Laura Belli

@article{gamadabecarafesg:2025:psy,

title = {Cardiac Autonomic Responsivity to Car Driving in a Real Context},

author = {Sara Gambetta and Veronica Mattioli and Luca Davoli and Laura Belli and Luca Carnevali and Riccardo Raheli and Gianluigi Ferrari and Andrea Sgoifo},

doi = {10.1027/0269-8803/a000345},

issn = {2151-2124},

year  = {2025},

date = {2025-06-19},

urldate = {2025-01-01},

journal = {Journal of Psychophysiology},

volume = {39},

number = {1},

pages = {36-48},

abstract = {Driving a vehicle is a complex behavior requiring an optimal psychophysiological state in order to safely accomplish the task. The identification of human factors influencing driving behavior could enable the development of technologies for monitoring drivers and improving their comfort. This study aims to monitor the driver’s cardiac autonomic activity during real road driving, assuming psychophysiological variations depending on the driving context (e.g., ring road vs. urban driving) and the induction of psychosocial stress during urban driving activity. Moreover, we investigated the extent to which perceived stress, anxiety symptoms, habitual driving behavior as well as sex, and driving experience, influenced cardiac autonomic responses while driving. Heart rate (HR) and its variability (HRV) were assessed during a real driving task in a sample of thirty-eight drivers, including twenty males and eighteen females. Drivers’ psychometric characteristics were collected using questionnaires. HRV analysis revealed a significant overall autonomic activation while driving, independent of the exposure to external stressors. Neither sex nor driving experience seemed to affect cardiac autonomic response to driving. A significant positive correlation emerged between anxiety-stress symptoms and aberrant driving behavior. In summary, our results suggest that the overall driving task produced a notable impact on cardiac autonomic neural modulation. Understanding the factors that influence driving performance and modulate the resulting physiological response could provide a springboard for practical applications, such as the development of human-vehicle interaction monitoring systems for optimal psychophysiological arousal while driving.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{roetal:2025:oj-ies,

title = {Artificial Intelligence for Wireless Communications: The InSecTT Perspective},

author = {Ramiro Samano Robles and Gowhar Javanmardi and Christoph Pilz and Przemyslaw Kwapisiewicz and Mateusz Rzymowski and Lukasz Kulas and Luca Davoli and Laura Belli and Gianluigi Ferrari and Bernd-Ludwig Wenning and Bugra Gonca and R. Venkatesha Prasad and Ashutosh Simha and Markku Kiviranta and Ilkka Moilanen and Sean Robinson and Gennaro Cirillo and Mujdat Soyturk and Yavuz Selim Bostanci and Leander B. Hörmann},

doi = {10.1109/OJIES.2025.3560946},

issn = {2644-1284},

year  = {2025},

date = {2025-04-16},

urldate = {2025-01-01},

journal = {IEEE Open Journal of the Industrial Electronics Society},

volume = {6},

pages = {802-819},

abstract = {This article presents an overview of how Artificial Intelligence (AI) and edge technology have been used to improve wireless connectivity in multiple industrial Use Cases (UCs) of the EU project “Intelligent Secure Trustable Things” (InSecTT). We present a brief introduction of the InSecTT framework for cross-domain architecture design, which targets UCs assisted by reusable and/or interoperable technical Building Blocks (BBs). These BBs constitute the “bricks” containing AI and supporting components that were used to build different UCs. The framework consists of multiple stages based on the processing of UC/BB requirements (RQs). These stages include collection, harmonization, refinement, classification, architecture alignment, and functionality modeling of RQs. The most relevant results of these stages are discussed here, with emphasis on the need for a refined granularity of technical components with common functionalities named Sub-Building blocks (SBBs), where collaboration and cross-domain reusability were optimized. The design process shed light on how AI and SBBs were implemented across different layers and entities of our reference architecture for the Internet-of-Things (IoT), including the interfaces used for information exchange. This detailed interface analysis is expected to reveal issues such as bottlenecks, constraints, vulnerabilities, scalability problems, security threats, etc. This will, in turn, contribute to identifying design gaps of AI-enabled IoT systems. The article summarizes the SBBs related to wireless connectivity, including a general description, implementation issues, a comparison of results, adopted interfaces, and conclusions across domains.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{bedaodprgagafe:2025:dib,

