.it/) of the University of Parma, Italy, exploiting a Raspberry Pi 4 (as processing unit) and three low-cost commercial sensors (namely: Adafruit MiCS5524, Sensirion SCD30, Sensirion SPS30). Then, as a time reference, each record contains the Unix-like data collection timestamp and the identity of the IoT node sampling the air parameters (for safety purposes, the association with a generic color name in the CSV file name has been a consequence of an anonymization naming process for the IoT nodes, in order to hide their precise positions inside the airside transit area).Andrea Abrardo; Patrizia Agnello; Silvia M. Ansaldi; Laura Belli; Paolo Bragatto; Luca Davoli; Francesca M. Fabiani; Gianluigi Ferrari; Lorenzo Parri
CP-SEC: Sistema Cyber-Fisico per la sicurezza dei lavoratori in presenza di sostanze pericolose Technical Report
(22), 2023, ISBN: 9788874848072.
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Roberta Stefanini; Luca Preite; Eleonora Bottani; Laura Belli; Luca Davoli; Gianluigi Ferrari; Giuseppe Vignali
Selection of 4.0 sensors for small holders: the compromise between the advantages and the costs of the implementation Inproceedings
In: Proceedings of the 9th International Food Operations and Processing Simulation Workshop (FoodOPS 2023), pp. 1-7, Athens, Greece, 2023.
@inproceedings{stprbobedafevi:2023:foodops,
title = {Selection of 4.0 sensors for small holders: the compromise between the advantages and the costs of the implementation},
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abstract = {The agricultural sector involves various environmental impacts, related to soil exploitation, water consumption and greenhouse gasses emissions. The advent of 4.0 technologies could help reduce them, e.g., by using sensors that constantly control the field. However, these solutions are often implemented by big producers that can easily bear their costs. Thence, in the case of small holders, can the benefits achievable with 4.0 technologies justify their implementation costs? To answer this question, an Italian field with three rows of tomatoes has been investigated as a case study. A row with a traditional irrigation system has been compared to two rows with a 60% irrigation scenario monitored with 4.0 sensors. Overall, one environmental sensor, three crop analysis sensors, three flowmeters, three valves and one network infrastructure have been selected and introduced. The key findings of the work allow for quantifying the amount of water that small holders can save; the positive Net Present Value recommends the investment, with a Pay Back Period of 1.9 years. In the next steps, additional 4.0 sensors will be tested in the agricultural supply chain of some selected small holders in the Mediterranean area, to check whether the 4.0 implementation could not only reduce water consumption, but also improve storage conditions and reduce wastage.},
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The agricultural sector involves various environmental impacts, related to soil exploitation, water consumption and greenhouse gasses emissions. The advent of 4.0 technologies could help reduce them, e.g., by using sensors that constantly control the field. However, these solutions are often implemented by big producers that can easily bear their costs. Thence, in the case of small holders, can the benefits achievable with 4.0 technologies justify their implementation costs? To answer this question, an Italian field with three rows of tomatoes has been investigated as a case study. A row with a traditional irrigation system has been compared to two rows with a 60% irrigation scenario monitored with 4.0 sensors. Overall, one environmental sensor, three crop analysis sensors, three flowmeters, three valves and one network infrastructure have been selected and introduced. The key findings of the work allow for quantifying the amount of water that small holders can save; the positive Net Present Value recommends the investment, with a Pay Back Period of 1.9 years. In the next steps, additional 4.0 sensors will be tested in the agricultural supply chain of some selected small holders in the Mediterranean area, to check whether the 4.0 implementation could not only reduce water consumption, but also improve storage conditions and reduce wastage.Veronica Mattioli; Luca Davoli; Laura Belli; Gianluigi Ferrari; Riccardo Raheli
Thermal Camera-based Driver Monitoring in the Automotive Scenario Inproceedings
In: 2023 AEIT International Conference on Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE), pp. 1-6, Modena, Italy, 2023.
@inproceedings{madabefera:2023:aeit,
title = {Thermal Camera-based Driver Monitoring in the Automotive Scenario},
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abstract = {Driver monitoring in the automotive scenario is a key task in preventing hazardous events, such as road accidents. To this purpose, driver monitoring systems aim at providing prompt assistance in case of anomalies, such as alterations of the driver’s psycho-physiological status. The driving performance may, indeed, be negatively affected by high levels of stress and workload, that might be caused by different factors.In this paper, a novel in-vehicle monitoring system to extract the skin temperature of a driver, as one of the main indicators of his/her psycho-physiological status, is proposed. Thermal imaging techniques and video processing algorithms are jointly employed to record and extract temperature-related information in a non-invasive and contactless way. Temperature variations detected on the subject’s face are regulated by the activity of the Autonomic Nervous System (ANS) and represent, indeed, an important index of perceived stress levels. The feasibility of the proposed method is assessed both in simulated and real driving scenarios on the basis of experimental results.},
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Driver monitoring in the automotive scenario is a key task in preventing hazardous events, such as road accidents. To this purpose, driver monitoring systems aim at providing prompt assistance in case of anomalies, such as alterations of the driver’s psycho-physiological status. The driving performance may, indeed, be negatively affected by high levels of stress and workload, that might be caused by different factors.In this paper, a novel in-vehicle monitoring system to extract the skin temperature of a driver, as one of the main indicators of his/her psycho-physiological status, is proposed. Thermal imaging techniques and video processing algorithms are jointly employed to record and extract temperature-related information in a non-invasive and contactless way. Temperature variations detected on the subject’s face are regulated by the activity of the Autonomic Nervous System (ANS) and represent, indeed, an important index of perceived stress levels. The feasibility of the proposed method is assessed both in simulated and real driving scenarios on the basis of experimental results.Laura Belli; Luca Davoli; Gianluigi Ferrari
Smart City as an Urban Intelligent Digital System: The Case of Parma Journal Article
In: Computer, 56 (7), pp. 106-109, 2023, ISSN: 1558-0814.
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A smart city is an intelligent digital system that implements an effective smart urban environment able to integrate information from heterogeneous data sources and to provide efficient high-level services to citizens and municipal authorities.2022
Luca Davoli; Laura Belli; Francesco Denaro; Dinesh Tamang; Andrea Abrardo; Gianluigi Ferrari
On Safety Enhancement in IIoT Scenarios Through Heterogeneous Localization Techniques Journal Article
In: Chemical Engineering Transactions, 91 , pp. 259-264, 2022.
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Antonio Cilfone; Luca Davoli; Laura Belli; Gianluigi Ferrari
Seamless IoT Mobile Sensing through Wi-Fi Mesh Networking Book Chapter
In: Davoli, Luca; Ferrari, Gianluigi (Ed.): Wireless Mesh Networks for IoT and Smart Cities: Technologies and Applications, pp. 67-80, Institution of Engineering and Technology, 2022.
