Description du projet
Convertir l’odorat humain en données numériques
La numérisation a envahi tous les domaines de la recherche, mais les données concernant les expériences olfactives humaines demeurent toutefois marginales. Le projet D2Smell, financé par le CER, entend combler cette lacune de la science fondamentale en menant trois expériences. L’une d’entre elles consiste à équiper les participants de dispositifs portables afin de mesurer l’échantillonnage des odeurs, l’activité neuronale, des séquences vidéo et des composés organiques volatils. L’objectif principal est de créer un équivalent olfactif de Google Street View et d’exploiter les données recueillies pour numériser l’espace perceptif olfactif humain. Pour ce faire, le projet améliorera un modèle existant capable de recréer des odeurs à l’aide d’un ensemble limité d’odeurs primaires. D2Smell validera ensuite ce modèle par le biais des cadres SmelloVision et TelleSmell.
Objectif
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.
Champ scientifique
Mots‑clés
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Thème(s)
Régime de financement
HORIZON-ERC-SYG - HORIZON ERC Synergy GrantsInstitution d’accueil
7610001 Rehovot
Israël