Tecnologías habilitadoras para automatizar la monitorización de blooms de cianobacterias

  1. Besada-Portas, Eva 1
  2. Risco-Martín, José Luis 1
  3. Esteban San Roman, Segundo 1
  4. Girón-Sierra, José María 1
  5. Pajares, Gonzalo 1
  6. López-Orozco, José Antonio 1
  1. 1 Universidad Complutense de Madrid
    info

    Universidad Complutense de Madrid

    Madrid, España

    ROR 02p0gd045

Libro:
XLIV Jornadas de Automática: libro de actas: Universidad de Zaragoza, Escuela de Ingeniería y Arquitectura, 6, 7 y 8 de septiembre de 2023, Zaragoza
  1. Ramón Costa Castelló (coord.)
  2. Manuel Gil Ortega (coord.)
  3. Óscar Reinoso García (coord.)
  4. Luis Enrique Montano Gella (coord.)
  5. Carlos Vilas Fernández (coord.)
  6. Elisabet Estévez Estévez (coord.)
  7. Eduardo Rocón de Lima (coord.)
  8. David Muñoz de la Peña Sequedo (coord.)
  9. José Manuel Andújar Márquez (coord.)
  10. Luis Payá Castelló (coord.)
  11. Alejandro Mosteo Chagoyen (coord.)
  12. Raúl Marín Prades (coord.)
  13. Vanesa Loureiro-Vázquez (coord.)
  14. Pedro Jesús Cabrera Santana (coord.)

Editorial: Servizo de Publicacións ; Universidade da Coruña

ISBN: 9788497498609

Ano de publicación: 2023

Páxinas: 6-11

Congreso: Jornadas de Automática (44. 2023. Zaragoza)

Tipo: Achega congreso

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Resumo

Cyanobacterial blooms are dynamic biological processes, dangerous for inhabitants and users of water resources, as they reduce the oxygen and light reach in water bodies, and can produce highly harmful toxins. Automatic monitoring and prediction of the blooms can enable authorities to detect them and anticipate their decisions to mitigate the risks that they pose. The use of technologies such as Modeling & Simulation, intelligent Autonomous Surface Vehicles, Internet of Things with edge computing, Digital Twins and Artificial Intelligence facilitates monitoring, prediction and knowledge-based management of the real situation of water bodies. This article presents different advances and research projects in these fields by the Systems Engineering, Control, Automation and Robotics group of the Complutense University of Madrid.

Fonte de datos: Dialnet