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hivepoll SIGNED

Polling beehives to monitor parasitic infestations and gather pollination information

Total Cost €

0

EC-Contrib. €

0

Partnership

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Project "hivepoll" data sheet

The following table provides information about the project.

Coordinator
COGVIS SOFTWARE UND CONSULTING GMBH 

Organization address
address: WIEDNER HAUPTSTRASSE 17 3 A
city: WIEN
postcode: 1040
website: www.cogvis.at

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Austria [AT]
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.3. (PRIORITY 'Societal challenges)
2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs)
3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies)
 Code Call H2020-SMEInst-2018-2020-1
 Funding Scheme SME-1
 Starting year 2019
 Duration (year-month-day) from 2019-06-01   to  2019-11-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    COGVIS SOFTWARE UND CONSULTING GMBH AT (WIEN) coordinator 50˙000.00

Map

 Project objective

One out of every three bites of food we eat is there because of pollinators. However, pollinator and especially bee diversity has declined markedly in Europe and a study from 2014 by the university of Reading calculates the existing shortage at seven billion bees. In addition to the challenges from climate change and an ever growing world population the agricultural sector is under tremendous pressure to produce a lot more crop on limited acres and a declining pollinator population. Hivepoll aims to establish a novel data exchange platform between beekeepers and other stakeholder in the agriculture market. The project will not only offer a low-cost visual computing system to detect threats and effectively manage bee hives in real time but also unprecedented insights into the performance of bee colonies as pollinators. Hivepoll allows to predict crop yield and using better models to manage crop failure risks, two features which are among the biggest opportunities for Big Data applications in agriculture. With hivepoll it will become possible to provide an early warning system in case of a low pollination performance as well as being able to counter these adverse effects. Furthermore, an effective parasite detection will contribute to the health of bee colonies and their survival in good health over the winter which is a prime concern of bee keepers and farmers as honey bees are among the few pollinators which are active in sufficient force early in the planting cycle. A fast pollination of crops is extremely important as it alleviates the negative effects of unstable weather conditions such as spring frost. We predict an up to 10% increase in crop yield due to the improved management of pollination by hivepoll. Hivepoll is based on a successfully concluded 2 years research project with universities. In the project important follow-up steps for commercialization will be carried out.

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The information about "HIVEPOLL" are provided by the European Opendata Portal: CORDIS opendata.

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