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 08-jul-2024