AI-Driven Design of Climate-Resilient Crops, Farm Layouts, and Adaptive Agricultural Techniques

Abstract: The worsening speed of climate change is causing agricultural issues never seen before to arise. Farmers' earnings and food security are under jeopardy from all these issues. It demonstrates how cleverly to cultivate climate-resilient crops, how best to build up farms, and how flexible farming utilizing artificial intelligence may be done. To provide efficient farming plans and forecast how crops will perform in response to changing weather conditions, the system combines temperature data, satellite images, and machine learning approaches. When reinforcement learning is coupled with real-time monitor inputs, agricultural chores including watering, planting, and pest control may vary on demand. These all-encompassing strategies enable everyone to make decisions that not only increase productivity but also assist in long-term survival and the resource economy. For instance, the recommended approach may alter farming by increasing its resistance to climatic fluctuations.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-05-01
DOI
https://doi.org/10.52783/jisem.v10i41s.7983
Citations
1
Primary Topic
Greenhouse Technology and Climate Control
Type
article
Field-Weighted Citation Impact
1.75
Controls
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article

AI-Driven Design of Climate-Resilient Crops, Farm Layouts, and Adaptive Agricultural Techniques

Delia Grace
1 citations
Journal of Information Systems Engineering & Management
Greenhouse Technology and Climate Control
1.75
article

AI-Driven Design of Climate-Resilient Crops, Farm Layouts, and Adaptive Agricultural Techniques

Delia Grace
article en
1 citations

Abstract

Abstract: The worsening speed of climate change is causing agricultural issues never seen before to arise. Farmers' earnings and food security are under jeopardy from all these issues. It demonstrates how cleverly to cultivate climate-resilient crops, how best to build up farms, and how flexible farming utilizing artificial intelligence may be done. To provide efficient farming plans and forecast how crops will perform in response to changing weather conditions, the system combines temperature data, satellite images, and machine learning approaches. When reinforcement learning is coupled with real-time monitor inputs, agricultural chores including watering, planting, and pest control may vary on demand. These all-encompassing strategies enable everyone to make decisions that not only increase productivity but also assist in long-term survival and the resource economy. For instance, the recommended approach may alter farming by increasing its resistance to climatic fluctuations.

Journal of Information Systems Engineering & ManagementVol. 10(41s)
Openalex Percentile: Top 16%
Greenhouse Technology and Climate Control
1.75
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AI-Driven Design of Climate-Resilient Crops, Farm Layouts, and Adaptive Agricultural Techniques — Delia Grace · Journal of Information Systems Engineering & Management (2025) | TGRS Research Map | TGRS