title = {Smart agriculture dataset in a tomato cultivation under different irrigation regimes},

author = {Laura Belli and Luca Davoli and Giulia Oddi and Luca Preite and Martina Galaverni and Tommaso Ganino and Gianluigi Ferrari},

doi = {10.1016/j.dib.2025.111521},

issn = {2352-3409},

year  = {2025},

date = {2025-04-08},

urldate = {2025-01-01},

journal = {Data in Brief},

volume = {60},

pages = {111521},

abstract = {This dataset contains data collected in a tomato cultivation (namely, a Solanum lycopersicum L. cv. HEINZ 1301 cultivation) located at the “Azienda Sperimentale Stuard,” Parma, Italy, through an IoT infrastructure featuring Long Range Wide Area Network (LoRaWAN)-enabled commercial devices deployed in the crop during the summer 2023 period (June 29–September 13). The IoT architecture also controls the irrigation system deployed to manage the watering conditions in the tomato crop, in detail considering three different experimental lines (each one associated with a different irrigation regime): (i) line #1 was irrigated with a water quantity equal to the irrigation recommendation provided by a national cloud service, denoted as Irriframe and developed by the Water Boards Italian Association (ANBI); (ii) line #2 was irrigated with a water quantity equal to 60% of line #1; (iii) line #3 was irrigated with a water quantity equal to 30% of line #1. The dataset comprises 4 different CSV files. The first three files (named as “stuard_environmental_data.csv,” “stuard_water_meter_data.csv,” and “stuard_soil_data.csv”) contain the information sampled every 10 minute by the IoT devices deployed in the crop—one environmental sensor, three water meters, and three soil sensors. The fourth CSV file (named as “indicators.csv”) contains the values of agronomic indicators of interest, calculated daily and mainly depending on daily air temperature values: (i) the Growing Degree Days (GDD) index and (ii) the Heat Units indicators, both calculated on the collected experimental tomato crop data.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{gaother:2025:cea,

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},

doi = {10.1016/j.compag.2024.109660},

issn = {0168-1699},

year  = {2024},

date = {2024-12-01},

urldate = {2025-01-01},

journal = {Computers and Electronics in Agriculture},

volume = {229},

pages = {109660},

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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{madabegacasgrafe:2024:sensors,

title = {IoT-Based Assessment of a Driver’s Stress Level},

author = {Veronica Mattioli and Luca Davoli and Laura Belli and Sara Gambetta and Luca Carnevali and Andrea Sgoifo and Riccardo Raheli and Gianluigi Ferrari},

doi = {10.3390/s24175479},

issn = {1424-8220},

year  = {2024},

date = {2024-08-23},

urldate = {2024-01-01},

journal = {Sensors},

volume = {24},

number = {17},

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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kaetal:2024:openreseurope,

title = {The OPEVA Manifest: OPtimisation of Electrical Vehicle Autonomy, a Research and Innovation project},

author = {Alper Kanak and Salih Ergün and Ibrahim Arif and S. Halit Ergün and Cengiz Bektaş and Ali Serdar Atalay and Oguzhan Herkiloğlu and Dominique Defossez and Ahmet Yazici and Luis Lino Ferreira and Martin Strelec and Karel Kubicek and Martin Cech and Luca Davoli and Laura Belli and Gianluigi Ferrari and Dilara Bayar and Ali Kafali and Yunus Karamavuş and Asaf Mustafa Sofu and Ahu Ece Hartavi Karci and Patrick Constant},

