Journals

@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.},

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}

@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.},

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@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 = {},

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}

@article{madafe:2025:dlt,

title = {Deep Learning Algorithms for Cryptocurrency Price Prediction: A Comparative Analysis},

author = {Armin Mazinani and Luca Davoli and Gianluigi Ferrari},

doi = {10.1145/3699966},

year  = {2025},

date = {2025-02-07},

urldate = {2025-01-01},

journal = {Distributed Ledger Technologies: Research and Practice},

volume = {4},

number = {1},

pages = {1-38},

publisher = {Association for Computing Machinery},

address = {New York, NY, USA},

abstract = {Over the past years, cryptocurrencies have experienced a surge in popularity within the financial markets. As of today, besides being considered for investment purposes, they also serve as a widely accepted form of currency for everyday transactions. Due to the intricate characteristics of financial markets and their dependence on various factors to determine the prices of stocks and assets, the ability to predict such prices is crucial to make investment choices, especially in terms of cryptocurrencies. In this work, a comparative analysis on the suitability of Deep Learning (DL) algorithms (effective for time series forecasting) in predicting the price of three cryptocurrencies (namely Bitcoin, BTC; Ethereum, ETH; and Ripple, XRP) is assessed in terms of both short-term and long-term prediction accuracy. The results, evaluated using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and coefficient of determination (denoted as (R^2) ), reveal that: Transformer is generally more effective for short-term forecasts and also performs well for long-term predictions; Convolutional Neural Network-Recurrent Neural Network (CNN-RNN) demonstrates the lowest complexity in terms of number of Multiply and ACcumulate (MAC) operations; SimpleRNN has the fewest parameters and the smallest FLASH memory requirement. Overall, CNN-Gated Recurrent Unit (CNN-GRU) provides the best joint accuracy-complexity for predicting BTC and ETH prices, whereas CNN-RNN yields superior results for XRP price prediction.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{damofe:2025:iotj,

title = {RouMBLE: A Sink-Oriented Routing Protocol for BLE Mesh Networks},

author = {Luca Davoli and Massimo Moreni and Gianluigi Ferrari},

doi = {10.1109/JIOT.2024.3524746},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {IEEE Internet of Things Journal},

volume = {12},

number = {10},

pages = {14202-14218},

abstract = {In Internet of Things (IoT)-like contexts, there is often the need to leverage traffic routing mechanisms among heterogeneous devices, especially when classical (and well-known) addressing paradigms cannot be adopted or supported by constrained IoT devices deployed on the field (e.g., due to memory footprint, internal limitations, etc.). This is even more true (and necessary) when nodes interact in unstructured networks (e.g., mesh-like) lacking a specific topology (e.g., exploiting flooding approaches to transfer information) and external “smart” devices should be allowed to interact with these networks. To this end, in this article a multisink routing protocol, denoted as routing on mesh Bluetooth low energy (RouMBLE), is proposed. Our implementation relies on Bluetooth low-energy advertisement channels and allows sink nodes to control topology formation and data collection (with both unicast and broadcast communications), with nodes identified with compressed addresses. A relevant experimental application to environmental lighting management is presented.},

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{suoldastnofe:2024:access,

title = {CSI-RSRP-Based Unnecessary Handover Mitigation Through Linear Regression in Dynamic 5G NR Environments},

author = {Sunil Mathew and Eleonora Oliosi and Luca Davoli and Nicolò Strozzi and Andrea Notari and Gianluigi Ferrari},

doi = {10.1109/ACCESS.2024.3451483},

issn = {2169-3536},

year  = {2024},

date = {2024-08-29},

urldate = {2024-01-01},

journal = {IEEE Access},

volume = {12},

pages = {121808-121821},

abstract = {5G New Radio (NR), introduced in 2019 in the 3rd Generation Partnership Project (3GPP) Release 15, has become the global radio standard for 5G networks. Because of the presence of an increasing number of available 5G gNodeBs (gNBs), HandOver (HO) management is crucial, especially in terms of Quality of Service (QoS) and Quality of Experience (QoE) perceived by a User Equipment (UE). Unnecessary HandOvers (UHOs) cause latency peaks (on the order hundreds of milliseconds) and multiple throughput drops in 5G communications. In this paper, we first carry out an experimental campaign to investigate the behaviour of latency and throughput in correspondence to UHOs. Then, on the basis of a Matlab-based 5G NR DownLink (DL) transmission simulator, we propose an innovative linear regression-based algorithm to avoid UHOs, which relies on Channel State Information-Reference Signal Received Power (CSI-RSRP) measurements.},

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{padafe:2024:taes,

title = {Wi-Fi-Based Real-Time UAV Localization: A Comparative Analysis Between RSSI-Based and FTM-Based Approaches},

