We’ve come a long way. Eight years ago, I updated an article series I originally contributed to Digi-Key in 2011. That update, The Five Senses of Sensors—Part I: Smell, Taste, and Hearing, discusses the technology that was available at the time, generally referred to as an “e-nose.”
This is how I introduced it in 2015: “An electrochemical nose, also called an e-nose, is an artificial olfaction device with an array of chemical gas sensors, a sampling system, and a pattern-classification algorithm to recognize, identify, and compare gases, vapors, or odors. In this way, the e-nose mimics the human olfactory system.”
Fast forward to today, where machine learning and robots reign.
Researchers at Tel Aviv University found a way for a robot to smell using a biological sensor. It works when the sensor sends electrical signals responding to a nearby odor, which a robot can detect and interpret. The researchers successfully connected the biological sensor to an electronic system and, using a machine learning algorithm, identified odors with sensitivity 10,000 times higher than that of a commonly used electronic device. They anticipate applications such as identifying explosives, drugs, diseases, and more—a far cry from yesterday’s e-nose. The scientists published their research in the journal Biosensor and Bioelectronics.
According to Dr. Maoz and Prof. Ayali, “Man-made technologies still can’t compete with millions of years of evolution. One area in which we particularly lag behind the animal world is that of smell perception. 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 explain that, in general, our sensory organs and those of all other animals use receptors that identify and distinguish between different signals. Then, the sensory organ translates these findings into electrical signals, which the brain decodes as information. The challenge of biosensors was the connection of the nose to an electronic system that knows how to translate the electrical signals received from the receptors.
The researchers connected the biological sensor and let it smell different odors while measuring the electrical activity that each scent induced. The system allowed for the detection of each odor at the level of the insect’s primary sensory organ. Then, machine learning created a ‘library’ of smells. They could characterize eight scents, such as geranium, lemon, and marzipan. After the experiment, they moved on to identify various types of Scotch whiskey.
The team believes that scientists can apply the technology to other senses, such as sight and touch. Now, the researchers plan to give the robot a navigation ability to allow it to localize the odor source and, later, its identity.
