AIRSENSE-TO-ACT: A Concept Paper for COVID-19 Countermeasures Based on Artificial Intelligence Algorithms and Multi-Source Data Processing

Description

Toolbox-ID

jz000145-0034

Identifier(s)

https://tustorage.ulb.tu-darmstadt.de/handle/tustorage/19922

Publisher

MDPI AG

License

https://creativecommons.org/licenses/by/4.0/

Subject(s)

DDC(s)

550

Distribution(s)

Distribution
AIRSENSE-TO-ACT: A Concept Paper for COVID-19 Countermeasures Based on Artificial Intelligence Algorithms and Multi-Source Data Processing
Alessandro Sebastianelli; Francesco Mauro; Gianluca Di Cosmo; Fabrizio Passarini; Marco Carminati; Silvia Liberata Ullo
Distribution
AIRSENSE-TO-ACT: A Concept Paper for COVID-19 Countermeasures Based on Artificial Intelligence Algorithms and Multi-Source Data Processing
Alessandro Sebastianelli; Francesco Mauro; Gianluca Di Cosmo; Fabrizio Passarini; Marco Carminati; Silvia Liberata Ullo