Francesco Beritelli

Automatic monitoring herbage prehensions in grazing cows using audio signals and deep learning techniques

Roberta Avanzato, Ludovica Beritelli, Salvatore Bognanno, Francesco Beritelli et autres

Background Accurate monitoring of feeding behavior in grazing ruminants, particularly the detection of prehension events, is a central challenge for Precision Livestock Farming (PLF). Traditional methods, such as accelerometers, show limitations in the reliable identification of individual events. Acoustic analysis based on …

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Intelligent Video Analysis-Based Pose Recognition and Localization for Improving Dairy Cow Welfare

Roberta Avanzato, Luca Guarnera, Ludovica Beritelli, Valerio Francesco Puglisi et autres

Ensuring the welfare of dairy cows is essential for sustainable and ethical livestock farming. This study presents an integrated system that combines pose recognition and spatial localization to monitor cow behavior in real-time. Using a convolutional neural network (YOLOv11n) trained on a …

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Nash Equilibrium Uniqueness in a Game-Theoretic Power Control Model for Ultra-Dense Wireless Networks

Roberta Avanzato, Francesco Beritelli, Fabio Raciti

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Sound and Video Detection as a Tool to Estimate Free Grazing Behavior in Sheep on Different Swards

Marcella Avondo, Matteo Bognanno, Francesco Beritelli, Roberta Avanzato et autres

The aims of the study were to evaluate the effectiveness of audio detection for identifying feeding sounds in free grazing sheep and to assess whether the recognition of these sounds could be influenced by pasture characteristics. Twelve Valle del Belice dry ewes …

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Deep Learning for Smart Surveillance: Multi-Class Detection of People, Weapons, and Masks using YOLOv11

Ludovica Beritelli, Roberta Avanzato, Luca Guarnera, Francesco Beritelli et autres

Computer vision technologies are revolutionizing the field of security, providing intelligent and automated tools for crime prevention. In this study, we propose an advanced approach for the simultaneous detection of people, weapons, and facial masks in images extracted from surveillance camera video …

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Audio-Based Rainfall Classification Using Spectrograms and YOLOv8n on Embedded Systems

Roberta Avanzato, Ludovica Beritelli, Kevin Munda, Francesco Beritelli

Hydrogeological risks such as floods and landslides increasingly threaten critical infrastructure, emphasizing the need for continuous and reliable rainfall monitoring. Traditional sensing approaches often face limitations in spatial resolution, latency, and installation cost. This paper presents an audio-based rainfall classification system using …

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Sky Classification Using CNNs for Meteorological Condition Detection

Ludovica Beritelli, Roberta Avanzato, Omar Abdelaziz, Kevin Munda et autres

Sky image classification under different meteorological conditions is crucial for numerous applications, including environmental monitoring and weather forecasting. In this work, we propose a Convolutional Neural Network (CNN)-based approach to classify sky images into four categories: “Day-clear”, “Day-cloudy”, “Nigh-clear”, and “Night-cloudy”. Several …

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A deep reinforcement learning-based UAV-smallcell system for mobile terminals geolocalization in disaster scenarios

Roberta Avanzato, Francesco Beritelli, Raoul Raftopoulos, Giovanni Schembra

Deep reinforcement learning (DRL) techniques have the potential to significantly improve the ability of Unmanned Aerial Vehicles (UAVs) for mobile device localization in disaster scenarios by optimizing flight paths and enhancing signal detection accuracy using Reference Signal Received Power (RSRP) measurements. DRL …

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Robust Biometric Verification Using Phonocardiogram Fingerprinting and a Multilayer-Perceptron-Based Classifier

Roberta Avanzato, Francesco Beritelli, Salvatore Serrano

Recently, a new set of biometric traits, called medical biometrics, have been explored for human identity verification. This study introduces a novel framework for recognizing human identity through heart sound signals, commonly referred to as phonocardiograms (PCGs). The framework is built on …

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Impact of Rain on Frequency Bands in 4G/5G Networks: Implications for Industrial Connectivity

Roberta Avanzato, Francesco Beritelli, Maria Grazia Borzì

In recent years, there has been a growing interest in understanding how rain affects frequency bands in 4G/5G networks, especially in outdoor industrial environments. Most studies focus on the use of frequencies above 10 GHz, while few address this issue using frequencies …

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A Game Theory-Based Flight Strategy to Energy Efficient UAV-Femtocell Geolocation Systems

Roberta Avanzato, Francesco Beritelli, Fabio Raciti, Enrica Spataro

Unmanned aerial vehicle (UAV)-femtocell systems have been a paragon solution to the challenge of geolocating missing persons in civil protection (e.g., post-earthquake) scenarios. Bearing in mind the limited energy capacity on board a drone, it is extremely critical to provide advanced green …

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Lung-DT: An AI-Powered Digital Twin Framework for Thoracic Health Monitoring and Diagnosis

Roberta Avanzato, Francesco Beritelli, Alfio Lombardo, Carmelo Ricci

The integration of artificial intelligence (AI) with Digital Twins (DTs) has emerged as a promising approach to revolutionize healthcare, particularly in terms of diagnosis and management of thoracic disorders. This study proposes a comprehensive framework, named Lung-DT, which leverages IoT sensors and …

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