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2021
Luca Davoli; Veronica Mattioli; Sara Gambetta; Laura Belli; Luca Carnevali; Marco Martalò; Andrea Sgoifo; Riccardo Raheli; Gianluigi Ferrari
Non-Invasive Psycho-Physiological Driver Monitoring through IoT-Oriented Systems Book Chapter
In: Pani, Subhendu Kumar; Patra, Priyadarsan; Ferrari, Gianluigi; Kraleva, Radoslava; Wang, Xinheng (Ed.): The Internet of Medical Things: Enabling technologies and emerging applications, pp. 19-33, Institution of Engineering and Technology, London, UK, 2021, ISBN: 9781839532733.
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abstract = {The definition, analysis, and implementation of in-vehicle monitoring systems that collect data which are informative of the status of the joint driver-vehicle system, represent a topic of strong interest from both academic players and industrial manufacturers. Many external factors, such as road design, road layout, traffic flow and weather can influence and increase driving-related stress, potentially increasing risks. The ubiquitous diffusion of Internet of Things (IoT) technologies allows to collect heterogeneous data that can build the foundation for driver's psycho-physiological characterization, with the aim of improving safety and security while driving. This chapter evaluates and discusses the feasibility and usefulness of a non-invasive IoT-oriented driver monitoring infrastructure aiming at collecting physiological parameters (such as Heart Rate Variability, HRV) that may be adopted as biomarkers of the driver’s psycho-physiological state in different driving scenarios.},
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The definition, analysis, and implementation of in-vehicle monitoring systems that collect data which are informative of the status of the joint driver-vehicle system, represent a topic of strong interest from both academic players and industrial manufacturers. Many external factors, such as road design, road layout, traffic flow and weather can influence and increase driving-related stress, potentially increasing risks. The ubiquitous diffusion of Internet of Things (IoT) technologies allows to collect heterogeneous data that can build the foundation for driver's psycho-physiological characterization, with the aim of improving safety and security while driving. This chapter evaluates and discusses the feasibility and usefulness of a non-invasive IoT-oriented driver monitoring infrastructure aiming at collecting physiological parameters (such as Heart Rate Variability, HRV) that may be adopted as biomarkers of the driver’s psycho-physiological state in different driving scenarios.Laura Belli; Luca Carnevali; Luca Davoli; Gianluigi Ferrari; Sara Gambetta; Marco Martalò; Veronica Mattioli; Riccardo Raheli; Andrea Sgoifo
Internet of Things per monitorare lo stress dei conducenti: le soluzioni Online
Agenda Digitale 2021, visited: 29.11.2021.
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abstract = {Presso l’Università di Parma nell’ambito del progetto europeo NextPerception è in fase di sviluppo un sistema di monitoraggio interno ai veicoli volto ad aumentare il grado di sicurezza e di protezione degli occupanti grazie al paradigma dell’Internet of Things. Ecco di cosa si tratta.},
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Presso l’Università di Parma nell’ambito del progetto europeo NextPerception è in fase di sviluppo un sistema di monitoraggio interno ai veicoli volto ad aumentare il grado di sicurezza e di protezione degli occupanti grazie al paradigma dell’Internet of Things. Ecco di cosa si tratta.Laura Belli; Luca Davoli; Gianluigi Ferrari
Internet of Things e intelligenza artificiale, l’unione vincente che cambierà il mondo Online
Agenda Digitale 2021, visited: 29.10.2021.
@online{bedafe:2021:ad,
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L’utilizzo congiunto di strumenti Internet of Things e algoritmi di intelligenza artificiale (AIoT) permette di creare sinergia tra mondi che rappresentano il futuro dell’evoluzione tecnologica e abilitare scenari molto eterogenei. Ecco alcuni esempi di utilizzi in cui l’AIoT rappresenta un’integrazione interessante.Laura Belli; Luca Davoli; Gianluigi Ferrari; Emanuele Pagliari
Droni intelligenti e reti mesh: stato dell’arte e sfide tecnologiche Online
Agenda Digitale 2021, visited: 11.10.2021.
@online{bedafepa:2021:ad,
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abstract = {La disponibilità di protocolli di comunicazione eterogenei a bordo di sciami di droni rappresenta un elemento abilitante per scenari molto eterogenei. Una panoramica delle sfide tecnologiche che devono essere affrontate per garantire una comunicazione efficace tra i droni.},
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La disponibilità di protocolli di comunicazione eterogenei a bordo di sciami di droni rappresenta un elemento abilitante per scenari molto eterogenei. Una panoramica delle sfide tecnologiche che devono essere affrontate per garantire una comunicazione efficace tra i droni.2020
Luca Davoli; Marco Martalò; Antonio Cilfone; Laura Belli; Gianluigi Ferrari; Roberta Presta; Roberto Montanari; Maura Mengoni; Luca Giraldi; Elvio G. Amparore; Marco Botta; Idilio Drago; Giuseppe Carbonara; Andrea Castellano; Johan Plomp
On Driver Behavior Recognition for Increased Safety: A Roadmap Journal Article
In: Safety, 6 (4), pp. 1-33, 2020, ISSN: 2313-576X.
@article{Davoli_2020,
title = {On Driver Behavior Recognition for Increased Safety: A Roadmap},
author = {Luca Davoli and Marco Martalò and Antonio Cilfone and Laura Belli and Gianluigi Ferrari and Roberta Presta and Roberto Montanari and Maura Mengoni and Luca Giraldi and Elvio G. Amparore and Marco Botta and Idilio Drago and Giuseppe Carbonara and Andrea Castellano and Johan Plomp},
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abstract = {Advanced Driver-Assistance Systems (ADASs) are used for increasing safety in the automotive domain, yet current ADASs notably operate without taking into account drivers’ states, e.g., whether she/he is emotionally apt to drive. In this paper, we first review the state-of-the-art of emotional and cognitive analysis for ADAS: we consider psychological models, the sensors needed for capturing physiological signals, and the typical algorithms used for human emotion classification. Our investigation highlights a lack of advanced Driver Monitoring Systems (DMSs) for ADASs, which could increase driving quality and security for both drivers and passengers. We then provide our view on a novel perception architecture for driver monitoring, built around the concept of Driver Complex State (DCS). DCS relies on multiple non-obtrusive sensors and Artificial Intelligence (AI) for uncovering the driver state and uses it to implement innovative Human–Machine Interface (HMI) functionalities. This concept will be implemented and validated in the recently EU-funded NextPerception project, which is briefly introduced.},
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Advanced Driver-Assistance Systems (ADASs) are used for increasing safety in the automotive domain, yet current ADASs notably operate without taking into account drivers’ states, e.g., whether she/he is emotionally apt to drive. In this paper, we first review the state-of-the-art of emotional and cognitive analysis for ADAS: we consider psychological models, the sensors needed for capturing physiological signals, and the typical algorithms used for human emotion classification. Our investigation highlights a lack of advanced Driver Monitoring Systems (DMSs) for ADASs, which could increase driving quality and security for both drivers and passengers. We then provide our view on a novel perception architecture for driver monitoring, built around the concept of Driver Complex State (DCS). DCS relies on multiple non-obtrusive sensors and Artificial Intelligence (AI) for uncovering the driver state and uses it to implement innovative Human–Machine Interface (HMI) functionalities. This concept will be implemented and validated in the recently EU-funded NextPerception project, which is briefly introduced.Laura Belli; Antonio Cilfone; Luca Davoli; Gianluigi Ferrari; Paolo Adorni; Francesco Di Nocera; Alessandro Dall'Olio; Cristina Pellegrini; Marco Mordacci; Enzo Bertolotti
IoT-Enabled Smart Sustainable Cities: Challenges and Approaches Journal Article
In: Smart Cities, 3 , pp. 1039-1071, 2020.