author = {Emanuele Pagliari and Luca Davoli and Gianluigi Ferrari},

doi = {10.1109/TAES.2024.3433829},

issn = {1557-9603},

year  = {2024},

date = {2024-07-25},

urldate = {2024-01-01},

journal = {IEEE Transactions on Aerospace and Electronic Systems},

volume = {60},

number = {6},

pages = {8757-8778},

abstract = {Wi-Fi connectivity for localization purposes has been used for several years in the Internet of Things (IoT) context, where the (general) static nature of IoT devices allows to approximately localize them in known environments with low effort and implementation costs. While the accuracy of Wi-Fi localization for IoT applications can be considered as acceptable, the adoption of Wi-Fi-based localization for (a highly mobile) unmanned aerial vehicle (UAV) has received limited attention. In this article, a low-cost and low-complexity system architecture is proposed and exploited to perform a comparative analysis between two Wi-Fi-based localization approaches: the traditional received signal strength indicator (RSSI) ranging and the more recent fine time measurement (FTM), based on the IEEE 802.11mc amendment. Our goal is to estimate and compare the efficacy of the proposed system for real-time positioning of a static or moving UAV, evaluating the impact of different filtering solutions on the localization accuracy. The obtained results show that FTM-based localization is more accurate, reducing the positioning error by 37% with respect to the RSSI-based positioning approach. Our results also confirm the better overall performance of the FTM-based solution for low-cost localization applications, discussing its limitations, scalability, and advantages as a viable backup positioning solution in (weak or denied) Global Navigation Satellite System-based environments and scenarios.},

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{padacipafe:2024:iop,

title = {On UAV Terrestrial Connectivity Enhancement through Smart Selective Antennas},

author = {Emanuele Pagliari and Luca Davoli and Giordano Cicioni and Valentina Palazzi and Gianluigi Ferrari},

doi = {10.1088/1742-6596/2716/1/012057},

year  = {2024},

date = {2024-03-17},

urldate = {2024-03-17},

journal = {Journal of Physics: Conference Series},

volume = {2716},

number = {1},

pages = {012057},

publisher = {IOP Publishing},

abstract = {Nowadays, Unmanned Aerial Vehicles (UAVs) are widely used in heterogeneous contexts and, thanks to a continuous technological evolution, are going to be used for several applications such as, for example, Beyond Visual Line of Sight (BVLOS) operations. Since in BVLOS flights the UAV and the ground control center may not have a direct visibility with each other, a robust communication system is needed to provide reliable connectivity. Although a cellular (4G/5G) network is the current best candidate to enable BVLOS applications, there are still some limitations to overcome, as 4G (LTE) and 5G (NR) cellular networks are natively designed for terrestrial use. In this paper, we first investigate current cellular communication limitations for UAV-based applications, in particular taking into account both results available in the literature, as well as experimental performance campaigns. Then, a viable solution for mitigating these drawbacks exploiting selective on-board antennas is proposed, whose performance is experimentally investigated with a preliminary prototypical architecture.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{modadhkufera:24:jnca,

title = {Throughput and delay analysis of cognitive M2M communications},

author = {Soumen Mondal and Luca Davoli and Sanjay Dhar Roy and Sumit Kundu and Gianluigi Ferrari and Riccardo Raheli},

doi = {10.1016/j.jnca.2024.103856},

issn = {1084-8045},

year  = {2024},

date = {2024-03-04},

urldate = {2024-01-01},

journal = {Journal of Network and Computer Applications},

volume = {225},

pages = {103856},

abstract = {In this paper, we analyze throughput and delay performance of clustered Machine Type Communication (MTC) devices which access an eNodeB utilizing a primary spectrum in underlay mode. We assume that the MTC devices form two clusters and there is an optimal preamble allocation between the two clusters to maximize the throughput. We further investigate the impact of the tolerable interference threshold on throughput, successful preamble decoding probability, and delay. Then, the impact of the preamble partition factor and the access barring factor on throughput and delay is analyzed. Finally, we evaluate the impact of the number of devices, retransmission requests, and preamble partitions on the delay.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{cidafe:2024:tmc,

title = {LoRa Meets IP: A Container-Based Architecture to Virtualize LoRaWAN End Nodes},

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

doi = {10.1109/TMC.2024.3359150},

issn = {1558-0660},

year  = {2024},

date = {2024-01-26},

urldate = {2024-10-01},

journal = {IEEE Transactions on Mobile Computing},

volume = {23},

number = {10},

pages = {9191-9207},

abstract = {In this work, a container-based architecture for the integration of Long Range Wide Area Network (LoRaWAN) end nodes—e.g., used to monitor industrial machines or mobile entities in specific environments—with Internet Protocol (IP)-based networks is proposed and its performance is investigated. To this end, we exploit the native service and resource discovery support of the Constrained Application Protocol (CoAP), as well as its light traffic requirements, owing to its use of User Datagram Protocol (UDP) rather than Transmission Control Protocol (TCP). This approach (i) adapts transparently (with no impact) to both private and public LoRaWAN networks, (ii) enables seamless interaction between LoRaWAN-based and CoAP-based nodes, through a logical “virtualization” of LoRaWAN nodes at server side, and (iii) enables routing among LoRaWAN end nodes, overcoming LoRaWAN's absence of inter-node communication and lack of compliance (at the end nodes’ side) with IP. Two virtualization approaches are proposed: (i) virtualization of a single end node (represented as a CoAP server) per container and (ii) virtualization of multiple end nodes (as CoAP servers) per container. Finally, deployments of the proposed virtualization architectures, using both a laptop and an Internet of Things (IoT) device (e.g., a Raspberry Pi), are considered, highlighting how the best solution relies on the use of several containers, with more than one CoAP server per container.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{padacipamealrofe:2023:access,

title = {Smart Selective Antennas System (SSAS): Improving 4G LTE Connectivity for UAVs Using Directive Selective Antennas},

author = {Emanuele Pagliari and Luca Davoli and Giordano Cicioni and Valentina Palazzi and Paolo Mezzanotte and Federico Alimenti and Luca Roselli and Gianluigi Ferrari},

