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Amirhossein Moallemi

Dottorando

Dipartimento di Ingegneria dell'Energia Elettrica e dell'Informazione "Guglielmo Marconi"

Settore scientifico disciplinare: ING-INF/01 ELETTRONICA

Pubblicazioni

Tommaso Polonelli; Amirhossein Moallemi; Weikang Kong; Hanna Müller; Julien Deparday; Michele Magno; Luca Benini, A Self-Sustainable and Micro-Second Time Synchronized Multi-Node Wireless System for Aerodynamic Monitoring on Wind Turbines, «IEEE ACCESS», 2023, 11, Article number: 10295442, pp. 119506 - 119522 [articolo]Open Access

Moallemi, A; Gaspari, R; Zonzini, F; De Marchi, L; Brunelli, D; Benini, L, Speeding up System Identification Algorithms on a Parallel RISC-V MCU for Fast Near-Sensor Vibration Diagnostic, «IEEE SENSORS LETTERS», 2023, 7, Article number: 10210513, pp. 1 - 4 [articolo]

MOALLEMI, AMIRHOSSEIN; ZANATTA, LUCA; BURRELLO, ALESSIO; SALVARO, MATTIA; LONGO, MONICA; DARO, PAOLA; BARCHI, FRANCESCO; BRUNELLI, DAVIDE; BENINI, LUCA; ACQUAVIVA, ANDREA, UNSUPERVISED VEHICLE CLASSIFICATION USING A STRUCTURAL HEALTH MONITORING SYSTEM, in: STRUCTURAL HEALTH MONITORING 2023, 2023, pp. 1069 - 1076 (atti di: 14th international workshop on structural health monitoring, Stanford, California, 12-14th of September 2023) [Contributo in Atti di convegno]

Amirhossein Moallemi; Alessio Burrello; Davide Brunelli; Luca Benini, Exploring Scalable, Distributed Real-Time Anomaly Detection for Bridge Health Monitoring, «IEEE INTERNET OF THINGS JOURNAL», 2022, 9, Article number: 9729869, pp. 17660 - 17674 [articolo]

Parisi, E; Moallemi, A; Barchi, F; Bartolini, A; Brunelli, D; Buratti, N; Acquaviva, A, Time and Frequency Domain Assessment of Low-Power MEMS Accelerometers for Structural Health Monitoring, in: 2022 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT), 345 E 47TH ST, NEW YORK, NY 10017 USA, IEEE, 2022, pp. 234 - 239 (atti di: Metrology for Industry 4.0 & IoT, Trento, Italy, 7-9 - June - 2022) [Contributo in Atti di convegno]

Moallemi A.; Burrello A.; Brunelli D.; Benini L., Model-based vs. Data-driven Approaches for Anomaly Detection in Structural Health Monitoring: A Case Study, in: Conference Record - IEEE Instrumentation and Measurement Technology Conference, Institute of Electrical and Electronics Engineers Inc., «CONFERENCE PROCEEDINGS - IEEE INSTRUMENTATION/MEASUREMENT TECHNOLOGY CONFERENCE», 2021, 2021-, pp. 1 - 6 (atti di: 2021 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2021, Technology and Innovation Centre (TIC), gbr, 2021) [Contributo in Atti di convegno]

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