Dottorando in Ingegneria Aerospaziale , 37o ciclo (2021-2024)
Dipartimento di Ingegneria Meccanica e Aerospaziale (DIMEAS)
Dottorato di ricerca
Argomento di ricerca
Stress e carico cognitivo in aviazione: sviluppo di un sistema real-time di monitoraggio di piloti
Interessi di ricerca
He obtained his bachelor’s and master’s degree in aerospace engineering, both cum laude at the Politecnico di Torino, specializing in Aeromechanics and Systems. He also followed the master’s double degree program “Alta Scuola Politecnica” together with the Politecnico di Milano.
His research interest is related to human factors applied to the Human-Machine Interaction systems (HMI) in the aeronautical field, especially in an optic of a possible future transition towards the so-called Single Pilot Operations (SPOs).
In particular, he is studying the relationship between the variation of pilots’ physiological signals and their stress and mental workload levels. His research project aims to develop an AI-based predictive model that can infer the real-time pilot physical and cognitive state of health starting from a physiological multimodal approach.
Gabriele Luzzani also collaborates with the startup Pipein as a project consultant.
Premi e riconoscimenti
- Gabriele Luzzani's PhD research project, "Study and development of a real-time pilot monitoring system," has been awarded by the EASA - European Union Aviation Safety Agency at the first edition of the European_Academia@EASA_conference 2023. EASA recognised the quality and pertinence of his work in applying AI to the current challenges and novel technologies that lie ahead for aviation. (2023)
Gruppi di ricerca
Pubblicazioni più recenti Vedi tutte le pubblicazioni su Porto@Iris
- Luzzani, G.; Buraioli, I.; Demarchi, D.; Guglieri, G. (2023)
A review of physiological measures for mental workload assessment in aviation. In: THE AERONAUTICAL JOURNAL, pp. 1-22. ISSN 0001-9240
Contributo su Rivista
- Giglio, Enrico; Luzzani, Gabriele; Terranova, Vito; Trivigno, Gabriele; Niccolai, ... (2023)
An Efficient Artificial Intelligence Energy Management System for Urban Building Integrating Photovoltaic and Storage. In: IEEE ACCESS, vol. 11, pp. 18673-18688. ISSN 2169-3536
Contributo su Rivista
- Borretta, Eloisa; Giglio, Enrico; Luzzani, Gabriele; Terranova, Vito; Trivigno, ... (2021)
Software-based solutions for the optimization of a building electric bill using integrated PV and storage systems: a case study. In: 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe, pp. 1-6. ISBN: 978-1-6654-3613-7
Contributo in Atti di Convegno (Proceeding)