@article{Belli2020,
title = {IoT-Enabled Smart Sustainable Cities: Challenges and Approaches},
author = {Laura Belli and Antonio Cilfone and Luca Davoli and Gianluigi Ferrari and Paolo Adorni and Francesco Di Nocera and Alessandro Dall'Olio and Cristina Pellegrini and Marco Mordacci and Enzo Bertolotti},
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abstract = {The ongoing diffusion of Internet of Things (IoT) technologies is opening new possibilities, and one of the most remarkable applications is associated with the smart city paradigm, which is continuously evolving. In general, it can be defined as the integration of IoT and Information Communication Technologies (ICT) into city management, with the aim of addressing the exponential growth of urbanization and population, thus significantly increasing people’s quality of life. The smart city paradigm is also strictly connected to sustainability aspects, taking into account, for example, the reduction of environmental impact of urban activities, the optimized management of energy resources, and the design of innovative services and solution for citizens. Abiding by this new paradigm, several cities started a process of strong innovation in different fields (such as mobility and transportation, industry, health, tourism, and education), thanks to significant investments provided by stakeholders and the European Commission (EC). In this paper, we analyze key aspects of an IoT infrastructure for smart cities, outlining the innovations implemented in the city of Parma (Emilia Romagna region, Italy) as a successful example. Special attention is dedicated to the theme of smart urban mobility.},
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The ongoing diffusion of Internet of Things (IoT) technologies is opening new possibilities, and one of the most remarkable applications is associated with the smart city paradigm, which is continuously evolving. In general, it can be defined as the integration of IoT and Information Communication Technologies (ICT) into city management, with the aim of addressing the exponential growth of urbanization and population, thus significantly increasing people’s quality of life. The smart city paradigm is also strictly connected to sustainability aspects, taking into account, for example, the reduction of environmental impact of urban activities, the optimized management of energy resources, and the design of innovative services and solution for citizens. Abiding by this new paradigm, several cities started a process of strong innovation in different fields (such as mobility and transportation, industry, health, tourism, and education), thanks to significant investments provided by stakeholders and the European Commission (EC). In this paper, we analyze key aspects of an IoT infrastructure for smart cities, outlining the innovations implemented in the city of Parma (Emilia Romagna region, Italy) as a successful example. Special attention is dedicated to the theme of smart urban mobility.Luca Davoli; Laura Belli; Gianluigi Ferrari
IoT-enabled Smart Monitoring and Optimization for Industry 4.0 Book Chapter
In: Atzori, Luigi; Ferrari, Gianluigi (Ed.): Internet of Things: Techonologies, Challenges and Impact, 5 , Chapter 11, pp. 207–226, TeXMAT, Roma, Italy, 2020, ISBN: 978-88-949-8239-8.
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abstract = {In the last decades, forward-looking companies have introduced Internet of Things (IoT) concepts in several industrial application scenarios, leading to the so-called Industrial IoT (IIoT) and, restricting to the manufacturing scenario, to Industry 4.0. Their ambition is to enhance, through proper field data collection and analysis, the productivity of their facilities and the creation of real-time digital twins of different industrial scenarios, aiming to significantly improve industrial management and business processes. Moreover, since modern companies should be as ``smart'' as possible and should adapt themselves to the varying nature of the digital supply chains, they need different mechanisms in order to (i) enhance the control of the production plant and (ii) comply with high-layer data analysis and fusion tools that can foster the most appropriate evolution of the company itself (thus lowering the risk of machine failures) by adopting a predictive approach. Focusing on the overall company management, in this chapter we present an example of a ``renovation'' process, based on: (i) digitization of the control quality process on multiple production lines, aiming at digitally collecting and processing information already available in the company environment; (ii) monitoring and optimization of the production planning activity through innovative approaches, aiming at extending the quantity of collected data and providing a new perspective of the overall current status of a factory; and (iii) a predictive maintenance approach, based on a set of heterogeneous analytical mechanisms to be applied to on-field data collected in different production lines, together with the integration of sensor-based data, toward a paradigm that can be denoted as Maintenance-as-a-Service (MaaS). In particular, these data are related to the operational status of production machines and the currently available warehouse supplies. Our overall goal is to show that IoT-based Industry 4.0 strategies allow to continuously collect heterogeneous Human-to-Things (H2T) and Machine-to-Machine (M2M) data, which can be used to optimize and improve a factory as a whole entity.},
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In the last decades, forward-looking companies have introduced Internet of Things (IoT) concepts in several industrial application scenarios, leading to the so-called Industrial IoT (IIoT) and, restricting to the manufacturing scenario, to Industry 4.0. Their ambition is to enhance, through proper field data collection and analysis, the productivity of their facilities and the creation of real-time digital twins of different industrial scenarios, aiming to significantly improve industrial management and business processes. Moreover, since modern companies should be as ``smart'' as possible and should adapt themselves to the varying nature of the digital supply chains, they need different mechanisms in order to (i) enhance the control of the production plant and (ii) comply with high-layer data analysis and fusion tools that can foster the most appropriate evolution of the company itself (thus lowering the risk of machine failures) by adopting a predictive approach. Focusing on the overall company management, in this chapter we present an example of a ``renovation'' process, based on: (i) digitization of the control quality process on multiple production lines, aiming at digitally collecting and processing information already available in the company environment; (ii) monitoring and optimization of the production planning activity through innovative approaches, aiming at extending the quantity of collected data and providing a new perspective of the overall current status of a factory; and (iii) a predictive maintenance approach, based on a set of heterogeneous analytical mechanisms to be applied to on-field data collected in different production lines, together with the integration of sensor-based data, toward a paradigm that can be denoted as Maintenance-as-a-Service (MaaS). In particular, these data are related to the operational status of production machines and the currently available warehouse supplies. Our overall goal is to show that IoT-based Industry 4.0 strategies allow to continuously collect heterogeneous Human-to-Things (H2T) and Machine-to-Machine (M2M) data, which can be used to optimize and improve a factory as a whole entity.Laura Belli; Antonio Cilfone; Luca Davoli; Gianluigi Ferrari; Paolo Adorni; Francesco Di Nocera; Alessandro Dall'Olio; Cristina Pellegrini; Marco Mordacci; Enzo Bertolotti
Smart City Parma, un bilancio: servizi, prospettive e innovazioni future Online
Agenda Digitale 2020, visited: 03.09.2020.
