An AI-Based Guiding System That Recommends the Optimal Crop Based On the Environment and Soil Type

Global food security depends heavily on agriculture, yet because soil and environmental conditions differ, farmers frequently struggle to choose the best crops for their region. Traditional crop selection methods rely on experience and manual assessments, which may not always yield optimal results. To address this issue, this project proposes an AI-Based Guiding System for Optimal Crop Recommendation that utilizes system of artificial intelligence, machine learning, and data analytics is to analyze key agricultural parameters, including soil type, $\mathbf{p H}$ levels, climate conditions, and water availability. By processing real-time and historical data, the system provides accurate recommendations of the best crops to cultivate, ensuring improved productivity and sustainability. By putting this system into place, farmers may maximize the use of their resources, increase crop production, and lower the risks that come with selecting the wrong crops. By integrating advanced AI-driven insights into agriculture, this project contributes to smart farming practices, promoting efficient and sustainable agricultural development.