doi = {10.12688/openreseurope.17021.1},

year  = {2024},

date = {2024-06-19},

urldate = {2024-01-01},

journal = {Open Research Europe},

volume = {4},

number = {118},

pages = {1-25},

abstract = {Electromobility is a critical component of Europe’s strategy to create a more sustainable society and support the European Green Transition while enhancing quality of life. Electrification also plays an important role in securing Europe’s position in the growing market of electric and autonomous vehicles (EAV). The EU-funded OPEVA project aims to take a big step towards deployment of sustainable electric vehicles by means of optimising their support in an ecosystem. Specifically, the project focuses on analysing and designing optimisation architecture, reducing battery charging time, and developing infrastructure, as well as reporting on the driver-oriented human factors. Overall, OPEVA’s goal is to enhance EAV market penetration and adoption, making them more accessible and convenient. The aim of this paper is to inform the European automotive, transportation, energy and mobility community be presenting the OPEVA manifestation, and the overall solution strategy solidified through the progress throughout the first year of the project.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dabefe:2023:dib,

title = {Air quality dataset from an indoor airport travelers transit area},

author = {Luca Davoli and Laura Belli and Gianluigi Ferrari},

doi = {10.1016/j.dib.2023.109821},

issn = {2352-3409},

year  = {2023},

date = {2023-11-20},

urldate = {2024-01-01},

journal = {Data in Brief},

volume = {52},

pages = {109821},

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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{bedafe:2023:computer,

title = {Smart City as an Urban Intelligent Digital System: The Case of Parma},

author = {Laura Belli and Luca Davoli and Gianluigi Ferrari},

doi = {10.1109/MC.2023.3267245},

issn = {1558-0814},

year  = {2023},

date = {2023-06-16},

urldate = {2023-07-01},

journal = {Computer},

volume = {56},

number = {7},

pages = {106-109},

abstract = {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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dabedetaabfe:2022:cisap10,

title = {On Safety Enhancement in IIoT Scenarios Through Heterogeneous Localization Techniques},

author = {Luca Davoli and Laura Belli and Francesco Denaro and Dinesh Tamang and Andrea Abrardo and Gianluigi Ferrari},

doi = {10.3303/CET2291044},

year  = {2022},

date = {2022-06-15},

urldate = {2022-06-01},

journal = {Chemical Engineering Transactions},

volume = {91},

pages = {259-264},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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},

doi = {10.3390/safety6040055},

issn = {2313-576X},

year  = {2020},

date = {2020-12-24},

journal = {Safety},

volume = {6},

number = {4},

pages = {1-33},

publisher = {MDPI AG},

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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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},

url = {https://www.mdpi.com/2624-6511/3/3/52},

doi = {10.3390/smartcities3030052},

year  = {2020},

date = {2020-09-18},

journal = {Smart Cities},

volume = {3},

pages = {1039-1071},

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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{mamebeda:2019:maco,

title = {Internet of Things e Industria 4.0. Un case study di successo di digital manufacturing},

author = {Pier Luigi Marchini and Alice Medioli and Laura Belli and Luca Davoli},

url = {http://www.francoangeli.it/Riviste/Scheda_rivista.aspx?idArticolo=65143},

doi = {10.3280/MACO2019-003002},

issn = {2239-4397},

year  = {2019},

date = {2019-12-19},

journal = {Management Control},

number = {3},

pages = {11-34},

abstract = {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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{bedamemafe:2019:frontiers,

title = {Toward Industry 4.0 With IoT: Optimizing Business Processes in an Evolving Manufacturing Factory},

author = { Laura Belli and Luca Davoli and Alice Medioli and Pier Luigi Marchini and Gianluigi Ferrari},

doi = {10.3389/fict.2019.00017},

issn = {2297-198X},

year  = {2019},

date = {2019-08-28},

journal = {Frontiers in ICT},

volume = {6},

pages = {17},

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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{cidabefe:2019:futureinternet,

title = {Wireless Mesh Networking: An IoT-Oriented Perspective Survey on Relevant Technologies},

author = {Antonio Cilfone and Luca Davoli and Laura Belli and Gianluigi Ferrari},

url = {http://www.mdpi.com/1999-5903/11/4/99},

doi = {10.3390/fi11040099},

issn = {1999-5903},

year  = {2019},

date = {2019-04-17},

journal = {Future Internet},

volume = {11},

number = {4},

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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dacibefe:2019:fgcs,

