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D2Smell

Financiado

Digitising Smell: From Natural Statistics of Olfactory Perceptual Space to Digit...

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

31/01/2030

WEIZMANN

12M€

Presupuesto del proyecto: 12M€

Líder del proyecto

WEIZMANN INSTITUTE OF SCIENCE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 4 Participantes

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-01-29

ERC-2023-SyG: ERC Synergy Grants Objective:The aim is to provide support for a small group of two to four Principal Investigators to...

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

4 Participantes

WEIZMANN

3.56M€ | Lider

KTH

2.45M€ | Participante

2.86M€ | Participante

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Duración del proyecto: 72 meses Fecha Inicio: 2024-01-29
Fecha Fin: 2030-01-31

Líder del proyecto

WEIZMANN INSTITUTE OF SCIENCE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 12M€

Descripción del proyecto 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.

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