Information and features
Published
Savonia University of Applied Sciences
SMAGRI Applications of digital twins and machine learning in climate-smart agriculture, final report
How to use the potential of digital twins and machine learning in agriculture? These tools can solve challenges allowing accurate, data-driven decision-making, optimizing use of resources, and increasing resilience to economic and environmental challenges.
Reading material
24.4.2025
- 31.12.2026
This report explores how Digital Twins (DT), and Machine Learning (ML) can help farmers achieve sustainable, resilient, and productive farming techniques by addressing important challenges with modern agriculture. The report aims to summarize information and state-of-the-art on how these technologies can support sustainable, productive, and efficient agricultural methods through analyzing their applications, advantages, and challenges.
Further details
Fields
Engineering and technology
Language
English
Author(s)
Md Zayed Bin Sakib Khan, Project Assistant
Patryk Wójtowicz, Research Manager
Publisher
Savonia-ammattikorkeakoulu