COVID19-Routes: A Safe Pedestrian Navigation Service
COVID-19 has become a global pandemic during 2020 due to its high contagiousness and the high mobility of the world’s population today. In just one year, this virus has caused millions of infections and deaths worldwide. These numbers will continue to grow until the population becomes imm...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9466116/ |
| _version_ | 1818740991319867392 |
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| author | Ruben Cantarero Ana Rubio Maria Jose Santofimia Romero Javier Dorado Jesus Fernandez Juan C. Lopez |
| author_facet | Ruben Cantarero Ana Rubio Maria Jose Santofimia Romero Javier Dorado Jesus Fernandez Juan C. Lopez |
| author_sort | Ruben Cantarero |
| collection | DOAJ |
| description | COVID-19 has become a global pandemic during 2020 due to its high contagiousness and the high mobility of the world’s population today. In just one year, this virus has caused millions of infections and deaths worldwide. These numbers will continue to grow until the population becomes immune to the virus thanks to an effective vaccine. Until this is possible, the only viable strategy is to try to stop its expansion through preventive measures such as limiting mobility, the use of masks, etc. In order to support these measures, this article presents a service to provide safe navigation solutions to reduce the likelihood of infection by avoiding potential conflict areas in the city. To identify these hotspots, a strategy that combines a rule-based system and a common-sense knowledge base is proposed. Through this strategy, an occupation model and a danger model are inferred. This requires the prior capture of knowledge about the general functioning of the city, its inhabitants and the virus. The proposed service makes decisions from these two models. Finally, a validation process has been carried out through surveys to evaluate the proposed solution. Obtained results demonstrate the potential of the proposed solution as a tool to identify safe routes that allow citizens to move around the city with low exposure to COVID-19. |
| first_indexed | 2024-12-18T01:49:31Z |
| format | Article |
| id | doaj.art-aba14542d24f44b78b8f845bc7aa741d |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-18T01:49:31Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-aba14542d24f44b78b8f845bc7aa741d2022-12-21T21:25:05ZengIEEEIEEE Access2169-35362021-01-019934339344910.1109/ACCESS.2021.30929709466116COVID19-Routes: A Safe Pedestrian Navigation ServiceRuben Cantarero0https://orcid.org/0000-0003-2893-0392Ana Rubio1https://orcid.org/0000-0003-0343-8596Maria Jose Santofimia Romero2https://orcid.org/0000-0001-6132-1199Javier Dorado3https://orcid.org/0000-0003-4700-5557Jesus Fernandez4https://orcid.org/0000-0002-4177-4526Juan C. Lopez5https://orcid.org/0000-0002-7372-1568Computer Architecture and Networks Group, School of Computer Science of Ciudad Real, University of Castilla-La Mancha, Ciudad Real, SpainComputer Architecture and Networks Group, School of Computer Science of Ciudad Real, University of Castilla-La Mancha, Ciudad Real, SpainComputer Architecture and Networks Group, School of Computer Science of Ciudad Real, University of Castilla-La Mancha, Ciudad Real, SpainComputer Architecture and Networks Group, School of Computer Science of Ciudad Real, University of Castilla-La Mancha, Ciudad Real, SpainComputer Architecture and Networks Group, School of Computer Science of Ciudad Real, University of Castilla-La Mancha, Ciudad Real, SpainComputer Architecture and Networks Group, School of Computer Science of Ciudad Real, University of Castilla-La Mancha, Ciudad Real, SpainCOVID-19 has become a global pandemic during 2020 due to its high contagiousness and the high mobility of the world’s population today. In just one year, this virus has caused millions of infections and deaths worldwide. These numbers will continue to grow until the population becomes immune to the virus thanks to an effective vaccine. Until this is possible, the only viable strategy is to try to stop its expansion through preventive measures such as limiting mobility, the use of masks, etc. In order to support these measures, this article presents a service to provide safe navigation solutions to reduce the likelihood of infection by avoiding potential conflict areas in the city. To identify these hotspots, a strategy that combines a rule-based system and a common-sense knowledge base is proposed. Through this strategy, an occupation model and a danger model are inferred. This requires the prior capture of knowledge about the general functioning of the city, its inhabitants and the virus. The proposed service makes decisions from these two models. Finally, a validation process has been carried out through surveys to evaluate the proposed solution. Obtained results demonstrate the potential of the proposed solution as a tool to identify safe routes that allow citizens to move around the city with low exposure to COVID-19.https://ieeexplore.ieee.org/document/9466116/Commonsense knowledgecovid-19rule-based systemssmart city |
| spellingShingle | Ruben Cantarero Ana Rubio Maria Jose Santofimia Romero Javier Dorado Jesus Fernandez Juan C. Lopez COVID19-Routes: A Safe Pedestrian Navigation Service IEEE Access Commonsense knowledge covid-19 rule-based systems smart city |
| title | COVID19-Routes: A Safe Pedestrian Navigation Service |
| title_full | COVID19-Routes: A Safe Pedestrian Navigation Service |
| title_fullStr | COVID19-Routes: A Safe Pedestrian Navigation Service |
| title_full_unstemmed | COVID19-Routes: A Safe Pedestrian Navigation Service |
| title_short | COVID19-Routes: A Safe Pedestrian Navigation Service |
| title_sort | covid19 routes a safe pedestrian navigation service |
| topic | Commonsense knowledge covid-19 rule-based systems smart city |
| url | https://ieeexplore.ieee.org/document/9466116/ |
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