doi = {10.1109/ACCESS.2023.3347335},

issn = {2169-3536},

year  = {2023},

date = {2023-12-25},

urldate = {2024-01-01},

journal = {IEEE Access},

volume = {12},

pages = {7040-7062},

abstract = {In this paper, the prototypical deployment of a Multiple-Input-Multiple-Output (MIMO) antennas system, denoted as Smart Selective Antennas System (SSAS), aiming at mitigating inter-cell interference effects of cellular networks for in-flight Unmanned Aerial Vehicles (UAVs), is discussed. In detail, the proposed SSAS is beneficial to increase the communication reliability over existing cellular networks, especially with regard to complex Beyond Visual Line of Sight (BVLOS) drones’ missions and applications. Its deployment is motivated as existing 4G Long Term Evolution (LTE) cellular networks (as well as 5G networks) are mainly designed and optimized for terrestrial utilization, thus not taking into account interference effects on flying connected devices. The prototypical implementation of the SSAS has been expedient to conduct multiple experimental flights with a drone at different altitudes, collecting performance results and validating the proposed SSAS as a viable solution for inter-cell interference mitigation.},

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{padafe:2023:iotj,

title = {Harnessing Communication Heterogeneity: Architectural Design, Analytical Modeling, and Performance Evaluation of an IoT Multi-Interface Gateway},

author = {Emanuele Pagliari and Luca Davoli and Gianluigi Ferrari},

doi = {10.1109/JIOT.2023.3317672},

year  = {2023},

date = {2023-09-20},

urldate = {2024-01-01},

journal = {IEEE Internet of Things Journal},

volume = {11},

number = {5},

pages = {8030-8051},

abstract = {Given the massive deployment of Internet of Things (IoT) applications over the last decade, the need for gateways able to efficiently route information flows across multiple heterogeneous networks has emerged, bringing new challenges. Therefore, the design and implementation of IoT gateways is crucial. In this article, with reference to the architecture of a prototypical multi-interface gateway (MIG) (based on commercial-off-the-shelf (COTS) devices), we evaluate its performance: 1) analytically, through an innovative Markov chain-based model; 2) by simulation, with a Python simulator; and 3) experimentally, through the (starting) COTS device-based prototype. In detail, the MIG is equipped with heterogeneous wireless communication interfaces (namely, LoRaWAN, BLE, cellular 4G Cat. 4, and IEEE 802.11 Wi-Fi 2.4 GHz) and is applicable to multiple IoT scenarios. The obtained simulation and experimental results show the validity of the proposed analytical model. Further improvements of the proposed framework are eventually discussed.},

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{nokey,

title = {On Sensor Data Clustering for Machine Status Monitoring and Its Application to Predictive Maintenance},

author = {Eleonora Oliosi and Gabriele Calzavara and Gianluigi Ferrari},

doi = {10.1109/JSEN.2023.3260314},

year  = {2023},

date = {2023-05-01},

urldate = {2023-05-01},

journal = {IEEE Sensors Journal},

volume = {23},

number = {9},

pages = {9620-9639},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{camadaciyuwafe:2023:comnet,

title = {Experimental analysis of RSSI-based localization algorithms with NLOS pre-mitigation for IoT applications},

author = {Fabrizio Carpi and Marco Martalò and Luca Davoli and Antonio Cilfone and Yingjie Yu and Yi Wang and Gianluigi Ferrari},

doi = {10.1016/j.comnet.2023.109663},

issn = {1389-1286},

year  = {2023},

date = {2023-03-06},

urldate = {2023-01-01},

journal = {Computer Networks},

volume = {225},

pages = {109663},

abstract = {In this paper, we propose an effective target localization strategy for Internet of Things (IoT) scenarios, where positioning is performed by resource-constrained devices. Target-anchor links may be impaired by Non-Line-Of-Sight (NLOS) communication conditions. In order to derive a feasible IoT-oriented positioning strategy, we rely on the acquisition, at the target, of a sequence of consecutive measurements of the Received Signal Strength Indicator (RSSI) of the wireless signals transmitted by the anchors. We then consider a pragmatic approach according to which the NLOS channels are pre-mitigated and “transformed” into equivalent Line-Of-Sight (LOS) channels to estimate more accurately each target-anchor distance. The estimated distances feed “agnostic” localization algorithms, operating as if all links were LOS. We experimentally assess the performance of our approach in indoor (IEEE 802.11-based) and outdoor (Long Term Evolution, LTE-based) scenarios, considering both geometric and Particle Swarm Optimization (PSO)-based localization algorithms. Even if NLOS mitigation per single communication link is very effective, our results show that, in a given environment, it is possible to derive an “average” NLOS mitigation strategy regardless of the specific position of the target in the given environment. This is crucial to limit the computational complexity at IoT nodes performing localization, yet guaranteeing a relatively high (for IoT scenarios) localization accuracy, especially in an IEEE 802.11-based indoor case (with six anchors). The obtained performance compares favorably (in relative terms) with that obtained with more sophisticated wireless technologies (e.g., Ultra-WideBand, UWB).},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{hidagrfe:2023,

title = {DynGATT: A dynamic GATT-based data synchronization protocol for BLE networks},

author = {Christian Hirsch and Luca Davoli and Radu Grosu and Gianluigi Ferrari},

