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

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dc.contributor.authorAlessandro Sebastianelli
dc.contributor.authorFrancesco Mauro
dc.contributor.authorGianluca Di Cosmo
dc.contributor.authorFabrizio Passarini
dc.contributor.authorMarco Carminati
dc.contributor.authorSilvia Liberata Ullo
dc.date.accessioned2025-05-14T12:04:59Z
dc.date.available2025-05-14T12:04:59Z
dc.identifier.urihttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/19924
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc550
dc.titleAIRSENSE-TO-ACT: A Concept Paper for COVID-19 Countermeasures Based on Artificial Intelligence Algorithms and Multi-Source Data Processing
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relation.isDatasetOfDistribution.latestForDiscovery4be423b2-b655-4682-849d-9632b9293374

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