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abstract = {Secondo gli indicatori del programma di "smart benchmarking" di FPA, la città di Parma si è posizionata al nono posto a livello nazionale nella classifica generale di iCity Rate 2017. Con il chiaro intento di migliorarsi ed offrire alla propria comunità servizi migliori, la città di Parma ha iniziato un percorso virtuoso per diventare sempre più "smart". Nell'articolo "Smart City Parma, metabolismo e sostenibilità: il viaggio verso il 2030" pubblicato nel Febbraio 2018, era stato discusso l’approccio intrapreso dalla municipalità ducale per diventare "smart". Nel presente articolo verrà tracciato un bilancio sulle attività condotte negli ultimi due anni dall’Amministrazione Comunale di Parma, anche in collaborazione con diverse realtà accademiche ed aziendali del territorio, evidenziando prospettive ed innovazioni possibili.},
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Secondo gli indicatori del programma di "smart benchmarking" di FPA, la città di Parma si è posizionata al nono posto a livello nazionale nella classifica generale di iCity Rate 2017. Con il chiaro intento di migliorarsi ed offrire alla propria comunità servizi migliori, la città di Parma ha iniziato un percorso virtuoso per diventare sempre più "smart". Nell'articolo "Smart City Parma, metabolismo e sostenibilità: il viaggio verso il 2030" pubblicato nel Febbraio 2018, era stato discusso l’approccio intrapreso dalla municipalità ducale per diventare "smart". Nel presente articolo verrà tracciato un bilancio sulle attività condotte negli ultimi due anni dall’Amministrazione Comunale di Parma, anche in collaborazione con diverse realtà accademiche ed aziendali del territorio, evidenziando prospettive ed innovazioni possibili.Laura Belli; Simone Cirani; Luca Davoli; Gianluigi Ferrari; Lorenzo Melegari; Marco Picone
Applying Security to a Big Stream Cloud Architecture for the Internet of Things Book Chapter
In: Securing the Internet of Things: Concepts, Methodologies, Tools, and Applications, pp. 1260–1284, IGI Global, Hershey, PA, USA, 2020, ISBN: 9781522598664.
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The Internet of Things (IoT) is expected to interconnect billions (around 50 by 2020) of heterogeneous sensor/actuator-equipped devices denoted as “Smart Objects” (SOs), characterized by constrained resources in terms of memory, processing, and communication reliability. Several IoT applications have real-time and low-latency requirements and must rely on architectures specifically designed to manage gigantic streams of information (in terms of number of data sources and transmission data rate). We refer to “Big Stream” as the paradigm which best fits the selected IoT scenario, in contrast to the traditional “Big Data” concept, which does not consider real-time constraints. Moreover, there are many security concerns related to IoT devices and to the Cloud. In this paper, we analyze security aspects in a novel Cloud architecture for Big Stream applications, which efficiently handles Big Stream data through a Graph-based platform and delivers processed data to consumers, with low latency. The authors detail each module defined in the system architecture, describing all refinements required to make the platform able to secure large data streams. An experimentation is also conducted in order to evaluate the performance of the proposed architecture when integrating security mechanisms.2019
Pier Luigi Marchini; Alice Medioli; Laura Belli; Luca Davoli
Internet of Things e Industria 4.0. Un case study di successo di digital manufacturing Journal Article
In: Management Control, (3), pp. 11-34, 2019, ISSN: 2239-4397.
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The value creation through production is currently shaped by Industry 4.0, whose paradigm aims at improving industry management and business processes. Through a case study, this research describes the renovation steps, in a manufac-turing environment. The research aims to study how the introduction of digital in-novation helps in making more efficient and time saving production (RQ1), as well as in increasing product quality, enabling on time detection of non-conformity (RQ2). At theoretical level, the research aims to close the gap between the Internet of Things (IoT) application and real-word aspects, analyzing how an industry 4.0 transformation could be modelled and implemented. At managerial level, the study shows how IoT technologies and process digitalization should provide ad-vantages in terms of cost reduction, product quality control, allowing continuous collection of heterogeneous data useful to optimize the production further.Laura Belli; Luca Davoli; Alice Medioli; Pier Luigi Marchini; Gianluigi Ferrari
Toward Industry 4.0 With IoT: Optimizing Business Processes in an Evolving Manufacturing Factory Journal Article
In: Frontiers in ICT, 6 , pp. 17, 2019, ISSN: 2297-198X.
