Information och funktioner
Publicerad
Savonia yrkeshögskola
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.
Skriftligt arbete
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.
Förtydligande information
Utbildningsområden
Teknik
Språk
Engelska
Författare
Md Zayed Bin Sakib Khan, Project Assistant
Patryk Wójtowicz, Research Manager
Utgivare
Savonia-ammattikorkeakoulu