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Fluorometer Control and Readout Using an Arduino Nano 33 BLE Sense Board.

Zechariah B Kitzhaber1, Caitlyn M English1, Kazi Ragib I Sanim2

  • 1Department of Chemistry and Biochemistry, 2629University of South Carolina, Columbia, SC, USA.

Applied Spectroscopy
|October 5, 2022
PubMed
Summary
This summary is machine-generated.

We developed a drone-based fluorometer for measuring chlorophyll-a using an Arduino Nano 33 BLE Sense board. This system enables automated water sampling and environmental monitoring from the air.

Keywords:
ArduinoAutomationaerial droneautomaticfluorometerlightweightlow-costlow-powermicrocontrollersUASsamplingsmall uncrewed aircraft systemwater

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Area of Science:

  • Environmental monitoring
  • Aquatic ecosystems
  • Remote sensing technology

Background:

  • Chlorophyll-a is a key indicator of aquatic ecosystem health.
  • Accurate in-situ measurements are crucial for water quality assessment.
  • Drone-based systems offer novel approaches for environmental sampling.

Purpose of the Study:

  • To describe the control and interfacing of a drone-based fluorometer for chlorophyll-a measurements.
  • To integrate a fluorometer with a small Uncrewed Aircraft System (sUAS) for automated water sampling.
  • To evaluate the performance and power consumption of the developed system.

Main Methods:

  • Utilized an Arduino Nano 33 BLE Sense board for fluorometer control and data processing.
  • Integrated the fluorometer into a sUAS, managed by a Raspberry Pi via the Robot Operating System (ROS).
  • Employed built-in sensors for monitoring environmental conditions and fluorometer integrity.

Main Results:

  • Achieved an average power consumption of 1.1 W.
  • Obtained a signal standard deviation of 334 µV for fluorescence blank measurements.
  • Reached an Analog-to-Digital Converter (ADC) precision of 130 µV for 10 Hz chopped measurements.

Conclusions:

  • The Arduino Nano 33 BLE Sense board is suitable for drone-based fluorometer control and data acquisition.
  • The integrated sUAS provides a viable platform for automated water sampling and chlorophyll-a monitoring.
  • The system demonstrates promising performance for aerial environmental sensing applications.