Diagnosis automática con 5G para entornos de emergencia
| dc.centro | E.T.S.I. Telecomunicación | es_ES |
| dc.contributor.author | Trujillo, José Antonio | |
| dc.contributor.author | De la Bandera Cascales, Isabel | |
| dc.contributor.author | Barco-Moreno, Raquel | |
| dc.date.accessioned | 2023-09-22T08:35:43Z | |
| dc.date.available | 2023-09-22T08:35:43Z | |
| dc.date.created | 2023-09 | |
| dc.date.issued | 2023 | |
| dc.departamento | Ingeniería de Comunicaciones | |
| dc.description.abstract | Emergency communications are a fundamental aspect for any community, becoming more necessary year after year. This fact, together with the continuous advance of mobile network technologies, enables increasingly more reliable and faster communications in critical situations. The aim of this work is to provide a diagnostic system to detect the specific failures that occur in a mobile network in an emergency situation. In the same way, the proposed methodology is also capable of providing the most suitable solution to mitigate the effects that the disaster or emergency has caused in the network. | es_ES |
| dc.description.sponsorship | Este trabajo ha sido financiado parcialmente por la Unión Europea en el marco del proyecto ’Massive AI for the Open Radio beyond 5G/6G (MAORI)’ de la Next Generation EU, .También parcialmente financiado a través del II Plan Propio de Investigación y Transferencia de la Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech. | es_ES |
| dc.identifier.uri | https://hdl.handle.net/10630/27640 | |
| dc.language.iso | eng | es_ES |
| dc.relation.eventdate | 13/09/2023 | es_ES |
| dc.relation.eventplace | Cáceres | es_ES |
| dc.relation.eventtitle | XXXVIII Simposio Nacional de la Unión Científica Internacional de Radio (URSI 2023) | es_ES |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
| dc.rights.accessRights | open access | es_ES |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
| dc.subject | Telecomunicaciones | es_ES |
| dc.subject | Sistemas de comunicaciones móviles | es_ES |
| dc.subject.other | Self-Organizing Networks | es_ES |
| dc.subject.other | Mobile Communications | es_ES |
| dc.subject.other | Emergency situations | es_ES |
| dc.subject.other | Machine learning | es_ES |
| dc.title | Diagnosis automática con 5G para entornos de emergencia | es_ES |
| dc.type | conference output | es_ES |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | c933e578-ad80-410f-88c2-f0dbdaa6cf72 | |
| relation.isAuthorOfPublication.latestForDiscovery | c933e578-ad80-410f-88c2-f0dbdaa6cf72 |
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