Iot Integrated Ml System For Fertilizer Dosage Prediction

Abstract

Agriculture Plays A Huge Role In The Economies Of Developing Nations Like India, Where It Keeps More Than Half The Workforce Employed. Yet, Despite Its Importance, Farmers Still Struggle With How They Use Chemical Fertilizers. Too Much Fertilizer Degrades The Soil, Pollutes Lakes And Rivers, And Costs Farmers A Fortune. Too Little? Crops Barely Grow, And Yields Drop.This Paper Introduces An IoT-powered, Smart Crop Fertilizer Recommendation System Using Machine Learning, Designed To Tackle The Problem Head-on. At The Heart Of The Setup Is An ESP8266 NodeMCU V3 Microcontroller, Which Connects To A DHT11 Sensor For Temperature And Humidity, Plus A Capacitive Sensor To Check Soil Moisture. Together, These Monitor Key Environmental And Soil Conditions Around The Clock — Temperature, Humidity, And How Much Moisture The Soil Holds. Alongside These Readings, The System Collects Soil Nutrient Levels (nitrogen, Phosphorus, Potassium) And Sends Everything Wirelessly To A Cloud Server.On The Server, A Trained XGBoost Model Analyzes The Data And Delivers A Clear, Targeted Recommendation: The Best Fertilizer, The Right Blend, And The Exact Dosage. Farmers Can Check These Recommendations In Real Time Through A Web Dashboard Built With React.js And Tailwind CSS. It’s Simple And Friendly, So Anyone Can Navigate It Without Fuss.Tests Show The System Reaches 93.6% Accuracy In Its Classifications And Responds In Under A Second — About 900 Milliseconds — From Data Collection To Recommendation. This Proves It Has Real Potential For Smarter, More Precise Farming At Scale.

Keywords