A Smart Agrisense IoT System with ML Integration

This paper presents an advanced agricultural monitoring system utilizing Internet of Things (IoT) technology to provide precise soil and nutrient analysis. The core of the system is the ESP32 microcontroller, which processes data from various sensors to facilitate seamless operation. The focus is on improving crop yield and soil health by continuously monitoring nitrogen, phosphorus, and potassium (NPK) levels. The system explores recent advancements, including machine learning algorithms for accurate crop recommendations and edge computing for real-time data processing. Challenges faced in implementing such systems-such as sensor calibration, maintaining data consistency, and integrating predictive models-are addressed. Despite these obstacles, field tests demonstrate the system’s reliability in analyzing soil fertility and offering tailored crop suggestions. The system consistently provides actionable insights to identify suitable crops, ensuring efficient resource use. This proposed agricultural monitoring system is designed to overcome these challenges and significantly advance precision farming. It is innovative, affordable, and easy to operate, making it a valuable tool for modern agriculture.