•  24
    Detection of forest fires outbreaks by dynamic fuzzy logic controller
    with Josué Toledo-Castro, Nayra Rodríguez-Pérez, Pino Caballero-Gil, Candelaria Hernández-Goya, and Ricardo Aguasca-Colomo
    Logic Journal of the IGPL. forthcoming.
    The use of wireless sensor networks and the Internet of things to detect forest fire outbreaks may help to reduce the response time and avoid natural disasters. This work proposes the deployment of WSN to enhance the real-time monitoring of dynamic variables such as polluting gases, temperature or the presence of fire flames by infrared. In addition, the activation of forest fire alerts if environmental status may involve evidence of a recent fire outbreak. A fuzzy-based controller is implemente…Read more
  •  25
    Proposal of an Adaptive Neurofuzzy System to Control Flow Power in Distributed Generation Systems
    with Helbert Eduardo Espitia, Hilario López-García, and Guzmán Díaz
    Complexity 2019 1-16. 2019.
  •  80
    Forest Fire Prevention, Detection, and Fighting Based on Fuzzy Logic and Wireless Sensor Networks
    with Josué Toledo-Castro, Pino Caballero-Gil, Nayra Rodríguez-Pérez, Candelaria Hernández-Goya, and Ricardo Aguasca-Colomo
    Complexity 2018 1-17. 2018.
    Huge losses and serious threats to ecosystems are common consequences of forest fires. This work describes a forest fire controller based on fuzzy logic and decision-making methods aiming at enhancing forest fire prevention, detection, and fighting systems. In the proposal, the environmental monitoring of several dynamic risk factors is performed with wireless sensor networks and analysed with the proposed fuzzy-based controller. With respect to this, meteorological variables, polluting gases an…Read more
  •  16
    Filling Control of a Conical Tank Using a Compact Neuro-Fuzzy Adaptive Control System
    with Helbert Espitia-Cuchango and Hilario López-García
    Complexity 2022 1-17. 2022.
    This document describes the implementation of a conical tank control system using an adaptive neurofuzzy system. For implementation, an indirect approach is used where the controller is optimized using the model obtained during the plant identification carried out using data obtained during the system operation. Furthermore, implementation includes training of neuro fuzzy-systems and application to control a conical tank. Regarding plant identification, preliminary training takes place using dat…Read more