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dc.contributor.authorNieto-Chaupis, Huber
dc.date.accessioned2022-04-29T22:15:41Z
dc.date.available2022-04-29T22:15:41Z
dc.date.issued2021-11
dc.identifier.citationNieto-Chaupis, H. (2021). Software Engineering For Estimation of Social Distancing in Pandemic Times. In 2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) (pp. 21-24). IEEE.es_PE
dc.identifier.isbn978-1-6654-0403-7
dc.identifier.issn2693-8421
dc.identifier.urihttps://hdl.handle.net/20.500.13067/1819
dc.description.abstractThis paper present a model of software engineering to estimate the social distancing with realistic inputs. This might be incorporated in a smart-phone application in order to get an exact estimate of the values of social distancing in times of global pandemic. Attention is paid on the measurement of outdoor scenarios where wind velocity would play an important role to move the aerosols at distances beyond the known social distances. Thus, the dehydration time emerges also as a predictor of risk to get the infection of virus. The proposed software has capabilities to yield numeric values of risk in terms of probabilities. It is expected that once the associated computational program is running then the permanent assessment of potential scenarios would give concrete values of social distancing. In this manner one expects that these values are uploaded at an Internet network.es_PE
dc.formatapplication/pdfes_PE
dc.language.isoenges_PE
dc.publisherInstitute of Electrical and Electronics Engineerses_PE
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_PE
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/es_PE
dc.sourceAUTONOMAes_PE
dc.subjectCodeses_PE
dc.subjectPandemicses_PE
dc.subjectWind speedes_PE
dc.subjectHuman factorses_PE
dc.subjectSocial factorses_PE
dc.subjectSoftwarees_PE
dc.subjectVelocity measurementes_PE
dc.titleSoftware Engineering For Estimation of Social Distancing in Pandemic Timeses_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.identifier.journal2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)es_PE
dc.identifier.doihttps://doi.org/10.1109/SNPD51163.2021.9704913
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.02.04es_PE
dc.publisher.countryPEes_PE
dc.relation.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85125730351&doi=10.1109%2fSNPD51163.2021.9704913&partnerID=40es_PE
dc.source.beginpage21es_PE
dc.source.endpage24es_PE


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