Internet of Things(IoT) Application for Crop Prediction and Fertilizer Suggestion Using Machine Learning Techniques

Abstract: Agriculture serves as the primary source of income globally, particularly in regions like the Indian subcontinent. However, modern challenges such as unpredictable weather patterns, water scarcity, and market fluctuations necessitate the adoption of advanced farming techniques. Soil fertility depletion, caused by various factors, further exacerbates these challenges, leading to decreased crop yields. To solve these problems, our project utilizes modern technology, specifically leveraging machine learning techniques. By integrating an NPK sensor with a web application, our goal is to give farmers practical insights into their soil's nutrient composition. Upon collecting nitrogen, phosphorus, potassium, and pH levels from the soil, these values are entered into the application. Compared to traditional farming methods, our project offers several advantages. Firstly, it empowers farmers with accurate and timely information about their soil's nutrient levels, giving them the ability to make wise decisions.