AI in Agricultural Technology: Optimizing Crop Yield Predictions

Artificial Intelligence (AI) is revolutionizing the agricultural industry, offering tools to optimize crop yield predictions with high accuracy and efficiency. By leveraging machine learning (ML), deep learning (DL), remote sensing, and data analytics, farmers can make informed decisions that enhance productivity and resource use. This paper explores the integration of AI techniques in crop yield prediction, evaluates current methodologies, and proposes a hybrid model combining remote sensing data with real-time sensor inputs to enhance predictive accuracy.

Publication Details

Journal
PhilPapers (PhilPapers Foundation)
Published
2025-01-01
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
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article

AI in Agricultural Technology: Optimizing Crop Yield Predictions

PhilPapers (PhilPapers Foundation)
Smart Agriculture and AI
article

AI in Agricultural Technology: Optimizing Crop Yield Predictions

article en

Abstract

Artificial Intelligence (AI) is revolutionizing the agricultural industry, offering tools to optimize crop yield predictions with high accuracy and efficiency. By leveraging machine learning (ML), deep learning (DL), remote sensing, and data analytics, farmers can make informed decisions that enhance productivity and resource use. This paper explores the integration of AI techniques in crop yield prediction, evaluates current methodologies, and proposes a hybrid model combining remote sensing data with real-time sensor inputs to enhance predictive accuracy.

PhilPapers (PhilPapers Foundation)
Zero hunger
Openalex Percentile: Top 35%
Smart Agriculture and AI
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AI in Agricultural Technology: Optimizing Crop Yield Predictions · PhilPapers (PhilPapers Foundation) (2025) | TGRS Research Map | TGRS