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abstract = {Research advances in the last decades have allowed the introduction of Internet of Things (IoT) concepts in several industrial application scenarios, leading to the so-called Industry 4.0 or Industrial IoT (IIoT). The Industry 4.0 has the ambition to revolutionize industry management and business processes, enhancing the productivity of manufacturing technologies through field data collection and analysis, thus creating real-time digital twins of industrial scenarios. Moreover, it is vital for companies to be as "smart" as possible and to adapt to the varying nature of the digital supply chains. This is possible by leveraging IoT in Industry 4.0 scenarios. In this paper, we describe the renovation process, guided by things2i s.r.l., a cross-disciplinary engineering-economic spin-off company of the University of Parma, which a real manufacturing industry is undergoing over consecutive phases spanning a few years. The first phase concerns the digitalization of the control quality process, specifically related to the company's production lines. The use of paper sheets containing different quality checks has been made smarter through the introduction of a digital, smart, and Web-based application, which is currently supporting operators and quality inspectors working on the supply chain through the use of smart devices. The second phase of the IIoT evolution - currently on-going - concerns both digitalization and optimization of the production planning activity, through an innovative Web-based planning tool. The changes introduced have led to significant advantages and improvement for the manufacturing company, in terms of: (i) impressive cost reduction; (ii) better products quality control; (iii) real-time detection and reaction to supply chain issues; (iv) significant reduction of the time spent in planning activity; and (v) resources employment optimization, thanks to the minimization of unproductive setup times on production lines. These two renovation phases represent a basis for possible future developments, such us the integration of sensor-based data on the operational status of production machines and the currently available warehouse supplies. In conclusion, the Industry 4.0-based on-going digitization process guided by things2i allows to continuously collect heterogeneous Human-to-Things (H2T) data, which can be used to optimize the partner manufacturing company as a whole entity.},
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Research advances in the last decades have allowed the introduction of Internet of Things (IoT) concepts in several industrial application scenarios, leading to the so-called Industry 4.0 or Industrial IoT (IIoT). The Industry 4.0 has the ambition to revolutionize industry management and business processes, enhancing the productivity of manufacturing technologies through field data collection and analysis, thus creating real-time digital twins of industrial scenarios. Moreover, it is vital for companies to be as "smart" as possible and to adapt to the varying nature of the digital supply chains. This is possible by leveraging IoT in Industry 4.0 scenarios. In this paper, we describe the renovation process, guided by things2i s.r.l., a cross-disciplinary engineering-economic spin-off company of the University of Parma, which a real manufacturing industry is undergoing over consecutive phases spanning a few years. The first phase concerns the digitalization of the control quality process, specifically related to the company's production lines. The use of paper sheets containing different quality checks has been made smarter through the introduction of a digital, smart, and Web-based application, which is currently supporting operators and quality inspectors working on the supply chain through the use of smart devices. The second phase of the IIoT evolution - currently on-going - concerns both digitalization and optimization of the production planning activity, through an innovative Web-based planning tool. The changes introduced have led to significant advantages and improvement for the manufacturing company, in terms of: (i) impressive cost reduction; (ii) better products quality control; (iii) real-time detection and reaction to supply chain issues; (iv) significant reduction of the time spent in planning activity; and (v) resources employment optimization, thanks to the minimization of unproductive setup times on production lines. These two renovation phases represent a basis for possible future developments, such us the integration of sensor-based data on the operational status of production machines and the currently available warehouse supplies. In conclusion, the Industry 4.0-based on-going digitization process guided by things2i allows to continuously collect heterogeneous Human-to-Things (H2T) data, which can be used to optimize the partner manufacturing company as a whole entity.Luca Davoli; Laura Belli; Gianluigi Ferrari
Enhancing Security in a Big Stream Cloud Architecture for the Internet of Things Through Blockchain Book Chapter
In: Kecskemeti, Gabor (Ed.): Applying Integration Techniques and Methods in Distributed Systems and Technologies, pp. 104-133, IGI Global, Hershey, PA, 2019, ISBN: 978-152-25-8295-3.
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abstract = {The Internet of Things (IoT) paradigm is foreseeing the development of our environment towards new enriched spaces in most areas of modern living, such as digital health, smart cities, and smart agriculture. Several IoT applications also have real-time and low-latency requirements and must rely on specific architectures. The authors refer to the paradigm that best fits the selected IoT scenario as “Big Stream” because it considers real-time constraints. Moreover, the blockchain concept has drawn attention as the next-generation technology through the authentication of peers that share encryption and the generation of hash values. In addition, the blockchain can be applied in conjunction with Cloud Computing and the IoT paradigms, since it avoids the involvement of third parties in a broker-free way. In this chapter, an analysis on mechanisms that can be adopted to secure Big Stream data in a graph-based platform, thus delivering them to consumers in an efficient and secure way, and with low latency, is shown, describing all refinements required employing federation-based and blockchain paradigms.},
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The Internet of Things (IoT) paradigm is foreseeing the development of our environment towards new enriched spaces in most areas of modern living, such as digital health, smart cities, and smart agriculture. Several IoT applications also have real-time and low-latency requirements and must rely on specific architectures. The authors refer to the paradigm that best fits the selected IoT scenario as “Big Stream” because it considers real-time constraints. Moreover, the blockchain concept has drawn attention as the next-generation technology through the authentication of peers that share encryption and the generation of hash values. In addition, the blockchain can be applied in conjunction with Cloud Computing and the IoT paradigms, since it avoids the involvement of third parties in a broker-free way. In this chapter, an analysis on mechanisms that can be adopted to secure Big Stream data in a graph-based platform, thus delivering them to consumers in an efficient and secure way, and with low latency, is shown, describing all refinements required employing federation-based and blockchain paradigms.Antonio Cilfone; Luca Davoli; Laura Belli; Gianluigi Ferrari
Wireless Mesh Networking: An IoT-Oriented Perspective Survey on Relevant Technologies Journal Article
In: Future Internet, 11 (4), 2019, ISSN: 1999-5903.
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abstract = {The Internet of Things (IoT), being a "network of networks", promises to allow billions of humans and machines to interact with each other. Owing to this rapid growth, the deployment of IoT-oriented networks based on mesh topologies is very attractive, thanks to their scalability and reliability (in the presence of failures). In this paper, we provide a comprehensive survey of the following relevant wireless technologies: IEEE 802.11, Bluetooth, IEEE 802.15.4-oriented, and Sub-GHz-based LoRa. Our goal is to highlight how various communication technologies may be suitable for mesh networking, either providing a native support or being adapted subsequently. Hence, we discuss how these wireless technologies, being either standard or proprietary, can adapt to IoT scenarios (e.g., smart cities and smart agriculture) in which the heterogeneity of the involved devices is a key feature. Finally, we provide reference use cases involving all the analyzed mesh-oriented technologies.},
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The Internet of Things (IoT), being a "network of networks", promises to allow billions of humans and machines to interact with each other. Owing to this rapid growth, the deployment of IoT-oriented networks based on mesh topologies is very attractive, thanks to their scalability and reliability (in the presence of failures). In this paper, we provide a comprehensive survey of the following relevant wireless technologies: IEEE 802.11, Bluetooth, IEEE 802.15.4-oriented, and Sub-GHz-based LoRa. Our goal is to highlight how various communication technologies may be suitable for mesh networking, either providing a native support or being adapted subsequently. Hence, we discuss how these wireless technologies, being either standard or proprietary, can adapt to IoT scenarios (e.g., smart cities and smart agriculture) in which the heterogeneity of the involved devices is a key feature. Finally, we provide reference use cases involving all the analyzed mesh-oriented technologies.Luca Davoli; Antonio Cilfone; Laura Belli; Gianluigi Ferrari
Design and experimental performance analysis of a B.A.T.M.A.N.-based double Wi-Fi interface mesh network Journal Article
In: Future Generation Computer Systems, 92 , pp. 593-603, 2019, ISSN: 0167-739X.
