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Digitising Smell: From Natural Statistics of Olfactory Perceptual Space to Digital Transmission of Odors

Project description

Converting human smell perception into digital data

Digitisation has permeated every realm of research, yet there remains a dearth of data regarding human olfactory experiences. The ERC-funded D2Smell project endeavours to address this gap in basic science by conducting three experiments. One of these experiments involves outfitting participants with wearable devices to measure odour sampling, neural activity, video footage, and volatile organic compounds. The overarching goal is to create an olfactory equivalent of Google Street View and leverage the gathered data to digitise the human olfactory perceptual space. To achieve this, the project will enhance an existing model capable of recreating odours using a set of limited odour primaries. D2Smell will then validate this model using the SmelloVision and TelleSmell frameworks.


This proposal is framed by a technological goal: We aim to digitize smell. Achieving this is currently prevented by gaps in basic science. We aim to fill these gaps, culminating in a proof of concept for our model. The primary gap we identify is lack of data on what humans typically smell. Phrased conceptually, in Aim 1 we ask what are the natural statistics of human olfactory perceptual space. We address this in a series of three experiments, highlighted by one where we equip participants with a wearable sampling apparatus we designed and built for this proposal. The apparatus measures sniffing behaviour to identify odor sampling, measures neural activity to verify olfactory perception, takes video of the visual scene, analyses total levels of volatile organic compounds in real time, and collects odor samples for detailed analysis off line. In other words, we generate an olfactory equivalent of Google Street View, with the addition of chemical, perceptual and neural data. Using this we will characterise the natural statistics of human olfactory perceptual space. Moreover, a major contribution of this proposal will be in posting this massive data as a publicly available recourse. Next, in Aim 2 we will use this data to digitize human olfactory perceptual space. We build on a model that allows us to recreate odors using a restricted set of odor primaries. We will test our model in two frameworks: One we call SmelloVision, where we develop the algorithmic framework to generate an odor to match any digital image, and one we call TelleSmell, where we develop a device to sense the environment, the algorithmic framework to transfer the data, and a device to generate the corresponding odor remotely. We provide pilot data for Aim 2 where we sensed an odor in Mainz (Germany), transmitted the data over IP to Rehovot (Israel), where we successfully recreated the smell. This was, as far as we know, the first transmission of odor over IP.

Host institution

Net EU contribution
€ 3 562 883,00
7610001 Rehovot

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Activity type
Higher or Secondary Education Establishments
Total cost
€ 3 562 883,00

Beneficiaries (4)