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Why can't we mimic a dog's ability to smell COVID?
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Problem
As far as I can tell, we have invented tools and algorithm to:
But why is it that dogs can smell COVID or Cancer and we can't produce a similar tool to "smell diseases"? Why can't we mimic the dog's sense of smell: is it a hardware limitation or a software one? Am I mistaken in thinking that this sense is the hardest to mimic?
- Detect a wider range of colors at a larger range than humans or any other animals on the planet
- Detect sound with wavelengths inaccessible to humans or most animals on the planet
But why is it that dogs can smell COVID or Cancer and we can't produce a similar tool to "smell diseases"? Why can't we mimic the dog's sense of smell: is it a hardware limitation or a software one? Am I mistaken in thinking that this sense is the hardest to mimic?
Solution
Addressing the hardware side of your question:
A dog's sense of smell was developed through millions of years of evolution. The dog's nose is powered by hundreds of millions of organic nanomachines (olfactory receptors) working in concert to detect the faintest traces of odors, in the form of individual molecules floating among an endless sea of nitrogen, oxygen, and molecules from other nearby sources producing orders. I don't think we have hard numbers, but some estimates say that a dog's nose can distinguish molecules in the parts-per-billion or even parts-per-trillion (or higher) range.
When these millions of finely crafted organic nanomachines detect molecules of something besides oxygen and nitrogen floating in the air, the signal is sent to the brain, which then cross-references this data against an exhaustive library of known molecules (some instinctive and some learned), and interprets it as a "smell". Different concentrations of different molecules will be interpreted as different smells, and we know from numerous practical use cases that dogs can be trained to seek out specific smells.
It takes extremely sophisticated sensors to even begin to approach a dog's ability to detect and classify those stray molecules floating through the air that make up an odor.
In contrast, measuring sound is child's play (since it's just vibrations through air or another medium) and even imaging is comparatively simple (measure the wavelength and intensity of light striking the image sensor).
An astronomically greater amount of R&D has gone into light and sound because these have the greatest number of commercial applications. We can use light sensors to record and share photos and videos. We can use audio sensors to record and share music, speech, and more. We can combine these two technologies to produce movies, television, and more.
On the other hand, the best you could do with an odor sensor is produce a chart or graph of relative molecular concentrations. We don't have any kind of consumer-level technology that can reproduce arbitrary odors from digital recordings for other audiences to smell. Hollywood isn't likely to be investing millions of dollars per year into odor sensors. There aren't enough practical applications.
When we do have a practical need for odor detection outside of scientific research (e.g. for security or police purposes), do we typically issue some multi-million dollar precision gadget that can detect all of the relevant molecules in the air? No, we do what humans have probably done for thousands of years before the first electronics: use a trained dog.
A dog's sense of smell was developed through millions of years of evolution. The dog's nose is powered by hundreds of millions of organic nanomachines (olfactory receptors) working in concert to detect the faintest traces of odors, in the form of individual molecules floating among an endless sea of nitrogen, oxygen, and molecules from other nearby sources producing orders. I don't think we have hard numbers, but some estimates say that a dog's nose can distinguish molecules in the parts-per-billion or even parts-per-trillion (or higher) range.
When these millions of finely crafted organic nanomachines detect molecules of something besides oxygen and nitrogen floating in the air, the signal is sent to the brain, which then cross-references this data against an exhaustive library of known molecules (some instinctive and some learned), and interprets it as a "smell". Different concentrations of different molecules will be interpreted as different smells, and we know from numerous practical use cases that dogs can be trained to seek out specific smells.
It takes extremely sophisticated sensors to even begin to approach a dog's ability to detect and classify those stray molecules floating through the air that make up an odor.
In contrast, measuring sound is child's play (since it's just vibrations through air or another medium) and even imaging is comparatively simple (measure the wavelength and intensity of light striking the image sensor).
An astronomically greater amount of R&D has gone into light and sound because these have the greatest number of commercial applications. We can use light sensors to record and share photos and videos. We can use audio sensors to record and share music, speech, and more. We can combine these two technologies to produce movies, television, and more.
On the other hand, the best you could do with an odor sensor is produce a chart or graph of relative molecular concentrations. We don't have any kind of consumer-level technology that can reproduce arbitrary odors from digital recordings for other audiences to smell. Hollywood isn't likely to be investing millions of dollars per year into odor sensors. There aren't enough practical applications.
When we do have a practical need for odor detection outside of scientific research (e.g. for security or police purposes), do we typically issue some multi-million dollar precision gadget that can detect all of the relevant molecules in the air? No, we do what humans have probably done for thousands of years before the first electronics: use a trained dog.
Context
StackExchange Computer Science Q#136333, answer score: 39
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