ARTICLE AD BOX
Scientists at Tel Aviv University in Isreal have created a robot that can recognise smells with 10,000 times more sensitivity than specialised devices, Neuroscience News reports.
The robot features a biological sensor comprising the antennae from a desert locust, electroantennogram technology, and artificial intelligence for signal analysis. The scientists say it could be used to detect drugs and explosives.
“A comparison with standard measuring devices showed that the sensitivity of the insect’s nose in our system is about 10,000 times higher than the devices that are in use today,” professor Yossi Yovel said.
The electrical system connected to the antennae measures the amount of signal produced when an odour is detected.
The robot is paired with an AI algorithm that has learned to characterise smells by the signal produced.
The scientists’ system can consistently differentiate between eight scents, including lemon, marzipan, geranium, and two mixtures of different smells.
Professors Ben Moaz and Amir Ayali explained that manufactured sensor technologies don’t hold a candle to their biological equivalents — which have undergone millions of years of evolution.
“One area in which we particularly lag behind the animal world is that of smell perception,” they said.
“An example of this can be found at the airport where we go through a magnetometer that costs millions of dollars and can detect if we are carrying any metal devices. But when they want to check if a passenger is smuggling drugs, they bring in a dog to sniff him.”
“In the animal world, insects excel at receiving and processing sensory signals. A mosquito, for example, can detect a 0.01 percent difference in the level of carbon dioxide in the air. Today, we are far from producing sensors whose capabilities come close to those of insects,” they added.
Now read: Scientists successfully test laser system that can redirect lightning
Share your thoughts: Scientists use locust antennae to gi…
Subscribe to our daily newsletter
Loading ...

3 years ago
1








English (US)