Integration, Calibration, and Experimental Verification of a Speed Sensor for Swimming Animals
Joaquin Gabaldon · Ellen L. Turner · Matthew Johnson-Roberson · Kira L. Barton · Mark P. Johnson · Erik J. Anderson · K. Alex Shorter
TL;DR
A micro-turbine speed sensor on animal tags was calibrated in flumes and towing tanks, and matched video-based speed and distance for dolphins.
BRIEF
Measuring how fast a swimming animal moves is hard, because GPS does not work underwater and speed sensors mounted near the skin read disturbed water rather than the true flow. This work tests a micro-turbine speed sensor mounted on an animal tag. Researchers used particle image velocimetry in a recirculating flume to see the flow around the tag, then compared tag readings from dolphins in a managed environment against overhead video, and checked tag-to-tag variability in a towing tank. The results help in interpreting speed data from animals and possibly underwater vehicles.
Abstract
Animal-attached GPS loggers are used to monitor the movement of land animals, but obtaining the measurements of aquatic animals remains challenging. Current animal-attached speed sensors are placed close to the body and measure the speed of the disturbed fluid near the skin interface, potentially affecting the accuracy of the measurement. Furthermore, the absolute speed estimates derived from the sensor data are affected by the location on the animal, orientation with respect to flow, and device shape. Here, we evaluate the performance of a micro-turbine in both the steady and variable flows using particle image velocimetry to visualize and measure the flow field around the tag and sensor. A closed recirculating flume was used to generate a range of both steady and oscillating flows at the sensor. During steady flow, turbine rotation rate was linearly correlated with both the free stream and near-sensor flow speeds. Following the controlled measurements of fluid speed in the flume, a tag with the speed sensor was used to measure both the speed and the total distance traveled by the dolphins in a managed environment. The results compared well with the speed and distance made from the analysis of video collected by an overhead camera system. Finally, the measurement variability of four specially designed tags with speed sensors was tested in the towing tank in the Marine Hydrodynamics Laboratory at the University of Michigan. These results provide a foundation for interpreting in-situ speed measurements from swimming animals, and potentially autonomous underwater vehicles, and will guide the development of the improved algorithms for the localization and energetics estimation.