doi = {10.1016/j.comnet.2023.109560},

issn = {1389-1286},

year  = {2023},

date = {2023-01-10},

urldate = {2023-01-01},

journal = {Computer Networks},

volume = {222},

pages = {109560},

abstract = {Bluetooth Low Energy (BLE) is a wireless communication technology for power-constrained Internet of Things (IoT) applications. BLE data can be transmitted via either the IPv6 or the Generic ATTribute (GATT) Profile protocol, with the former supporting dynamic IoT structures and the latter being application-friendly. In fact, GATT requires the data layout to be known in advance by peer devices, in order to properly interpret the received data. In this paper, we introduce DynGATT, a protocol that achieves the benefits of both IPv6 and GATT, by extending GATT in a seamless fashion to support dynamic IoT structures. The key idea of DynGATT is to use GATT descriptors, originally intended to specify data in static IoT scenarios, to also specify IoT systems whose structures may dynamically evolve. Peer devices reading these descriptors will know how to interpret the data of GATT characteristics provided by devices joining the IoT network. Because no additional data have to be transmitted, the connection time is then reduced with respect to classical BLE. DynGATT has been implemented and tested in an agricultural IoT application, with different types of sensor nodes. Our experimental evaluation shows that DynGATT is very power-efficient, despite its added flexibility. Its worst-case power consumption is only around 19.37µA per data transmission and around 41.37µA overall. This consumption can be further reduced by using the methods discussed in this paper. To the best of our knowledge, this work is the first to support dynamic IoT structures in a GATT-based setting.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{AleenaFarooq2022,

title = {Type-II Diabetes Prediction by using Classification and Novel based Method (AWOD)},

author = {Aleena Farooq and Muhammad Kamran Abid and Wasif Akbar and Hafiz Humza and Naeem Aslam},

doi = {10.56979/401/2022/110},

issn = {2710-1606},

year  = {2022},

date = {2022-12-01},

urldate = {2022-12-01},

journal = {Journal of Computing & Biomedical Informatics},

volume = {4},

number = {1},

pages = {152–174},

publisher = {Research Center of Computing and Biomedical Informatics},

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{Hilmand2022,

title = {A Blockchain-based privacy preserving mechanism for mobile crowdsensing},

author = {Khan Hilmand and Khan Hajra and Shauqat Ayesha and Tahir Sibgha and Hanif Sarmad and Hamza Hafiz},

doi = {10.17352/tcsit.000044},

issn = {2641-3086},

year  = {2022},

date = {2022-02-01},

urldate = {2022-02-01},

journal = {Trends in Computer Science and Information Technology},

volume = {7},

number = {1},

pages = {1–6},

publisher = {Peertechz Publications Private Limited},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dapafe:2021:drones,

title = {Hybrid LoRa-IEEE 802.11s Opportunistic Mesh Networking for Flexible UAV Swarming},

author = {Luca Davoli and Emanuele Pagliari and Gianluigi Ferrari},

doi = {10.3390/drones5020026},

issn = {2504-446X},

year  = {2021},

date = {2021-06-24},

urldate = {2021-06-24},

journal = {Drones},

volume = {5},

number = {2},

abstract = {Unmanned Aerial Vehicles (UAVs) and small drones are nowadays being widely used in heterogeneous use cases: aerial photography, precise agriculture, inspections, environmental data collection, search-and-rescue operations, surveillance applications, and more. When designing UAV swarm-based applications, a key “ingredient” to make them effective is the communication system (possible involving multiple protocols) shared by flying drones and terrestrial base stations. When compared to ground communication systems for swarms of terrestrial vehicles, one of the main advantages of UAV-based communications is the presence of direct Line-of-Sight (LOS) links between flying UAVs operating at an altitude of tens of meters, often ensuring direct visibility among themselves and even with some ground Base Transceiver Stations (BTSs). Therefore, the adoption of proper networking strategies for UAV swarms allows users to exchange data at distances (significantly) longer than in ground applications. In this paper, we propose a hybrid communication architecture for UAV swarms, leveraging heterogeneous radio mesh networking based on long-range communication protocols—such as LoRa and LoRaWAN—and IEEE 802.11s protocols. We then discuss its strengths, constraints, viable implementation, and relevant reference use cases.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{codafe:2021:sensors,

title = {Forecasting Air Temperature on Edge Devices with Embedded AI},

author = {Gaia Codeluppi and Luca Davoli and Gianluigi Ferrari},

doi = {10.3390/s21123973},

issn = {1424-8220},

year  = {2021},

date = {2021-06-09},

journal = {Sensors},

volume = {21},

number = {12},

pages = {1-29},

abstract = {With the advent of the Smart Agriculture, the joint utilization of Internet of Things (IoT) and Machine Learning (ML) holds the promise to significantly improve agricultural production and sustainability. In this paper, the design of a Neural Network (NN)-based prediction model of a greenhouse’s internal air temperature, to be deployed and run on an edge device with constrained capabilities, is investigated. The model relies on a time series-oriented approach, taking as input variables the past and present values of the air temperature to forecast the future ones. In detail, we evaluate three different NN architecture types—namely, Long Short-Term Memory (LSTM) networks, Recurrent NNs (RNNs) and Artificial NNs (ANNs)—with various values of the sliding window associated with input data. Experimental results show that the three best-performing models have a Root Mean Squared Error (RMSE) value in the range 0.289÷0.402°C, a Mean Absolute Percentage Error (MAPE) in the range of 0.87÷1.04%, and a coefficient of determination (R2) not smaller than 0.997. The overall best performing model, based on an ANN, has a good prediction performance together with low computational and architectural complexities (evaluated on the basis of the NetScore metric), making its deployment on an edge device feasible.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dapacabaviabfe,

