TP37 - Tracking Fish Trajectories through Dynamic Pressure Signals: A Dual-Sensor System for Hydrodynamic Cues Monitoring

Accurate characterization of hydrodynamic cues produced during fish locomotion is essential for understanding behavioral dynamics.In this work, a novel pressure sensor system is presented to isolate the dynamic pressure components associated with fish movements, while compensating for wave induced p ressure.The system combines a differential pressure sensor and a water level sensor.Its accuracy has been demonstrated through experimental validation against a classical potential flow model around a cylinder, confirming the robustness and effectiveness of the proposed approach.

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Published
2025-01-01
DOI
https://doi.org/10.5162/eurosensors2025/tp37
Primary Topic
Water Quality Monitoring Technologies
Type
article
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article

TP37 - Tracking Fish Trajectories through Dynamic Pressure Signals: A Dual-Sensor System for Hydrodynamic Cues Monitoring

Gurvan Jodin, Florence Razan, Bastien Lagneaux, Corentin Porcon
Water Quality Monitoring Technologies
article

TP37 - Tracking Fish Trajectories through Dynamic Pressure Signals: A Dual-Sensor System for Hydrodynamic Cues Monitoring

Gurvan Jodin, Florence Razan, Bastien Lagneaux, Corentin Porcon
article en

Abstract

Accurate characterization of hydrodynamic cues produced during fish locomotion is essential for understanding behavioral dynamics.In this work, a novel pressure sensor system is presented to isolate the dynamic pressure components associated with fish movements, while compensating for wave induced p ressure.The system combines a differential pressure sensor and a water level sensor.Its accuracy has been demonstrated through experimental validation against a classical potential flow model around a cylinder, confirming the robustness and effectiveness of the proposed approach.

Institut d'Électronique et des Technologies du numéRique (FR), Laboratoire des systèmes et applications des technologies de l'information et de l'énergie (FR), École Normale Supérieure de Rennes (FR)
Openalex Percentile: Top 71%
Water Quality Monitoring Technologies
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