Today, electronic noses are used in applications from air quality monitoring to food flavor research. The problem though is that they cost $5000 to $10,000. However, printable organic electronics could bring the cost down to tens of dollars, leading to a slew of new applications like refrigerators that sniff out spoiled food, pest-detectors for gardens, and pocket-sized medical diagnostic devices that can smell disease. The new issue of IEEE Spectrum looks at the latest in electronic nose research. The article was written by Josephine B. Chang, a former UC Berkeley student, and Berkeley professor Vivek Subramanian, whose early work on e-noses I wrote about in Lab Notes here. From their IEEE Spectrum article:
This e-nose will be the culmination of decades of work at countless laboratories, where researchers have sought to create a tiny, cheap, automatic sniffer that would let wine bottles monitor the aging of their contents, allow meat packages to flag spoilage, and enable mailboxes to check for bombs. Imagine barroom coasters that double as Breathalyzers, bumper stickers that monitor car emissions…
Rather than developing one nose for wine monitoring and a different one to detect bad fish, the same piece of hardware could be trained separately for different tasks. Imagine an electronic-nose system shipped with standard pattern-recognition libraries. Load up one for the refrigerator and the system will sniff for spoiling foodstuffs; load up a different one for the garden and the system searches instead for the telltale odors of snails and other pests. And what if you want the e-nose to learn the difference between Grandma’s apple pie and Mom’s? Well, chances are the manufacturers will have never met Grandma or Mom or sampled the output of their ovens. But they may have included software for generating new pattern-recognition libraries. If so, you would hook up the nose to the training system, introduce it to one apple pie at a time, and find out if the pies generate distinguishable responses in the array. If they do, then generate a new library, load it up, and you’ve got a personalized apple- pie connoisseur.