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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.

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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.

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  • SMAGRI Applications of digital twins and machine learning in climate-smart agriculture, final report

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Savonia-ammattikorkeakoulu

Savonia-ammattikorkeakoulu

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Tiina Haatainen

tiina.haatainen@savonia.fi