Application of teams of usvs for cyanobacteria monitoring: initial steps
dc.contributor.author | Girón Sierra, José María Ricardo | |
dc.contributor.author | Chacón Sombría, Jesús | |
dc.date.accessioned | 2023-06-17T09:18:06Z | |
dc.date.available | 2023-06-17T09:18:06Z | |
dc.date.issued | 2021 | |
dc.description | ©2021 The Authors. The authors wish to thank the support of the Spanish MCINN Retos Project RTI 2018-098962-B-C21. | |
dc.description.abstract | Reservoirs and other water masses could suffer dangerous situations because cyanobacteria blooms. It is convenient for public safety, and for research purposes, to be able to detect the presence of this bacterium in the water, and to monitor its evolution along time. When possible, it would be useful to predict a bloom in the near future. And, in case of having a bloom, it would be relevant to have an eye on its dynamics Our research proposes the use of a specialized team of USVs for these objectives. A series of initial steps has been accomplished, for having microbiology experts on board, and for developing strategies and infrastructure for this project. Standard lawn-mower procedures were precluded: it is more a scenario for intelligent methods, based on models and data-driven explorations of water masses. Some studies in simulation, and experiments with USVs have been initiated. | |
dc.description.department | Sección Deptal. de Arquitectura de Computadores y Automática (Físicas) | |
dc.description.faculty | Fac. de Ciencias Físicas | |
dc.description.refereed | TRUE | |
dc.description.sponsorship | Ministerio de Cienncia e Innovación (MICINN) | |
dc.description.status | pub | |
dc.eprint.id | https://eprints.ucm.es/id/eprint/69043 | |
dc.identifier.doi | 10.1016/j.ifacol.2021.10.125 | |
dc.identifier.issn | 2405-8963 | |
dc.identifier.officialurl | http://dx.doi.org/10.1016/j.ifacol.2021.10.125 | |
dc.identifier.relatedurl | https://www.sciencedirect.com/ | |
dc.identifier.uri | https://hdl.handle.net/20.500.14352/8562 | |
dc.issue.number | 16 | |
dc.journal.title | IFAC papersonline | |
dc.language.iso | eng | |
dc.page.final | 421 | |
dc.page.initial | 416 | |
dc.publisher | Elsevier | |
dc.relation.projectID | RTI 2018-098962-B-C21 | |
dc.rights | Atribución-NoComercial-SinDerivadas 3.0 España | |
dc.rights.accessRights | open access | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/es/ | |
dc.subject.cdu | 004.8 | |
dc.subject.keyword | Water pollution | |
dc.subject.keyword | Autonomous surface vehicles | |
dc.subject.keyword | Cyanobacteria | |
dc.subject.keyword | Robot teams | |
dc.subject.keyword | Environmental monitoring | |
dc.subject.ucm | Inteligencia artificial (Informática) | |
dc.subject.unesco | 1203.04 Inteligencia Artificial | |
dc.title | Application of teams of usvs for cyanobacteria monitoring: initial steps | |
dc.type | journal article | |
dc.volume.number | 54 | |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | 528ed45e-3f1d-488d-a0e4-0ed88ca2370e | |
relation.isAuthorOfPublication | e987dc75-a909-418c-93a6-23ad9eb40ce6 | |
relation.isAuthorOfPublication.latestForDiscovery | e987dc75-a909-418c-93a6-23ad9eb40ce6 |
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