Project description DEENESFRITPL Safeguarding bees and Europe’s agricultural sector Climate change coupled with a growing population and a decline in pollinator and bee diversity are putting a tremendous strain on the agricultural sector. Using Big Data and deep learning, researchers of the EU-funded hivepoll project will work on the real-time detection of threats to beehives as well as the quantification of the pollination performance of an apiary. Using the gathered data, the project will set out to establish a novel data exchange platform between beekeepers and other stakeholders in the agriculture market. The data will also be used for crop yield prediction as well as the development of improved models for the management of crop failure risks. Show the project objective Hide the project objective 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. Fields of science natural sciencescomputer and information sciencesdata sciencebig datanatural sciencesbiological scienceszoologyentomologyapidologyagricultural sciencesagriculture, forestry, and fisheriesagriculturenatural sciencescomputer and information sciencesdata sciencedata exchangenatural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changes Programme(s) H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs Main Programme H2020-EU.3. - PRIORITY 'Societal challenges H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies Topic(s) EIC-SMEInst-2018-2020 - SME instrument Call for proposal H2020-EIC-SMEInst-2018-2020 See other projects for this call Sub call H2020-SMEInst-2018-2020-1 Funding Scheme SME-1 - SME instrument phase 1 Coordinator COGVIS SOFTWARE UND CONSULTING GMBH Net EU contribution € 50 000,00 Address Wiedner hauptstrasse 17 3 a 1040 Wien Austria See on map Region Ostösterreich Wien Wien Activity type Private for-profit entities (excluding Higher or Secondary Education Establishments) Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 21 429,00
