In precision agriculture, optimizing crop management is essential for
sustainable and efficient food production. This research leverages
artificial intelligence (AI) data mining techniques, specifically
employing a 3D CNN, to enhance precision in wheat crop production.
The background underscores the need for advanced technologies in
agriculture to address the challenges of increasing global demand and
environmental sustainability. The method involves the utilization of 3D
CNN for simultaneous feature extraction and prediction, providing a
holistic approach to crop monitoring. The contribution of this research
lies in the integration of AI-driven data mining to streamline crop
management processes, resulting in improved resource utilization and
increased yield. The application of 3D CNN demonstrated superior
performance in accurately predicting wheat crop production. The
model effectively extracted intricate spatial and temporal features,
contributing to enhanced decision-making capabilities for farmers.
The findings highlight the potential of AI-driven precision agriculture
in revolutionizing crop management, offering a scalable solution for
sustainable food production.