A step to smart fishways: An autonomous obstruction detection system using hydraulic modeling and sensor networks
2021
Fuentes Pérez, Juan Francisco | García Vega, Ana | Bravo Cordoba, Francisco Javier | Sanz Ronda, Francisco Javier
Producción Científica
Показать больше [+] Меньше [-]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.
Показать больше [+] Меньше [-]European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Smart fishways—grant agreement n° 101032024)
Показать больше [+] Меньше [-]Ключевые слова АГРОВОК
Библиографическая информация
Эту запись предоставил Universidad de Valladolid