limel

7 ms·

1.
by limel 6mo ago
For the type of application you describe, we are planning to incorporate nanobio detectors, which can be extremely sensitive. In some applications we already combine non-selective and selective sensors, and together they create a multidimen
2.
by limel 6mo ago
Thanks for sharing these insights and real-life examples, they are very interesting. Yes, I believe there are situations where an olfactory sensor could detect a problem earlier than conventional sensors. For example, the smell of burnt oil
3.
by limel 6mo ago
You nailed it with the ‘poocalypse’. My parents have two cats, and that exact scenario was the reasons they decided not to buy a cleaning robot. Technically, I’m quite confident that Sniphi could recognize the smell of poo. The bigger chall
4.
by limel 6mo ago
Azure, together with Power Platform tools such as Power Apps, is primarily used for large-scale training. Since the odor and gas data require efficient labeling to be reliable, Power Apps combined with Data Explorer provides an easy, cost-e
5.
by limel 6mo ago
Yes, many current solutions rely on VOC sensors such as those from Sensirion, and we share the observation that a lot of the existing implementations remain at the demo stage and struggle in real industrial environments. In our case we are
6.
by limel 6mo ago
lol, that would be fun
7.
by limel 6mo ago
That’s a very good point, and we actually see fermentation batches as one of the most promising early use cases. In many facilities, smell is already used informally as a pass/fail indicator, but it is subjective and difficult to scale
8.
by limel 6mo ago
That’s true. We even started a PoC with a skincare products factory. The challenge, however, was that the frequent rotation of the product portfolio — and the large number of SKUs — made it difficult to justify the training effort. On the l
9.
by limel 6mo ago
That is actually an interesting direction. Since smoke detectors already exist, the next level could be distinguishing smoke from a cigarette — or even something harmless like burning scrambled eggs — from more dangerous sources such as bur
10.
by limel 6mo ago
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 f
11.
by limel 7mo ago
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
12.
by limel 7mo ago
The problem is not whether we can digitize the sense of smell, but that no industrial process currently relies on it by default. The real challenge is identifying the first scalable use case that proves measurable business value (sniphi tea