title = {Ultrasonic-Based Environmental Perception for Mobile 5G-Oriented XR Applications},

author = { Luca Davoli and Ioannis Paraskevopoulos and Cinzia Campanella and Stefano Bauro and Tommaso Vio and Andrea Abrardo and Gianluigi Ferrari},

doi = {10.3390/s21041329},

issn = {1424-8220},

year  = {2021},

date = {2021-02-13},

journal = {Sensors},

volume = {21},

number = {4},

pages = {1329},

publisher = {MDPI AG},

abstract = {One of the sectors that is expected to significantly benefit from 5G network deployment is eXtended Reality (XR). Besides the very high bandwidth, reliability, and Quality of Service (QoS) to be delivered to end users, XR also requires accurate environmental perception for safety reasons: this is fundamental when a user, wearing XR equipment, is immersed in a “virtual” world, but moves in a “real” environment. To overcome this limitation (especially when using low-cost XR equipments, such as cardboards worn by the end user), it is possible to exploit the potentialities offered by Internet of Things (IoT) nodes with sensing/actuating capabilities. In this paper, we rely on ultrasonic sensor-based IoT systems to perceive the surrounding environment and to provide “side information” to XR systems, then performing a preliminary experimental characterization campaign with different ultrasonic IoT system configurations worn by the end user. The combination of the information flows associated with XR and IoT components is enabled by 5G technology. An illustrative experimental scenario, relative to a “Tourism 4.0” IoT-aided VR application deployed by Vodafone in Milan, Italy, is presented.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{9486939,

title = {Non-Wearable IoT-Based Smart Ambient Behavior Observation System},

author = {Muhammad Irfan and Husnain Jawad and Barkoum Betra Felix and Saadullah Farooq Abbasi and Anum Nawaz and Saeed Akbarzadeh and Muhammad Awais and Lin Chen and Tomi Westerlund and Wei Chen},

doi = {10.1109/JSEN.2021.3097392},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {IEEE Sensors Journal},

volume = {21},

number = {18},

pages = {20857-20869},

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{SeFeNiPeTaVa_COMPUTER20,

title = {Embedded Artificial Intelligence: the ARTEMIS vision},

author = {Dimitrios Serpanos and Gianluigi Ferrari and George Nikolakopoulos and Jon Perez and Markus Tauber and Stefan Van Baelen},

url = {https://ieeexplore.ieee.org/document/9237345},

doi = {10.1109/MC.2020.3016104},

issn = {0018-9162},

year  = {2020},

date = {2020-10-22},

journal = {Computer},

volume = {53},

number = {11},

pages = {65-69},

abstract = {Advances in embedded and cyberphysical systems have disrupted numerous application domains. We examine the requirements and challenges of these technologies, which present significant opportunities for interdisciplinary research.},

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{Nawaz_2020,

title = {Edge Computing to Secure IoT Data Ownership and Trade with the Ethereum Blockchain},

author = {Anum Nawaz and Jorge Peña Queralta and Jixin Guan and Muhammad Awais and Tuan Nguyen Gia and Ali Kashif Bashir and Haibin Kan and Tomi Westerlund},

doi = {10.3390/s20143965},

issn = {1424-8220},

year  = {2020},

date = {2020-07-01},

urldate = {2020-07-01},

journal = {Sensors},

volume = {20},

number = {14},

pages = {3965},

publisher = {MDPI AG},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{HeFe_IJDSN20,

title = {A novel approach for energy- and memory-efficient data loss prevention to support Internet of Things networks},

author = {Pooya Hejazi and Gianluigi Ferrari},

url = {https://journals.sagepub.com/doi/full/10.1177/1550147720929823},

doi = {10.1177/1550147720929823},

year  = {2020},

date = {2020-06-04},

journal = {International Journal of Distributed Sensor Networks},

volume = {16},

number = {6},

pages = {16 pages},

abstract = {Internet of Things integrates various technologies, including wireless sensor networks, edge computing, and cloud computing, to support a wide range of applications such as environmental monitoring and disaster surveillance. In these types of applications, IoT devices operate using limited resources in terms of battery, communication bandwidth, processing, and memory capacities. In this context, load balancing, fault tolerance, and energy and memory efficiency are among the most important issues related to data dissemination in IoT networks. In order to successfully cope with the abovementioned issues, two main approaches—data-centric storage and distributed data storage—have been proposed in the literature. Both approaches suffer from data loss due to memory and/or energy depletion in the storage nodes. Even though several techniques have been proposed so far to overcome the abovementioned problems, the proposed solutions typically focus on one issue at a time. In this article, we propose a cross-layer optimization approach to increase memory and energy efficiency as well as support load balancing. The optimization problem is a mixed-integer nonlinear programming problem, and we solve it using a genetic algorithm. Moreover, we integrate the data-centric storage features into distributed data storage mechanisms and present a novel heuristic approach, denoted as Collaborative Memory and Energy Management, to solve the underlying optimization problem. We also propose analytical and simulation frameworks for performance evaluation. Our results show that the proposed method outperforms the existing approaches in various IoT scenarios.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{cocidafe:2020:sensors,

