A
Andrea Sciarrone
Researcher at University of Genoa
Publications - 67
Citations - 1468
Andrea Sciarrone is an academic researcher from University of Genoa. The author has contributed to research in topics: Mobile device & Microwave imaging. The author has an hindex of 19, co-authored 60 publications receiving 1066 citations.
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Enabling IoT for In-Home Rehabilitation: Accelerometer Signals Classification Methods for Activity and Movement Recognition
TL;DR: This paper surveys and compares accelerometer signals classification methods to enable IoT for rehabilitation and elderly monitoring for active aging and considers two functions useful for such treatments: activity recognition and movement recognition.
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Blind Detection: Advanced Techniques for WiFi-Based Drone Surveillance
TL;DR: This paper proposes a WiFi statistical fingerprint-based drone detection approach, which is capable of identifying nearby drone threats, even in the presence of malicious attacks.
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Unauthorized Amateur UAV Detection Based on WiFi Statistical Fingerprint Analysis
TL;DR: A WiFi-based approach aimed at detecting nearby aerial or terrestrial devices by performing statistical fingerprint analysis on wireless traffic is proposed, able to efficiently detect and identify intruder drones in all the considered experimental setups, making it a promising unmanned aerial vehicle detection approach in the framework of amateur drone surveillance.
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A Trainingless WiFi Fingerprint Positioning Approach Over Mobile Devices
Igor Bisio,Matteo Cerruti,Fabio Lavagetto,Mario Marchese,Matteo Pastorino,Andrea Randazzo,Andrea Sciarrone +6 more
TL;DR: A novel approach, where the training data are obtained by means of finite-difference time-domain (FDTD) simulations of the electromagnetic propagation in the considered scenario, is presented and the performances of the method are assessed by Means of experimental results in a real scenario.
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Gender-Driven Emotion Recognition Through Speech Signals For Ambient Intelligence Applications
TL;DR: The results highlight that the a priori knowledge of the speaker's gender allows a performance increase, and that the features selection adoption assures a satisfying recognition rate and allows reducing the employed features.