Objetivo
PhytlSigns is the world’s first wearable for plants that harnesses bioelectrical signals, translates them into digital form & visualizes them for further analysis. PhytlSigns amplifies the plant signals & reduces the background noise, allowing plant researchers & plant growers to measure important plant activity in response to changing environmental conditions. PhytlSigns allows to detect dangerous conditions such as pests or insects while the damage is still limited, saving growers thousands of euro per greenhouse & growth cycle.
Because electrical activity of plants is negligible compared to the electromagnetic interference around them, until now measuring it was possible only in labs with Faraday cages & other expensive equipment, which severely limited their practical applications.
PhytlSigns is currently used by plant researchers (such as University of Lausanne & Tel Aviv, Agroscope, etc.) to measure responses of tomatoes & eggplants to stress factors, to insect attacks & agrochemicals use and to track changes of nectar production in flowering plants.
PhytlSigns is aimed at getting a 30% share of the €100m total target market of equipment for plant researchers and 5-10% share of the ~1.3bn market of smart agriculture equipment for plant producers (in greenhouses)
Globally, PhytlSigns will contribute to wider adoption of smart agriculture addressing global food security & sustainability issues, as well as fostering novel agricultural research.
Vivent forecasts €30m+ revenues & 40+ employees in 2023.
In this Phase 1 project Vivent will produce a report that includes in-depth competitive threats analysis, additional market requirements & integration scenarios, sales/distribution strategy & detailed go-to-market strategy.
Ámbito científico (EuroSciVoc)
CORDIS clasifica los proyectos con EuroSciVoc, una taxonomía plurilingüe de ámbitos científicos, mediante un proceso semiautomático basado en técnicas de procesamiento del lenguaje natural.
CORDIS clasifica los proyectos con EuroSciVoc, una taxonomía plurilingüe de ámbitos científicos, mediante un proceso semiautomático basado en técnicas de procesamiento del lenguaje natural.
- ciencias naturalesciencias físicaselectromagnetismo y electrónicaelectromagnetismo
- ingeniería y tecnologíaingeniería eléctrica, ingeniería electrónica, ingeniería de la informacióningeniería electrónicasensoresbiosensores
- ingeniería y tecnologíaingeniería médicaimagenologíatomografía axial computerizada
- ciencias médicas y de la saludciencias de la saludnutrición
- ciencias médicas y de la saludmedicina básicafisiología
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Programa(s)
- H2020-EU.3.2. - SOCIETAL CHALLENGES - Food security, sustainable agriculture and forestry, marine, maritime and inland water research, and the bioeconomy Main Programme
- H2020-EU.3.2.4. - Sustainable and competitive bio-based industries and supporting the development of a European bioeconomy
- H2020-EU.3.2.1. - Sustainable agriculture and forestry
- H2020-EU.2.3.1. - Mainstreaming SME support, especially through a dedicated instrument
- H2020-EU.3.2.2. - Sustainable and competitive agri-food sector for a safe and healthy diet
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-SMEINST-1-2016-2017
Régimen de financiación
SME-1 - SME instrument phase 1Coordinador
1296 Gland
Suiza
Organización definida por ella misma como pequeña y mediana empresa (pyme) en el momento de la firma del acuerdo de subvención.