title = {LoRaFarM: A LoRaWAN-Based Smart Farming Modular IoT Architecture},

author = {Gaia Codeluppi and Antonio Cilfone and Luca Davoli and Gianluigi Ferrari},

doi = {10.3390/s20072028},

issn = {1424-8220},

year  = {2020},

date = {2020-04-04},

journal = {Sensors},

volume = {20},

number = {7},

abstract = {Presently, the adoption of Internet of Things (IoT)-related technologies in the Smart Farming domain is rapidly emerging. The ultimate goal is to collect, monitor, and effectively employ relevant data for agricultural processes, with the purpose of achieving an optimized and more environmentally sustainable agriculture. In this paper, a low-cost, modular, and Long-Range Wide-Area Network (LoRaWAN)-based IoT platform, denoted as “LoRaWAN-based Smart Farming Modular IoT Architecture” (LoRaFarM), and aimed at improving the management of generic farms in a highly customizable way, is presented. The platform, built around a core middleware, is easily extensible with ad-hoc low-level modules (feeding the middleware with data coming from the sensors deployed in the farm) or high-level modules (providing advanced functionalities to the farmer). The proposed platform has been evaluated in a real farm in Italy, collecting environmental data (air/soil temperature and humidity) related to the growth of farm products (namely grapes and greenhouse vegetables) over a period of three months. A web-based visualization tool for the collected data is also presented, to validate the LoRaFarM architecture.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{9044721,

title = {Novel Framework: Face Feature Selection Algorithm for Neonatal Facial and Related Attributes Recognition},

author = {Muhammad Awais and Chen Chen and Xi Long and Bin Yin and Anum Nawaz and Saadullah Farooq Abbasi and Saeed Akbarzadeh and Linkai Tao and Chunmei Lu and Laishuan Wang and Ronald M. Aarts and Wei Chen},

doi = {10.1109/ACCESS.2020.2982865},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

journal = {IEEE Access},

volume = {8},

pages = {59100-59113},

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{AlFeNeChPePaFeCaCiAzPrMa_SENSORS19,

title = {An Integrated Multi-Sensor Approach for the Remote Monitoring of Parkinson’s Disease},

author = {Giovanni Albani and Claudia Ferraris and Roberto Nerino and Antonio Chimienti and Giuseppe Pettiti and Federico Parisi and Gianluigi Ferrari and Nicola Cau and Veronica Cimolin and Corrado Azzaro and Lorenzo Priano and Alessandro Mauro},

url = {https://www.mdpi.com/1424-8220/19/21/4764},

doi = {10.3390/s19214764},

year  = {2019},

date = {2019-11-02},

journal = {Sensors},

volume = {19},

number = {21:4764},

pages = {18 pages},

abstract = {The increment of the prevalence of neurological diseases due to the trend in population aging demands for new strategies in disease management. In Parkinson’s disease (PD), these strategies should aim at improving diagnosis accuracy and frequency of the clinical follow-up by means of decentralized cost-effective solutions. In this context, a system suitable for the remote monitoring of PD subjects is presented. It consists of the integration of two approaches investigated in our previous works, each one appropriate for the movement analysis of specific parts of the body: low-cost optical devices for the upper limbs and wearable sensors for the lower ones. The system performs the automated assessments of six motor tasks of the unified Parkinson’s disease rating scale, and it is equipped with a gesture-based human machine interface designed to facilitate the user interaction and the system management. The usability of the system has been evaluated by means of standard questionnaires, and the accuracy of the automated assessment has been verified experimentally. The results demonstrate that the proposed solution represents a substantial improvement in PD assessment respect to the former two approaches treated separately, and a new example of an accurate, feasible and cost-effective mean for the decentralized management of PD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{modafe:2019:iotj,

title = {A Wave-Based Request-Response Protocol for Latency Minimization in WSNs},

author = {Riccardo Monica and Luca Davoli and Gianluigi Ferrari},

doi = {10.1109/JIOT.2019.2914578},

issn = {2327-4662},

year  = {2019},

date = {2019-10-10},

journal = {IEEE Internet of Things Journal},

volume = {6},

number = {5},

pages = {7971-7979},

abstract = {Transmission latency is a key performance metrics in most wireless sensor network (WSN) applications. Nodes in a WSN often keep their radio transceivers off, and turn them on periodically using a duty cycling mechanism. The latter is a major source of delay in the network, because transmissions must wait for the next receiver wake-up. In this paper, we present a cross-layer approach to minimize latency of a request-response (RR) protocol adopted in an IEEE 802.15.4-based WSN where the IPv6 routing protocol for low-power and lossy networks (RPLs) is used. Extra wake-ups are generated dynamically to match the predicted arrival time of the response packet, in order to reduce the duty cycling delay. The proposed approach is verified with the Cooja simulator, relying on the Contiki operating system (OS). The observed experimental results show a shorter RR delay with respect to a phase alignment (PA) approach.},

