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Artificial Intelligence and Machine Learning in Precision Farming a Case Study of Nigeria: A Review

Domaine:

agriculture

Type de record:

paper
Créateur:
WanSilHamUsm
Éditeur:
Zenodo
Hôte:avatar

Precision farming leverages Artificial Intelligence (AI) and Machine Learning (ML) and has the 
potential to transform the agricultural landscape in Nigeria. This paper reviews the concepts, 
applications, benefits, and challenges of AI and ML in precision farming in Nigeria. Our case study 
highlights the use of AI-powered tools for crop monitoring, soil health analysis, and predictive 
analytics, demonstrating significant improvements in crop yields, water usage, and farmers’ 
income. The paper also considers the future prospects and limitations of adopting AI and ML in 
Nigerian Agriculture including infrastructure, data quality and farmers awareness. Our findings 
suggest that AI and ML can play a vital role in enhancing agricultural productivity and 
sustainability in Nigeria, and we recommend increased investment in digital infrastructure, 
capacity building and policy support to unlock the full potential of precision farming in the country. 

Visit

doi.org

Tags

Precision farming; Artificial Intelligence (AI); Machine Learning (ML); Technologies; Yield.

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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