EXPLORE THE DATA ECOSYSTEM

VinBot responds to a need to boost the quality of European wines by implementing precision viticulture (PV) tools in the face of serious market threats worldwide and structural shortcomings within the EU wine sector. Wine producer associations have no control over yield management throughout their members’ vineyards, which leads to reduced quality wine at the association level. At the vineyard level, wine growers are not able to accurately assess yield due to the large amount of terrain to inspect, and use sample-based estimates of smaller production areas to estimate yield, which also negatively affects wine quality. An automatic yield monitoring system would allow winegrowers to accurately assess grape yield and relevant phyto-data via a set of sensors, tracking the state and location of the assets, generating maps, capturing sample locations, and sharing such information in a quick, flexible, autonomous and easy-to-use way.

By means of a novel, all-terrain, autonomous robot, VinBot automates the traditional visual yield estimation process throughout the entire vineyard, estimating the amount of leaves and grapes on the vine via computer vision and other sensors. Data-intensive computer vision algorithms are offloaded to external internet servers (the cloud). The VinBot extends visual leaf and fruit estimation throughout the entire vineyard, and centralises yield management in the SME-AGs by providing them with online yield maps of their members' vineyards. The VinBot represents a powerful precision viticulture tool, which does not exist today: the cloud-computing agricultural robot. Using the VinBot, the consortium SME wine producer associations will be able to coordinate and optimise yield management strategies throughout their thousands of members' vineyards, based on their collective expertise and commercial objectives. They expect to sell their wine for 8%-20% more over a five year period by employing the VinBot system to accurately estimate yield.

Acronym
VINBOT
Website
Address
ES
Scientific discipline(s)
Geographic coverage
Type
Data science categories
Data science categories