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{FoWaVeFe_FI19,

title = {A Next-generation core network architecture for mobile networks},

author = {Andrea G. Forte and Wei Wang and Luca Veltri and Gianluigi Ferrari},

url = {https://www.mdpi.com/1999-5903/11/7/152},

doi = {10.3390/fi11070152},

year  = {2019},

date = {2019-07-09},

journal = {Future Internet},

volume = {11},

number = {7},

pages = {25 pages},

abstract = {Over the years, the cellular mobile network has evolved from a wireless plain telephone system to a very complex system providing telephone service, Internet connectivity and many interworking capabilities with other networks. Its air interface performance has increased drastically over time, leading to high throughput and low latency. Changes to the core network, however, have been slow and incremental, with increased complexity worsened by the necessity of backwards-compatibility with older-generation systems such as the Global System for Mobile communication (GSM). In this paper, a new virtualized Peer-to-Peer (P2P) core network architecture is presented. The key idea of our approach is that each user is assigned a private virtualized copy of the whole core network. This enables a higher degree of security and novel services that are not possible in today’s architecture. We describe the new architecture, focusing on its main elements, IP addressing, message flows, mobility management, and scalability. Furthermore, we will show some significant advantages this new architecture introduces. Finally, we investigate the performance of our architecture by analyzing voice-call traffic available in a database of a large U.S. cellular network provider.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{vedapevaza:2019:softwarex,

title = {NEMO: A flexible and highly scalable network EMulatOr},

author = { Luca Veltri and Luca Davoli and Riccardo Pecori and Armando Vannucci and Francesco Zanichelli},

doi = {10.1016/j.softx.2019.100248},

issn = {2352-7110},

year  = {2019},

date = {2019-06-20},

journal = {SoftwareX},

volume = {10},

pages = {1-7},

abstract = {Evaluating novel applications and protocols in realistic scenarios has always been a very important task for all stakeholders working in the networking field. Network emulation, being a trade-off between actual deployment and simulations, represents a very powerful solution to this issue, providing a working network platform without requiring the actual deployment of all network components. We present NEMO, a flexible and scalable Java-based network emulator, which can be used to emulate either only a single link, a portion of a network, or an entire network. NEMO is able to work in both real and virtual time, depending on the tested scenarios and goals, and it can be run as either a stand-alone instance on a single machine, or distributed among different network-connected machines, leading to distributed and highly scalable emulation infrastructures. Among different features, NEMO is also capable of virtualizing the execution of third-party Java applications by running them on top of virtual nodes, possibly attached to an emulated or external network.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{LiFeTaMo_WCMC_EEWN_Editorial_19,

title = {Energy efficient wireless networks},

author = {Yujin Lim and Gianluigi Ferrari and Hideyuki Takahashi and Rossana M. C. Andrade},

url = {https://www.hindawi.com/journals/wcmc/2019/1726458/},

doi = {10.1155/2019/1726458},

year  = {2019},

date = {2019-06-12},

journal = {Wireless Communications and Mobile Computing},

volume = {2019},

pages = {1},

abstract = {The scope of this special issue is in line with recent contributions from academia and industry to tackle the technical challenges in order to concretize the energy efficient wireless networks. For the current issue, we are pleased to introduce a collection of papers covering a range of topics as follows:

(i)	Switching strategy for energy efficient wireless networks

(ii)	Clustering protocol for energy efficient wireless networks

(iii)	Transmission power control for energy efficient wireless networks

(iv)	Vertical handover algorithm for energy efficient wireless networks

(v)	Optimization of directional antennas for energy efficient wireless networks},

note = {Article ID 1726458},

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{davoli:2019:applsci,

title = {DiRPL: A RPL-Based Resource and Service Discovery Algorithm for 6LoWPANs},

author = {Luca Davoli and Mattia Antonini and Gianluigi Ferrari},

url = {http://www.mdpi.com/2076-3417/9/1/33},

doi = {10.3390/app9010033},

issn = {2076-3417},

year  = {2019},

date = {2019-01-01},

journal = {Applied Sciences},

volume = {9},

number = {1},

pages = {15},

abstract = {The Internet of Things (IoT) will bring together billions of devices, denoted as Smart Objects (SOs), in an Internet-like architecture. Typically, SOs are embedded devices with severe constraints in terms of processing capabilities, available memory (RAM/ROM), and energy consumption. SOs tend to be deployed in environments in which the human intervention is not suitable or needs to be minimized (e.g., smart city maintenance). They must adapt to the surrounding environment by self-configuring: to this end, several mechanisms have been proposed (e.g., UPnP, ZeroConf, etc.). In this paper, we focus on IEEE 802.15.4 networks with IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) adaptation layer, where IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is the routing protocol of choice. In this context, we propose a lightweight RPL-based mechanism to Resource Discovery (RD) and Service Discovery (SD), denoted as DiRPL. In particular, DiRPL exploits the RPL handshake to detect new nodes in the network; resources are then simply discovered with a Constrained Application Protocol (CoAP) request and can thus be published in a local resource directory. A very attractive feature of the proposed DiRPL approach is that it builds on well-defined and well-known standard protocols. The performance of the proposed system is investigated with WisMote nodes deployed inside the Cooja simulator, running the Contiki operating system. Practical application scenarios to large-scale smart city monitoring, such as smart lighting and large-scale water consumption monitoring, are investigated.},

note = {Special Issue IoT for Smart Cities},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{monica2018improving,

title = {Improving UWB-Based Localization in IoT Scenarios with Statistical Models of Distance Error},