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abstract = {Mesh networks and, in particular, Wireless Mesh Networks (WMNs) are gaining a growing interest because of their scalability, robustness, and ease of deployment. These characteristics make WMNs suitable for several applications, such as distributed sensing, monitoring, and public safety. In this paper, we describe a novel WMN implementation based on the use of low-cost double Wi-Fi interface embedded IoT-oriented devices. At each node, one interface provides external connectivity, whereas the other interface is used to create a mesh backbone. On the mesh side, the Better Approach To Mobile Ad-hoc Networking (B.A.T.M.A.N.) routing algorithm is used to route the traffic flows from external clients (possibly towards an Internet gateway), which can be IoT nodes and/or mobile nodes (e.g., smartphones and tablets). After providing a description of the architecture and relevant implementation details, we carry out an extensive experimental campaign to evaluate the WMN performance, especially in terms of the trade-off between throughput and number of hops.},
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Mesh networks and, in particular, Wireless Mesh Networks (WMNs) are gaining a growing interest because of their scalability, robustness, and ease of deployment. These characteristics make WMNs suitable for several applications, such as distributed sensing, monitoring, and public safety. In this paper, we describe a novel WMN implementation based on the use of low-cost double Wi-Fi interface embedded IoT-oriented devices. At each node, one interface provides external connectivity, whereas the other interface is used to create a mesh backbone. On the mesh side, the Better Approach To Mobile Ad-hoc Networking (B.A.T.M.A.N.) routing algorithm is used to route the traffic flows from external clients (possibly towards an Internet gateway), which can be IoT nodes and/or mobile nodes (e.g., smartphones and tablets). After providing a description of the architecture and relevant implementation details, we carry out an extensive experimental campaign to evaluate the WMN performance, especially in terms of the trade-off between throughput and number of hops.2018
Laura Belli; Simone Cirani; Luca Davoli; Gianluigi Ferrari; Lorenzo Melegari; Màrius Montón; Marco Picone
A Scalable Big Stream Cloud Architecture for the Internet of Things Incollection
In: Fog Computing: Breakthroughs in Research and Practice, pp. 25-53, IGI Global, Hershey, PA, USA, 2018, ISBN: 9781522556497.
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The Internet of Things (IoT) will consist of billions (50 billions by 2020) of interconnected heterogeneous devices denoted as "Smart Objects:" tiny, constrained devices which are going to be pervasively deployed in several contexts. To meet low-latency requirements, IoT applications must rely on specific architectures designed to handle the gigantic stream of data coming from Smart Objects. This paper propose a novel Cloud architecture for Big Stream applications that can efficiently handle data coming from Smart Objects through a Graph-based processing platform and deliver processed data to consumer applications with low latency. The authors reverse the traditional "Big Data" paradigm, where real-time constraints are not considered, and introduce the new "Big Stream" paradigm, which better fits IoT scenarios. The paper provides a performance evaluation of a practical open-source implementation of the proposed architecture. Other practical aspects, such as security considerations, and possible business oriented exploitation plans are presented.Luca Davoli; Laura Belli; Antonio Cilfone; Gianluigi Ferrari
From Micro to Macro IoT: Challenges and Solutions in the Integration of IEEE 802.15.4/802.11 and Sub-GHz Technologies Journal Article
In: IEEE Internet of Things Journal, 5 (2), pp. 784-793, 2018, ISSN: 2327-4662.
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Research efforts in the field of Internet of Things (IoT) are providing solutions in building new types of “network of networks,” going beyond the technological barriers due to intrinsic limitations of the constrained devices typically used in this context. Thanks to the improvement in communication/networking protocols and the hardware cost reduction, it is now possible to define new IoT architectures, combining the “micro” IoT paradigm, based on short-range radio technologies (e.g., IEEE 802.15.4 and IEEE 802.11), with the rising “macro” IoT paradigm, based on sub-GHz radio technologies. This allows the implementation of scalable network architectures, able to collect data coming from constrained devices and process them in order to provide useful services and applications to final consumers. In this paper, we focus on practical integration between micro and macro IoT approaches, providing architectural and performance details for a set of experimental tests carried out in the campus of the University of Parma. We then discuss challenges and solutions of the proposed micro–macro integrated IoT systems.Luca Davoli; Laura Belli; Luca Veltri; Gianluigi Ferrari
THORIN: an Efficient Module for Federated Access and Threat Mitigation in Big Stream Cloud Architectures Journal Article
In: IEEE Cloud Computing, 5 (1), pp. 38-48, 2018, ISSN: 2325-6095.
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In order to make cloud services attractive for several IT organizations, it is necessary to provide access control and to implement safe and reliable mechanisms of Identity and Access Management (IAM). In this work, we focus on security issues and challenges in the design and implementation of cloud architectures and, in particular, for the management of Big Stream applications in Internet of Things (IoT) scenarios. The proposed work introduces a new set of modules allowing a federated access control policy for cloud users. An analysis of possible threats and attacks against the proposed Big Stream platform is presented, investigating the system performance in terms of detection and elimination of malicious nodes. In particular, we propose a new module, denoted as Traffic Handler Orchestrator & Rapid Intervention (THORIN), which is very efficient in counteracting botnet-based threats.2016
Luca Davoli; Laura Belli; Antonio Cilfone; Gianluigi Ferrari
Integration of Wi-Fi mobile nodes in a Web of Things Testbed Journal Article
In: ICT Express, 2 (3), pp. 96 - 99, 2016, ISSN: 2405-9595, (Special Issue on ICT Convergence in the Internet of Things (IoT)).
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The Internet of Things (IoT) is supposed to connect billions of devices to the Internet through IP-based communications. The main goal is to foster a rapid deployment of Web-enabled everyday objects, allowing end users to manage and control smart things in a simple way, by using Web browsers. This paper focuses on the integration of Wi-Fi nodes, hosting HTTP resources, into a Web of Things Testbed (WoTT). The main novelty of the proposed approach is that the WoTT integrates new nodes by using only standard mechanisms, allowing end-users to interact with all Smart Objects without worrying about protocol-specific details.Laura Belli; Simone Cirani; Luca Davoli; Gianluigi Ferrari; Lorenzo Melegari; Marco Picone
Applying Security to a Big Stream Cloud Architecture for the Internet of Things Journal Article
In: International Journal of Distributed Systems and Technologies (IJDST), 7 (1), pp. 37-58, 2016, ISSN: 1947-3532.
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The Internet of Things (IoT) is expected to interconnect billions (around 50 by 2020) of heterogeneous sensor/actuator-equipped devices denoted as Smart Objects (SOs), characterized by constrained resources in terms of memory, processing, and communication reliability. Several IoT applications have real-time and low-latency requirements and must rely on architectures specifically designed to manage gigantic streams of information (in terms of number of data sources and transmission data rate). We refer to Big Stream as the paradigm which best fits the selected IoT scenario, in contrast to the traditional Big Data concept, which does not consider real-time constraints. Moreover, there are many security concerns related to IoT devices and to the Cloud. In this paper, we analyze security aspects in a novel Cloud architecture for Big Stream applications, which efficiently handles Big Stream data through a Graph-based platform and delivers processed data to consumers, with low latency. The authors detail each module defined in the system architecture, describing all refinements required to make the platform able to secure large data streams. An experimentation is also conducted in order to evaluate the performance of the proposed architecture when integrating security mechanisms.Michele Amoretti; Laura Belli; Francesco Zanichelli
UTravel: Smart mobility with a novel user profiling and recommendation approach Journal Article
In: Pervasive and Mobile Computing, 38 (2), pp. 474-489, 2016.
