Autonomous multi-species environmental gas sensing using drone-based Fourier-transform infrared spectroscopy

Area of Science:

• Environmental Science
• Spectroscopy
• Robotics

Background:

• Unmanned aerial vehicles (UAVs) offer new possibilities for airborne gas sensing.
• Current UAV gas sensors (electrochemical, photo-ionisation) have limitations in speed, selectivity, sensitivity, and accuracy.
• There is a need for advanced airborne gas sensing technologies with improved performance.

Purpose of the Study:

• To design and integrate a broadband Fourier-transform infrared (FTIR) spectrometer with an autonomous UAV.
• To enable rapid, quantitative aerial surveys of multiple gas species simultaneously.
• To demonstrate precise gas source localization and distribution mapping with uncertainty quantification.

Main Methods:

• Integration of a broadband FTIR spectrometer (3-11 µm) with an autonomous UAV.
• Utilizing ro-vibrational spectroscopy for gas analysis.
• Application of Bayesian interpolation for gas concentration mapping and source localization.

Main Results:

• Successful integration of FTIR spectrometer with UAV for airborne gas sensing.
• Demonstrated rapid, quantitative aerial surveys of multiple species.
• Achieved noise-limited performance of 18 ppm for propane.
• Accurate localization of gas point sources (approx. 1m accuracy) and gas cloud mapping with uncertainty quantification.

Conclusions:

• The developed UAV-based FTIR system overcomes limitations of traditional sensors.
• This technology enables advanced environmental monitoring and hazardous scene assessment.
• The system provides accurate, quantitative, and spatially resolved gas distribution data.