The ENOTECH 4.0 project "Development and validation of sensory, artificial vision and big data solutions for the wine sector" aims to promote the use of digital technologies and solutions – specifically IoT sensory, artificial vision and big data, and machine learning and deep learning– in the wine sector, to help improve production performance and product quality (wine).
ENOTECH 4.0 addresses the need of the wine sector to improve its productivity through the collection, monitoring and analysis of data in the vineyard and the winery. This will allow wine companies to make better and more agile decisions in their processes, such as harvesting, fermentation or bottling.
The result pursued by the project is to develop and validate a platform for the collection, monitoring and analysis of big data, taken through IoT sensors and artificial vision, in the wine production environment. In this way, wineries will be able to test advanced analytics algorithms, machine learning and deep learning, thus optimizing their operations.
ENOTECH 4.0 is a strategic inter-cluster project (promoted by Clusaga, Innovi and Packaging Cluster) and inter-territorial (involving companies from Galicia and Catalonia), designed to promote competitiveness and the transition towards digital leadership in the wine sector. It receives funding from the 2022 call of the support program for Innovative Business Groups (AEI) of the Ministry of Industry, Commerce and Tourism and is coordinated by the Galician Food Cluster (Clusaga).
Objectives of ENOTECH 4.0
- Study the potential impact of different critical variables of cultivation (vineyard) and production (cellar) on business KPIs and select those key factors to increase productivity and product quality.
- Define the BATs (Best Avaliable Technologies) that allow monitoring the selected variables and automate the collection of data necessary for their management in real time at a low cost.
- Develop new forms of management, analysis and visualization of the data and main KPIs that are generated in the vineyards and in the production processes that allow producers and processors to optimize decision-making.