dc.contributor.author | Nieto-Chaupis, Huber | |
dc.date.accessioned | 2022-04-29T22:15:41Z | |
dc.date.available | 2022-04-29T22:15:41Z | |
dc.date.issued | 2021-11 | |
dc.identifier.citation | Nieto-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.isbn | 978-1-6654-0403-7 | |
dc.identifier.issn | 2693-8421 | |
dc.identifier.uri | https://hdl.handle.net/20.500.13067/1819 | |
dc.description.abstract | This 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.format | application/pdf | es_PE |
dc.language.iso | eng | es_PE |
dc.publisher | Institute of Electrical and Electronics Engineers | es_PE |
dc.rights | info:eu-repo/semantics/restrictedAccess | es_PE |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | es_PE |
dc.source | AUTONOMA | es_PE |
dc.subject | Codes | es_PE |
dc.subject | Pandemics | es_PE |
dc.subject | Wind speed | es_PE |
dc.subject | Human factors | es_PE |
dc.subject | Social factors | es_PE |
dc.subject | Software | es_PE |
dc.subject | Velocity measurement | es_PE |
dc.title | Software Engineering For Estimation of Social Distancing in Pandemic Times | es_PE |
dc.type | info:eu-repo/semantics/article | es_PE |
dc.identifier.journal | 2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) | es_PE |
dc.identifier.doi | https://doi.org/10.1109/SNPD51163.2021.9704913 | |
dc.subject.ocde | https://purl.org/pe-repo/ocde/ford#2.02.04 | es_PE |
dc.publisher.country | PE | es_PE |
dc.relation.url | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125730351&doi=10.1109%2fSNPD51163.2021.9704913&partnerID=40 | es_PE |
dc.source.beginpage | 21 | es_PE |
dc.source.endpage | 24 | es_PE |