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

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datacite.relatedItem.firstPage34
datacite.relatedItem.issue1
datacite.relatedItem.relatedIdentifierTypeISSN
datacite.relatedItem.relatedItemIdentifier2220-9964
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datacite.relatedItem.titleIJGI
datacite.relatedItem.volume10
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.accessioned2025-05-14T12:04:58Z
dc.date.available2025-05-14T12:04:58Z
dc.date.issued2021
dc.identifier.doihttps://doi.org/10.3390/ijgi10010034
dc.identifier.otherjz000145-0034
dc.identifier.urihttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/19922
dc.publisherMDPI AG
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
dc.typeArticle
dcat.distribution.pdfhttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/19923
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