Agriculture Plays A Pivotal Role In Ensuring Food Security And Sustaining Livelihoods Globally. Soil Quality Is A Fundamental Determinant Of Agricultural Productivity, And Precise Soil Analysis Is Essential For Optimizing Crop Selection And Cultivation Practices. This Paper Presents An Innovative Approach To Soil Analysis And Crop Recommendation Using Long Short-Term Memory (LSTM) Algorithms With Soil Image Data. Traditionally, Soil Analysis Involves Time-consuming And Costly Laboratory Tests, Making It Challenging For Farmers To Access Real-time Information About Their Soil Quality. In This Study, We Propose A Non-invasive And Efficient Method That Leverages Soil Image Data Collected Through Remote Sensing And Drone Technology. These Images Capture Crucial Information About Soil Properties, Such As Texture, Moisture, And Nutrient Levels.
