AI Nose Technology Unveiled for Health Care, Chip Manufacturing
- tech360.tv
- Sep 9, 2025
- 2 min read
A 40-year-old Taiwanese organisation, Ainos, has introduced what it calls the "world’s first" commercially available AI Nose. The technology, debuting this week at SEMICON, aims to detect illnesses, enhance factory safety, and improve chip yields.
The AI Nose uses tiny micro-electro-mechanical sensor arrays to "sniff" the air. A proprietary Smell Language Model (SLM), trained on a 13-year scent dataset, then analyses the scent signature.
This mechanical nose detects volatile organic compounds down to the parts-per-billion range. The SLM translates this physical data into a "Smell ID," which is an indexable, machine-readable representation of scent patterns.
Ainos Chief Executive Officer Eddy Tsai stated that smell represents a "new category in industrial sensing."
Initially, the AI Nose targets the semiconductor industry, a sector valued at USD 115 billion in Taiwan. In this industry, tiny chemical leaks can lead to costly yield losses or safety hazards.
The company also focuses on hospital infection control, environmental monitoring, and food quality assurance. Future modules could be tailored for flexible detection ranges, including ammonia in clean rooms and methane in energy facilities. This expansion could broaden the AI Nose market to areas like environmental compliance, agriculture, and municipal infrastructure.
The artificial nose business includes other organisations developing similar technologies. Noze has received investment from the Bill & Melinda Gates Foundation, while Canaery concentrates on port and shipping safety. Koniku reportedly uses biological neurons for applications such as airport security, military sensing purposes, and agriculture. Universities, startups, and DARPA have also experimented with digital noses, though most of these efforts remain niche, experimental, or confined to laboratories.
Ainos launched its "AI Nose," claiming it is the "world’s first" commercially available AI nose.
The technology uses micro-electro-mechanical sensor arrays and a proprietary Smell Language Model.
Initial target markets include the semiconductor industry, hospital infection control, and environmental monitoring.
Source: FORBES