author = {Stefania Monica and Gianluigi Ferrari},

url = {https://www.mdpi.com/1424-8220/18/5/1592/htm},

doi = {10.3390/s18051592},

year  = {2018},

date = {2018-05-11},

journal = {Sensors},

volume = {18},

number = {5},

pages = {23},

publisher = {Multidisciplinary Digital Publishing Institute},

abstract = {Interest in the Internet of Things (IoT) is rapidly increasing, as the number of connected devices is exponentially growing. One of the application scenarios envisaged for IoT technologies involves indoor localization and context awareness. In this paper, we focus on a localization approach that relies on a particular type of communication technology, namely Ultra Wide Band (UWB). UWB technology is an attractive choice for indoor localization, owing to its high accuracy. Since localization algorithms typically rely on estimated inter-node distances, the goal of this paper is to evaluate the improvement brought by a simple (linear) statistical model of the distance error. On the basis of an extensive experimental measurement campaign, we propose a general analytical framework, based on a Least Square (LS) method, to derive a novel statistical model for the range estimation error between a pair of UWB nodes. The proposed statistical model is then applied to improve the performance of a few illustrative localization algorithms in various realistic scenarios. The obtained experimental results show that the use of the proposed statistical model improves the accuracy of the considered localization algorithms with a reduction of the localization error up to 66%.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nallagonda2018censoring,

title = {Censoring-Based Cooperative Spectrum Sensing with Improved Energy Detectors and Multiple Antennas in Fading Channels},

author = {Srinivas Nallagonda and Sanjay Dhar Roy and Sumit Kundu and Gianluigi Ferrari and Riccardo Raheli},

url = {https://ieeexplore.ieee.org/document/7994707



http://www.tlc.unipr.it/ferrari/Publications/Journals/NaDhKuFeRa_TAES18.pdf},

doi = {10.1109/TAES.2017.2732798},

year  = {2018},

date = {2018-04-02},

journal = {IEEE Transactions on Aerospace and Electronic Systems},

volume = {54},

number = {2},

pages = {537--553},

publisher = {IEEE},

abstract = {In this paper, the performance of cooperative spectrum sensing (CSS) with threshold-based censoring is investigated in the presence of noisy and faded environments. In particular, scenarios with Rayleigh, Hoyt, and Rician fading, affecting both the sensing (S) and reporting (R) channels, are considered. Each secondary user (SU) is equipped with multiple antennas and relies on an improved energy detector (IED).More precisely, the signals from the primary user (PU), received by multiple antennas of an SU, are fed to the IED, the IED outputs are combined using a selection combiner, and the combined signal is used to make a local decision. At the fusion center (FC), censoring of SUs is done on the basis of the quality, evaluated by the FC, of the faded R-channels. The censored decisions received at the FC are fused, using majority logic or maximal ratio combining, to obtain a final decision on the status of the PU. The performance of CSS, in terms of average miss detection probability and error rate, is evaluated considering the impact of relevant network parameters. Optimized values of the censoring threshold, as well as of the required parameters of the IED, are determined under several network conditions. The performance of the proposed IED is compared with that of a conventional energy detector.},

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{IET_StPaFe18,

title = {Impact of on-body IMU placement on inertial navigation},

author = {Nicolò Strozzi and Federico Parisi and Gianluigi Ferrari},

url = {http://ieeexplore.ieee.org/document/8269863/},

doi = {10.1049/iet-wss.2017.0087},

issn = {2043-6394},

year  = {2018},

date = {2018-02-01},

journal = {IET Wireless Sensor Systems - Special Issue on Body Sensor Networks },

volume = {8},

number = {1},

pages = {3-9},

abstract = {Even though technology-aided personal navigation is an extensively studied research topic, approaches based on inertial sensors remain challenging. In this study, the authors present a comparison between different inertial systems, investigating the impacts of on-body placement of Inertial Measurement Units (IMUs) and, consequently, of different algorithms for the estimation of the travelled path on the navigation accuracy. In particular, the system performance is investigated considering two IMU placements: (i) on the feet and (ii) on the lower back. Sensor fusion is then considered in order to take advantage of the strengths of each placement. The results are validated through an extensive data collection in indoor and outdoor environments.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{FrFe_AST18,

title = {Enhancing precision agriculture by Internet of Things and cyber physical systems},

author = {Roberto Fresco and Gianluigi Ferrari},

url = {http://www.tlc.unipr.it/ferrari/Publications/Journals/FrFe_AST18.pdf},

doi = {10.2424/ASTSN.M.2018.8},

year  = {2018},

date = {2018-02-01},

journal = {Atti Soc. Tosc. Sci. Nat., Mem., Supplemento},

volume = {125},

pages = {53-60},

abstract = {The recent advances in Internet of Things (IoT) and the proliferation of sensor platforms have allowed the implementation of different applications used to connect physical devices (Things) to the real world, enabling a multi cross domain and multidisciplinary data exchange.

The agricultural sector is also greatly benefiting from this progress with several advantages, including the optimal management of resources and the improvement of human labour (i.e., crop growth monitoring and selection, irrigation decision support, fertilizers, pesticide and agrochemicals application, etc.). Moreover, advancements in mechanization and GPS-assisted vehicle guidance in agriculture has established the concept of precision agronomy and precision farming, as well as automation in food production chain.

However, current systems still have significant drawbacks in areas such as flexibility, networking, standardization, robustness, skills’ requirements and lack of real time data and actuation. A current trend is based on the interaction of machines and autonomous systems, in order

to fit into cyber-physical production systems and enabling data collection and networked site-specific monitoring and control.

This paper explores all the cutting-edge challenges and solutions required to implement the digital agriculture framework, intended as the evolution from Precision Farming to connected, knowledge-based farm production systems, in a context where digital technologies are first-class elements for the automation of sustainable processes in agriculture.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}