Wine sector
Smart monitoring of vines thanks to TracIAWine
We have developed a tracking and support system to manage the emergency from Sick Fish Disease
Ensure the health of the vines
monitoring the health status of the vineyards is a complex and often inefficient process:
Diseases are often detected too late, causing irreversible damage to crops;
I traditional methods are based on manual sampling and laboratory analysis, with long times and high costs;
The lack of updated and centralized data makes it difficult to compare the evolution of diseases over time and adopt effective intervention strategies.
Partner
The TracAIWine project was born thanks to the collaboration with Agrea, a research entity and scientific partner of the project, which contributed its expertise to address emerging challenges and new dangerous organisms, ensuring innovative solutions based on concrete data.
Announcement
We worked on the I-NEST call: a funding line of Spoke 7 within the PNRR and NextGenerationEU programs, focusing on innovation and digital transformation, especially in rural areas and the agritech sector.
Technologies
Machine Learning, blockchain, and Cloud Web platform
Location
Veneto Region, Italy
Recognizing and preventing diseases through AI
Our design approach is based on the scientific method: we started by analyzing the different types of vineyards to identify the main risk factors for the most common diseases, such as trunk disease, studying their life cycle, the ways they spread over time, and their effects on productivity.
Solution
The tracking system
The system is based on the implementation of blockchain technology and artificial intelligence, which is trained to recognize the presence of Downy Mildew by analyzing sample leaves from the vineyard.
The training process of the AI is dynamic, automated, and has a simple interface, with a series of charts that allow tracking the health status of the field and seeing the results provided by the artificial intelligence.
Data acquisition
I drones and ground sensors capture sample images of the grapevine leaves following routes in the vineyard
AI analysis of diseases
The AI detects the presence of the Esca disease using a trained machine learning model
Cloud Storage
The data is stored on a platform to ensure traceability and security
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
Results
Do you have a newly formed idea, a project to refine, or a specific need? Let's start from here.
