RT info:eu-repo/semantics/article
T1 A step to smart fishways: An autonomous obstruction detection system using hydraulic modeling and sensor networks
A1 Fuentes Pérez, Juan Francisco
A1 García Vega, Ana
A1 Bravo Córdoba, Francisco Javier
A1 Sanz Ronda, Francisco Javier
K1 Piscicultura
K1 Cursos de Agua
K1 Water-level sensors
K1 Hydraulic modeling
K1 Fishways
K1 Sensores de nivel de agua
K1 Modelado hidráulico
K1 Escalas de peces
K1 3105.04 Protección de Los Peces
K1 3199 Otras Especialidades Agrarias
AB Stepped fishways are structures that allow the free movement of fish in transversal obstacles in rivers. However, the lack of or incorrect maintenance may deviate them from this objective. To handle this problem, this research work presents a novel low-cost sensor network that combines fishway hydraulics with neural networks programmed in Python (Keras + TensorFlow), generating the first autonomous obstruction/malfunction detection system for stepped fishways. The system is based on a network of custom-made ultrasonic water level nodes that transmit data and alarms remotely and in real-time. Its performance was assessed in a field study case as well as offline, considering the influence of the number of sensing nodes and obstruction dimensions. Results show that the proposed system can detect malfunctions and that allows monitoring of the hydraulic performance of the fishway. Consequently, it optimizes the timing of maintenance on fishways and, thus, has the potential of automatizing and reducing the cost of these operations as well as augmenting the service of these structures. Therefore, this novel tool is a step forward to achieve smart fishway management and to increase their operability.
PB MDPI
YR 2021
FD 2021
LK https://uvadoc.uva.es/handle/10324/59416
UL https://uvadoc.uva.es/handle/10324/59416
LA eng
NO Sensors, 2021, vol. 21, n. 20, 6909
NO Producción Científica
DS UVaDOC
RD 16-jul-2024