Contributo in atti di convegno, 2022, ENG, 10.1109/PerComWorkshops53856.2022.9767501
De Caro V.; Bano S.; MacHumilane A.; Gotta A.; Cassarà P.; Carta A.; Semola R.; Sardianos C.; Chronis C.; Varlamis I.; Tserpes K.; Lomonaco V.; Gallicchio C.; Bacciu D.
Department of Computer Science, University of Pisa, Pisa, Italy; Department of Information Engineering, University of Pisa and CNR-ISTI, Pisa, Italy; Department of Information Engineering, University of Pisa and CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; Department of Computer Science, University of Pisa, Pisa, Italy; Department of Computer Science, University of Pisa, Pisa, Italy; Harokopio University of Athens, Athens, Greece; Harokopio University of Athens, Athens, Greece; Harokopio University of Athens, Athens, Greece; Harokopio University of Athens, Athens, Greece; Department of Computer Science, University of Pisa, Pisa, Italy; Department of Computer Science, University of Pisa, Pisa, Italy; Department of Computer Science, University of Pisa, Pisa, Italy
This paper presents a proof-of-concept implementation of the AI-as-a-Service toolkit developed within the H2020 TEACHING project and designed to implement an autonomous driving personalization system according to the output of an automatic driver's stress recognition algorithm, both of them realizing a Cyber-Physical System of Systems. In addition, we implemented a data-gathering subsystem to collect data from different sensors, i.e., wearables and cameras, to automatize stress recognition. The system was attached for testing to a driving emulation software, CARLA, which allows testing the approach's feasibility with minimum cost and without putting at risk drivers and passengers. At the core of the relative subsystems, different learning algorithms were implemented using Deep Neural Networks, Recurrent Neural Networks, and Reinforcement Learning.
PerCom Workshops - 2022 IEEE International Conference on Pervasive Computing and Communications, pp. 91–93, Pisa, Italy, 21-25 March 2022
AI-as-a-Service, Autonomous driving, Human state monitoring, Recurrent neural networks
Machumilane Achilles, Bano Saira, Gotta Alberto, Cassara Pietro
ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"
ID: 471820
Year: 2022
Type: Contributo in atti di convegno
Creation: 2022-10-07 17:47:03.000
Last update: 2022-12-14 11:52:28.000
External links
OAI-PMH: Dublin Core
OAI-PMH: Mods
OAI-PMH: RDF
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:471820
DOI: 10.1109/PerComWorkshops53856.2022.9767501
Scopus: 2-s2.0-85130602084
ISI Web of Science (WOS): 000821801200025