Estimating the distance of a gas source is important in many applications of chemical sensing, like e.g. environmental monitoring, or chemically-guided robot navigation. If an estimation of the gas concentration at the source is available, source proximity can be estimated from the time-averaged gas concentration at the sensing site. However, in turbulent environments, where fast concentration fluctuations dominate, comparably long measurements are required to obtain a reliable estimate. A lesser known feature that correlates with source proximity in a turbulent environment is the temporal variance of local gas concentration: Gas encounters become more intermittent farther from the source. However, is has commonly been assumed that exploiting this feature requires gas concentration measurements at the millisecond scale, usually requiring expensive photo-ionisation detectors. We have recently shown that, with appropriate signal processing, off-the-shelf metal-oxide sensors are capable of extracting rapidly fluctuating features of gas plumes that strongly correlate with source distance . We present a straightforward analysis method to decode events of large, consistent changes in the measured signal, which we denote ‘bouts’. The frequency of these bouts predicted the distance of a gas source in wind-tunnel experiments with good accuracy. In addition, we found that the variance of bout counts indicates cross-wind offset to the centre- line of the gas plume. Our results offer an alternative approach to estimating gas source proximity that is largely independent of gas concentration, using off-the-shelf metal-oxide sensors.
 Michael Schmuker, Viktor Bahr, and Ramón Huerta, “Exploiting Plume Structure to Decode Gas Source Distance Using Metal-Oxide Gas Sensors,” Sensors and Actuators B: Chemical 235 (November 2016): 636–46. Open access version available at https://arxiv.org/abs/1602.01815.