Comment by chabes
4 days ago
I built a prototype “digital nose” almost a decade ago, inspired by this blog post https://web.archive.org/web/20180513090020/http://www.maskau...
I have a friend with Chrons, IBS, and a handful of other gut issues. He wants me to build something like this to help self-diagnose acute issues as they arise. Yes, a fart classifier.
I want to use a smell classifier to identify ripeness levels in agriculture.
I haven’t tested to see if this is even feasible, but I’d like to also use a tool like this for pest scouting in agriculture. If the sensors are sensitive enough to detect small amounts of fungi, arthropod activity, or hormonal shifts, this could be useful for early detection in integrated pest management systems.
We conducted research with local universities, and the digital nose was able to detect the presence of pests in oat flakes and beans (two different species).
When we published the white paper ( https://sniphi.com/wp-content/uploads/2025/10/Sniphi_digital... ), we expected a queue of agricultural companies interested in the technology. However, pests apparently aren’t “sexy” enough to capture attention.
We observed the same reaction with bananas — fresh vs. overripe, like in the video. Technically interesting, but no one saw clear business potential.
So now we are looking for use cases that are more obvious and compelling from a business perspective. Any ideas?
Are not there medical applications ? Like the lady that can detect parkinson's by the smell. https://www.scientificamerican.com/article/a-supersmeller-ca...
How good are digital smellers compared with super human smellers?
Unfortunately, medical applications require enormous time and effort to meet strict verification and regulatory requirements. While this is an important long-term direction, we are currently focusing on lower-hanging opportunities such as food manufacturing and processing, where there is strong potential for cost savings and loss prevention.
Digital smellers are scalable and more repeatable than human noses. At the current stage our electronic nose operate either through classification of previously trained odor classes or through anomaly detection. What is still missing is a possibility to run a more sophisticated conversation with the model when something smells "suspicious".