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The exponentially growing availability of online information calls for personalized search and recommendation. Such systems provide recommendations typically based on user profiles built taking into account user actions. Not yet fully explored, is the domain of context-aware recommendation. In this article, we introduce a novel approach, where user profiling and context-based data filtering both concur to recommendation production. Based on the aforementioned approach, UTravel is a smart mobility application that recommends points of interest (POIs) to end users. After describing the UTravel architecture and implementation, we present the results of an experimental evaluation we carried out involving both simulated and real users.2015
Laura Belli; Simone Cirani; Luca Davoli; Andrea Gorrieri; Mirko Mancin; Marco Picone; Gianluigi Ferrari
Design and Deployment of an IoT Application-Oriented Testbed Journal Article
In: Computer, 48 (9), pp. 32-40, 2015, ISSN: 0018-9162.
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The global reach and extreme heterogeneity of the Internet of Things present major application development challenges. Using the same Web-based approach underlying the Internet's evolution into the IoT, the Web of Things Testbed provides a stable, open, dynamic, and secure infrastructure to simplify application design and testing.Laura Belli; Simone Cirani; Luca Davoli; Gianluigi Ferrari; Lorenzo Melegari; Màrius Montón; Marco Picone
A Scalable Big Stream Cloud Architecture for the Internet of Things Journal Article
In: International Journal of Systems and Service-Oriented Engineering (IJSSOE), 5 (4), pp. 26-53, 2015, ISSN: 1947-3052.
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The Internet of Things (IoT) will consist of billions (50 billions by 2020) of interconnected heterogeneous devices denoted as “Smart Objects:” tiny, constrained devices which are going to be pervasively deployed in several contexts. To meet low-latency requirements, IoT applications must rely on specific architectures designed to handle the gigantic stream of data coming from Smart Objects. This paper propose a novel Cloud architecture for Big Stream applications that can efficiently handle data coming from Smart Objects through a Graph-based processing platform and deliver processed data to consumer applications with low latency. The authors reverse the traditional “Big Data” paradigm, where real-time constraints are not considered, and introduce the new “Big Stream” paradigm, which better fits IoT scenarios. The paper provides a performance evaluation of a practical open-source implementation of the proposed architecture. Other practical aspects, such as security considerations, and possible business oriented exploitation plans are presented.Laura Belli; Simone Cirani; Luca Davoli; Lorenzo Melegari; Màrius Montón; Marco Picone
An Open-Source Cloud Architecture for Big Stream IoT Applications Incollection
In: Žarko, Ivana Podnar; Pripužić, Krešimir; Serrano, Martin (Ed.): Interoperability and Open-Source Solutions for the Internet of Things (International Workshop, FP7 OpenIoT Project, Held in Conjunction with SoftCOM 2014, Split, Croatia, September 18, 2014, Invited , 9001 , pp. 73-88, Springer International Publishing, 2015, ISBN: 978-3-319-16545-5.
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Laura Belli; Simone Cirani; Gianluigi Ferrari; Lorenzo Melegari; Marco Picone
A Graph-based cloud architecture for big stream real-time applications in the Internet of Things Inproceedings
In: 2nd International Workshop on CLoud for IoT (CLIoT 2014), Manchester, United Kingdom, September 2014, 2014.
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Laura Belli
-
Laura Belli
Fixed-term Assistant Professor
email:laura.belli[at]unipr.it
mailing address:
Department of Engineering and Architecture
Parco Area delle Scienze, 181/A
I-43124 ParmaLaura Belli was born in Fiorenzuola d’Arda, on April 14th, 1984 and currently is a Fixed-term Assistant Professor at the University of Parma.
She received the Dr. Ing. degree (Master) in Computer Engineering from the University of Parma in 2011.
In 2015, he received his Ph.D. at the Department of Information Engineering of the same university with a thesis entitled “Efficient Data Management with Applications to IoT”.
Since January 2013, he is a member of the Internet of Things Lab (IoTLab) (ex Wireless Ad-Hoc and Sensor Networks Laboratory – WASNLab) at the Department of Engineering and Architecture of the University of Parma. -
- Internet of Things
- Smart Systems
- Database integration
- Mobile computing
- Cloud computing
2024
An IoT-based data analysis system: A case study on tomato cultivation under different irrigation regimes Journal Article
In: Computers and Electronics in Agriculture, 229 , pp. 109660, 2024, ISSN: 0168-1699.
City2i, innovazione IoT per smart city: l’esempio Parma Miscellaneous
2024.
Optimizing Tomato Production through IoT-based Smart Data Collection and Analysis Inproceedings
In: 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE), pp. 45-50, Bari, Italy, 2024.
CoAP-based Digital Twin Modelling of Heterogeneous IoT Scenarios Inproceedings
In: 10th International Food Operations and Processing Simulation Workshop (FoodOPS 2024), pp. 1-5, Tenerife, Spain, 2024.
IoT-Based Assessment of a Driver’s Stress Level Journal Article
In: Sensors, 24 (17), 2024, ISSN: 1424-8220.
IoT in agricoltura: vantaggi e casi d’uso reali Miscellaneous
2024.
Hyperledger Fabric in Precision Agriculture: A Study on Data Integrity and Availability Inproceedings
In: 2024 International Conference on Computer, Information and Telecommunication Systems (CITS), pp. 1-8, Girona, Spain, 2024.
Poster: Evaluation of Hop Cone Maturation through Internet of Things (IoT) and Smart Farming Technologies. A Preliminary Study Inproceedings
In: 39th EBC Congress, pp. 1-1, Lille, France, 2024.
A Cloud-Oriented Indoor-Outdoor Real-Time Localization IoT Architecture for Industrial Environments Inproceedings
In: 2024 IEEE 21st Consumer Communications & Networking Conference (CCNC), pp. 1-6, Las Vegas, NV, USA, 2024, ISSN: 2331-9860.
An Edge Computing-Oriented WoT Architecture for Air Quality Monitoring in Mobile Vehicular Scenarios Inproceedings
In: 2024 IEEE 21st Consumer Communications & Networking Conference (CCNC), pp. 1-7, Las Vegas, NV, USA, 2024, ISSN: 2331-9860.
Data Integration in a Smart City: A Real Case Book Chapter
In: Information and Communications Technologies for Smart Cities and Societies, 5 , Chapter 2, pp. 11-24, Springer Nature Switzerland, 2024.
2023
Air quality dataset from an indoor airport travelers transit area Journal Article
In: Data in Brief, 52 , pp. 109821, 2023, ISSN: 2352-3409.
Indoor Air Quality Monitoring @ Brindisi Airport Miscellaneous
2023.
CP-SEC: Sistema Cyber-Fisico per la sicurezza dei lavoratori in presenza di sostanze pericolose Technical Report
(22), 2023, ISBN: 9788874848072.
