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Наталя ХандусенкоRobots
22 April 2025, 09:42
2025-04-22
Robots get AI noses. Now they will perceive the world not only through sight and sound, but also through smell
The American developer of medical and wellness technologies has installed AI Nose — its new development — on humanoid robots from the Japanese company ugo. The robots will be able to experience the world in a completely new way, allowing them to make smarter and more intuitive decisions.
This breakthrough could chart a new course for robotics, artificial intelligence, and human-machine interaction, and could transform industry, healthcare, and everyday life.
The American developer of medical and wellness technologies has installed AI Nose — its new development — on humanoid robots from the Japanese company ugo. The robots will be able to experience the world in a completely new way, allowing them to make smarter and more intuitive decisions.
This breakthrough could chart a new course for robotics, artificial intelligence, and human-machine interaction, and could transform industry, healthcare, and everyday life.
How AI Nose works
The AI Nose system combines a high-precision array of gas sensors, real-time signal processing, and advanced artificial intelligence algorithms to identify and digitize a wide range of odors, transforming them into unique “odor identifiers,” Interesting Engineering writes .
These identifiers allow the robot to detect odors and environmental conditions similar to the human sense of smell.
“This marks a turning point for AI-based sensing. By adding smell to the sensor stack, robots can now understand their environment in ways previously only available to living things. I believe this is a game-changer for healthcare, industry, and everyday life,” said Ainos CEO Chung-Hsien (Eddie) Tsai.
What's next?
Companies are moving on to the next phase, which includes user interface (UI) development and internal control system integration, as well as fine-tuning sensor parameters and response logic. All of this is planned to be completed in 2-4 weeks.
This will be followed by real-world testing, namely in commercial buildings and public spaces.
In addition, the tests will include hazard warnings, as well as real-time data collection for deep learning and training AI models.
The team will also focus on developing applications for various sectors, including security, elderly care, hygiene monitoring, and industrial use.
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