A café, the metro, a supermarket, a book store - many locations of everyday life have a specific smell. Recognising such olfactory scenes could inform personal activity tracking, environmental monitoring, and assist robotic navigation. Yet it is unclear if current Metal-oxide (MOx) sensor technology is sensitive and specific enough to achieve this. Factors like sensor drift, and sensitivity to ambient humidity and temperature further complicate the recognition of olfactory scenes. Hotplate temperature modulation has been suggested as a method to counter these drawbacks. We present an electronic nose based on MEMS-MOx sensors that support rapid hotplate temperature modulation with a 150 ms period. We recorded different natural olfactory scenes in an urban context. A linear SVM was able to recognise four olfactory scenes in single hotplate cycles with near-perfect performance when trained and tested on the same day, and 73% accuracy when tested in the same locations on the next day. Gas sensor responses yielded higher recognition accuracy than humidity, temperature, and pressure, which were also partly-location specific. Our results indicate that hotplate modulation enables recognition of natural odor scenes across extended timespans. These findings encourage the use of MOx-sensors as rapid sensing devices in natural, uncontrolled environments.
|Title of host publication||2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN)|
|Publication status||Published - 10 Jun 2022|