title = {Design and experimental performance analysis of a B.A.T.M.A.N.-based double Wi-Fi interface mesh network},

author = {Luca Davoli and Antonio Cilfone and Laura Belli and Gianluigi Ferrari},

doi = {10.1016/j.future.2018.02.015},

issn = {0167-739X},

year  = {2019},

date = {2019-01-01},

journal = {Future Generation Computer Systems},

volume = {92},

pages = {593-603},

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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dabecife:iotj:2018,

title = {From Micro to Macro IoT: Challenges and Solutions in the Integration of IEEE 802.15.4/802.11 and Sub-GHz Technologies},

author = {Luca Davoli and Laura Belli and Antonio Cilfone and Gianluigi Ferrari},

url = {https://ieeexplore.ieee.org/document/8024171/},

doi = {10.1109/JIOT.2017.2747900},

issn = {2327-4662},

year  = {2018},

date = {2018-04-01},

journal = {IEEE Internet of Things Journal},

volume = {5},

number = {2},

pages = {784-793},

abstract = {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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dabevefe:2018:ccm,

title = {THORIN: an Efficient Module for Federated Access and Threat Mitigation in Big Stream Cloud Architectures},

author = {Luca Davoli and Laura Belli and Luca Veltri and Gianluigi Ferrari},

url = {https://ieeexplore.ieee.org/document/8327545/},

doi = {10.1109/MCC.2018.011791713},

issn = {2325-6095},

year  = {2018},

date = {2018-03-28},

journal = {IEEE Cloud Computing},

volume = {5},

number = {1},

pages = {38-48},

abstract = {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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Davoli201696,

title = {Integration of Wi-Fi mobile nodes in a Web of Things Testbed},

author = {Luca Davoli and Laura Belli and Antonio Cilfone and Gianluigi Ferrari},

editor = {Yacine Ghamri-Doudane and Yeong Min Jang and Daeyoung Kim and Hossam Hassanein and JaeSeung Song},

url = {http://www.sciencedirect.com/science/article/pii/S2405959516300637},

doi = {10.1016/j.icte.2016.07.001},

issn = {2405-9595},

year  = {2016},

date = {2016-08-05},

journal = {ICT Express},

volume = {2},

number = {3},

pages = {96 - 99},

abstract = {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.},

note = {Special Issue on ICT Convergence in the Internet of Things (IoT)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{becidafemepi2016,

title = {Applying Security to a Big Stream Cloud Architecture for the Internet of Things},

author = {Laura Belli and Simone Cirani and Luca Davoli and Gianluigi Ferrari and Lorenzo Melegari and Marco Picone},

doi = {10.4018/IJDST.2016010103},

issn = {1947-3532},

year  = {2016},

date = {2016-01-14},

journal = {International Journal of Distributed Systems and Technologies (IJDST)},

volume = {7},

number = {1},

pages = {37-58},

publisher = {IGI Global},

abstract = {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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{amoretti2016utravel,

title = {UTravel: Smart mobility with a novel user profiling and recommendation approach},

author = {Michele Amoretti and Laura Belli and Francesco Zanichelli},

url = {https://www.sciencedirect.com/science/article/pii/S1574119216301341},

doi = {10.1016/j.pmcj.2016.08.008},

year  = {2016},

date = {2016-01-01},

journal = {Pervasive and Mobile Computing},

volume = {38},

number = {2},

pages = {474-489},

publisher = {Elsevier},

abstract = {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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ieee-computer-sep2015-testbed,

title = {Design and Deployment of an IoT Application-Oriented Testbed},

author = {Laura Belli and Simone Cirani and Luca Davoli and Andrea Gorrieri and Mirko Mancin and Marco Picone and Gianluigi Ferrari},

url = {https://ieeexplore.ieee.org/document/7274422},

doi = {10.1109/MC.2015.253},

issn = {0018-9162},

year  = {2015},

date = {2015-09-23},

journal = {Computer},

volume = {48},

number = {9},

pages = {32-40},

abstract = {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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}