Gas dispersion with induced airflow in mobile olfaction testbed

The unpredictable nature of gas dispersion is a well-known issue in mobile olfaction. As roboticists tend to depend on simulations and try to recreate environmental conditions in such simulations, an accurate representation of the gas plume is needed. Current model based simulations may not be able to capture the time-varying and unpredictable nature of gas distribution accurately. This paper presents the real-time gas distribution dataset collected in a mobile olfaction testbed which captures the time varying nature of a gas plume.