Selection of 4.0 sensors for small holders: the compromise between the advantages and the costs of the implementation Inproceedings
In: Proceedings of the 9th International Food Operations and Processing Simulation Workshop (FoodOPS 2023), pp. 1-7, Athens, Greece, 2023.
Thermal Camera-based Driver Monitoring in the Automotive Scenario Inproceedings
In: 2023 AEIT International Conference on Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE), pp. 1-6, Modena, Italy, 2023.
Smart City as an Urban Intelligent Digital System: The Case of Parma Journal Article
In: Computer, 56 (7), pp. 106-109, 2023, ISSN: 1558-0814.
2022
On Safety Enhancement in IIoT Scenarios Through Heterogeneous Localization Techniques Journal Article
In: Chemical Engineering Transactions, 91 , pp. 259-264, 2022.
Seamless IoT Mobile Sensing through Wi-Fi Mesh Networking Book Chapter
In: Davoli, Luca; Ferrari, Gianluigi (Ed.): Wireless Mesh Networks for IoT and Smart Cities: Technologies and Applications, pp. 67-80, Institution of Engineering and Technology, 2022.
2021
Non-Invasive Psycho-Physiological Driver Monitoring through IoT-Oriented Systems Book Chapter
In: Pani, Subhendu Kumar; Patra, Priyadarsan; Ferrari, Gianluigi; Kraleva, Radoslava; Wang, Xinheng (Ed.): The Internet of Medical Things: Enabling technologies and emerging applications, pp. 19-33, Institution of Engineering and Technology, London, UK, 2021, ISBN: 9781839532733.
Internet of Things per monitorare lo stress dei conducenti: le soluzioni Online
Agenda Digitale 2021, visited: 29.11.2021.
Internet of Things e intelligenza artificiale, l’unione vincente che cambierà il mondo Online
Agenda Digitale 2021, visited: 29.10.2021.
Droni intelligenti e reti mesh: stato dell’arte e sfide tecnologiche Online
Agenda Digitale 2021, visited: 11.10.2021.
2020
On Driver Behavior Recognition for Increased Safety: A Roadmap Journal Article
In: Safety, 6 (4), pp. 1-33, 2020, ISSN: 2313-576X.
IoT-Enabled Smart Sustainable Cities: Challenges and Approaches Journal Article
In: Smart Cities, 3 , pp. 1039-1071, 2020.
IoT-enabled Smart Monitoring and Optimization for Industry 4.0 Book Chapter
In: Atzori, Luigi; Ferrari, Gianluigi (Ed.): Internet of Things: Techonologies, Challenges and Impact, 5 , Chapter 11, pp. 207–226, TeXMAT, Roma, Italy, 2020, ISBN: 978-88-949-8239-8.
Smart City Parma, un bilancio: servizi, prospettive e innovazioni future Online
Agenda Digitale 2020, visited: 03.09.2020.
Applying Security to a Big Stream Cloud Architecture for the Internet of Things Book Chapter
In: Securing the Internet of Things: Concepts, Methodologies, Tools, and Applications, pp. 1260–1284, IGI Global, Hershey, PA, USA, 2020, ISBN: 9781522598664.
2019
Internet of Things e Industria 4.0. Un case study di successo di digital manufacturing Journal Article
In: Management Control, (3), pp. 11-34, 2019, ISSN: 2239-4397.
Toward Industry 4.0 With IoT: Optimizing Business Processes in an Evolving Manufacturing Factory Journal Article
In: Frontiers in ICT, 6 , pp. 17, 2019, ISSN: 2297-198X.
Enhancing Security in a Big Stream Cloud Architecture for the Internet of Things Through Blockchain Book Chapter
In: Kecskemeti, Gabor (Ed.): Applying Integration Techniques and Methods in Distributed Systems and Technologies, pp. 104-133, IGI Global, Hershey, PA, 2019, ISBN: 978-152-25-8295-3.
Wireless Mesh Networking: An IoT-Oriented Perspective Survey on Relevant Technologies Journal Article
In: Future Internet, 11 (4), 2019, ISSN: 1999-5903.
Design and experimental performance analysis of a B.A.T.M.A.N.-based double Wi-Fi interface mesh network Journal Article
In: Future Generation Computer Systems, 92 , pp. 593-603, 2019, ISSN: 0167-739X.
2018
A Scalable Big Stream Cloud Architecture for the Internet of Things Incollection
In: Fog Computing: Breakthroughs in Research and Practice, pp. 25-53, IGI Global, Hershey, PA, USA, 2018, ISBN: 9781522556497.
From Micro to Macro IoT: Challenges and Solutions in the Integration of IEEE 802.15.4/802.11 and Sub-GHz Technologies Journal Article
In: IEEE Internet of Things Journal, 5 (2), pp. 784-793, 2018, ISSN: 2327-4662.
THORIN: an Efficient Module for Federated Access and Threat Mitigation in Big Stream Cloud Architectures Journal Article
In: IEEE Cloud Computing, 5 (1), pp. 38-48, 2018, ISSN: 2325-6095.
2016
Integration of Wi-Fi mobile nodes in a Web of Things Testbed Journal Article
In: ICT Express, 2 (3), pp. 96 - 99, 2016, ISSN: 2405-9595, (Special Issue on ICT Convergence in the Internet of Things (IoT)).
Applying Security to a Big Stream Cloud Architecture for the Internet of Things Journal Article
In: International Journal of Distributed Systems and Technologies (IJDST), 7 (1), pp. 37-58, 2016, ISSN: 1947-3532.
UTravel: Smart mobility with a novel user profiling and recommendation approach Journal Article
In: Pervasive and Mobile Computing, 38 (2), pp. 474-489, 2016.
2015
Design and Deployment of an IoT Application-Oriented Testbed Journal Article
In: Computer, 48 (9), pp. 32-40, 2015, ISSN: 0018-9162.
A Scalable Big Stream Cloud Architecture for the Internet of Things Journal Article
In: International Journal of Systems and Service-Oriented Engineering (IJSSOE), 5 (4), pp. 26-53, 2015, ISSN: 1947-3052.
An Open-Source Cloud Architecture for Big Stream IoT Applications Incollection
In: Žarko, Ivana Podnar; Pripužić, Krešimir; Serrano, Martin (Ed.): Interoperability and Open-Source Solutions for the Internet of Things (International Workshop, FP7 OpenIoT Project, Held in Conjunction with SoftCOM 2014, Split, Croatia, September 18, 2014, Invited , 9001 , pp. 73-88, Springer International Publishing, 2015, ISBN: 978-3-319-16545-5.
2014
A Graph-based cloud architecture for big stream real-time applications in the Internet of Things Inproceedings
In: 2nd International Workshop on CLoud for IoT (CLIoT 2014), Manchester, United Kingdom, September 2014, 2014.