Living as he does near a wastewater treatment plant, Santiago Marco knows all about recurring odors fouling the surrounding air. So the researcher at the Institute for Bioengineering of Catalonia developed an e-nose that, when paired with a drone, may help managers proactively reduce the stink their facilities emit.
Up to now, smells produced by wastewater treatment plants and other facilities processing or storing pong-prone substances have been carried out by humans. Bags of pungent air are collected, brought to a lab, plugged into a device, and released with lowering levels of oxygen mixed in until the odor is registered by people breathing it in. Marco and his team used a similar approach to train a portable electronic sensor to sniff out some of the most common and objectionable stenches treatment plants give off. Once they’d refined its olfactory capacities, the researchers strapped their e-nose to a drone for air collection and analysis above the sources of the various stink.
The full and definitely wonky study was first published by iScience, and subsequently described in a mercifully accessible and entertaining report by Engineering and Technology. Both note that while the drone-transported, 1.3 kg. e-nose may not be entirely perfected yet, its analyses mostly matched the 10 out of 13 correct responses provided by human nostrils.
“We are extremely happy with the results, but we need more validation and to make the device more robust for a real plant operation,” Marco, senior author of the study, told E&T. “The team plans to shave off some extra weight from the e-nose and develop a standardized process for the method. They are also planning to further optimize the device against influence from temperature, humidity, and other environmental conditions that can affect the accuracy.”
When flown around treatment plants by the drone in tests, the e-nose not only registered the various kinds and intensities of smells rising from wastewater, but eventually their location in the plant as well. The fast and full mobility of the UAV, paired with an onboard artificial intelligence AI algorithm, allowed research to map location and concentration of different odors.
That was put into a database whose growing inflows began to predict where, when, and how strong stink indeed stank – a capacity that, over time, should allow plant operators to devise preemptive methods of odor emission management.
Though the e-nose will undergo continued refinement before it can be routinely used with drones to monitor wastewater treatment plant smell, Marco feels confident the tech will eventually bring relief to human sniffers near those installations, and perhaps others like them.
“The work may also have implications for other facilities like landfills, composting plants, or even large farms with cattle and pigs that are also known to produce all types of malodors,” Marco said.
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