Smart "nose" identifies a person by breathing. Created a replacement for fingerprints

Japanese scientists have created an array of olfactory sensors with 16 channels. The device collects breathing data

person, and AI identifies the person.A study published in Chemical Communications showed the device was highly accurate: 97.8% accurate. The main disadvantage: to pass the test, you need to follow a six-hour diet.

The researchers analyzed people's breathing andidentified 28 volatile compounds that can be used to identify. Engineers created a complex chip consisting of several sensors, each of which captured the compounds of a certain group. The collected data is processed by AI, which is trained on the basis of breath patterns and determines the personality of a person.

System prototype and olfactory sensor. Source: Kyushu University, Yanagida Lab

Biometric identification widelycommon and fairly easy to fake, scientists say. Fingerprint or iris scanners are based on the physical uniqueness of each person, but they can be fooled. Physical characteristics can be copied or compromised by trauma, the researchers say.

Scientists note that chemical sensors are alreadyconsidered as a viable alternative. But most researchers have tried to recognize subcutaneous gas, compounds produced by the skin. The disadvantage of this method is the small number of volatile molecules that are difficult to detect and track. Breath, on the contrary, contains more compounds with individual composition.

According to the researchers, the sensor showed the samehigh efficiency when working with different people. Scientists have tested their method of identification on individuals of different sexes, ages and nationalities. But the sensor is still too early to introduce into industrial production. In order for the method to work, the test participants had to fast for six hours before the start of the experiment, the scientists report.

The developers plan to modify their device so that it can be used without a special diet. They believe that increasing the number of sensors will help overcome this hurdle.

Cover image: Kyushu University, Yanagida Lab

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