Transmitting Odors Over the Internet with Scentronic
A dual-device setup pairs gas sensor arrays and piezoelectric misters to send digitized aromas through online servers.
By Letizia Giugliano
2 min readHuman-Edited, AI-Assisted
Two research teams from The Ohio State University and Zhejiang Laboratory have demonstrated a method to digitize and transmit odors over network connections. The setup pairs an electronic nose with an emitting unit called Scentronic, using machine learning to classify scents before misting preloaded liquid fragrances. So far, the system has successfully transmitted the aromas of coffee, beer, cake, oranges and red wine.
Six sensors that read airborne chemicals
The invention begins with an electronic nose mounted on a circular circuit board. According to New Atlas, the device relies on tin dioxide, a metal-oxide semiconductor whose electrical resistance changes when gas molecules touch its surface. In clean air, ambient oxygen binds to the material and draws away electrons. When volatile organic compounds drift across the sensors, they react with that adsorbed oxygen and return electrons, reducing resistance and causing measurable voltage increases.
Different airborne compounds generate distinct electrical reactions across the board, as reported by New Atlas. Ethanol in alcoholic drinks, limonene from citrus and diacetyl found in buttery aromas each create a separate pattern across the six sensors. This array produces a collective electrical reading that acts as a fingerprint for the target scent.
Classifying the chemistry through artificial intelligence
To convert raw electrical readings into identifiable scent categories, engineers turned to artificial intelligence algorithms. As detailed by New Atlas, the team compiled 250 labeled recordings, logging 50 runs for each of five foods and beverages: beer, cake, coffee, oranges and red wine. Each measurement tracked changing voltages across the sensor array over 200 seconds.
The researchers evaluated multiple machine learning models to match those electrical signatures to the correct food types, achieving classification accuracies between 96% and 100% in controlled tests covered by New Atlas. Once the software identifies an odor pattern, it assigns a category label and sends that command over the internet through a cloud server.
A miniature misting prototype in three wearable formats
The receiving terminal features Scentronic, a prototype that releases scents using liquid-filled chambers and piezoelectric atomizers. According to New Atlas, the hardware does not synthesize molecules from raw chemicals. Instead, preloaded liquids pass through cotton filters to reach vibrating discs, where an ESP32 microcontroller sends rapid electrical pulses to oscillate the discs at 110,000 vibrations per second, releasing the fragrance as a microscopic mist.
The development team built three versions of the dispenser: a two-channel wristband, a five-channel handheld unit, and a necklace holding five beads, per New Atlas. In tests with 14 human volunteers sniffing the handheld unit, users identified single scents with 73% accuracy and two-odor mixtures with 71% accuracy, while scent intensity ranking reached 59% accuracy.
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