Facing climate and health challenges in viticulture
The wine sector faces numerous challenges that jeopardize the quality and productivity of the harvest:
periods of drought alternating with intense rains cause water stress in the vines, compromising growth and reducing yield;
fungal diseases and pests, often detected too late, spread rapidly, causing serious damage and requiring expensive chemical treatments;
nutritional deficiencies weaken plants, increasing their vulnerability to diseases and reducing productivity.
Partner
Vine AI was developed in collaboration with the National Research Council (CNR), our scientific partner in the project. We combined our technological expertise with the CNR's research activity to ensure the robustness and scientific validity of Vine AI.
Announcement
We have worked on the NODES (North West Digital and Sustainable) funding financed by the PNRR and NextGenerationEU. The project aims to support the digitalization of agricultural supply chains and the development of rural areas, through concrete applications of research and collaboration between businesses and the academic world.
Technologies
Drones, AI, Computer vision, Data Analytics
Location
Villareggia, Turin, Italy
Innovation to transform agricultural management
After analyzing the industry challenges, we have developed a tool to allow winemakers to digitally monitor the health of the vines.
Through a web platform, we enable real-time visualization and analysis of data related to the vineyard and the well-being of the plants, also detecting the most imperceptible changes in their growth.
Solution
The tracking system
To ensure constant monitoring of the health status of the vines, drones fly over the rows of the vineyard capturing high-resolution images. These images are analyzed by an AI model, trained to detect signs of stress and pests.
The data is processed to create a 2D and 3D reconstruction of the vineyard, allowing winemakers to monitor the plants in real time. Through our web platform, winemakers can view this information to make quick decisions based on concrete data.
Data acquisition
I drones and ground sensors capture sample images of the grapevine leaves following routes in the vineyard
AI analysis of diseases
AI detects the presence of diseases using a trained machine learning model
3D Reconstruction
The vineyard is reproduced in a three-dimensional model to visualize its health status and compare it over time
Crop traceability
The system monitors the state of the crops by identifying critical points to prevent losses and waste
Interactive monitoring
The platform allows farmers to view in real time the status of the vines' health and the results of the AI
Cloud Storage
The data is stored on a platform to ensure traceability and security
Results
Do you have a newly formed idea, a project to refine, or a specific need? Let's start from here.
