IoT-Based Smart AgroRobot for Soil Monitoring and AI-Based Crop Prediction

Abstract

The proposed “IoT-Based Smart AgroRobot for Soil Monitoring and AI-Based Crop Prediction” system is designed to improve modern agricultural practices using IoT technology, machine learning, robotics, and real-time monitoring systems. The system integrates soil moisture sensors, pH sensors, temperature and humidity sensors, ESP32 microcontroller, robotic movement control, and a Flask-based web dashboard to perform intelligent soil monitoring and crop prediction operations. The collected sensor data is analyzed using a machine learning model to predict suitable crops, fertilizer recommendations, and agricultural precautions based on realtime soil conditions. The AgroRobot supports wireless communication through ESP32 hotspot connectivity and enables live dashboard monitoring, robotic movement control, servo motor control, history management, and PDF report generation. The proposed system reduces manual effort, improves monitoring efficiency, and supports precision agriculture through automation and intelligent decision-making. Experimental results demonstrated reliable real-time monitoring, stable communication, successful robotic operation, and accurate AIbased crop prediction. The system can significantly contribute toward smart farming and sustainable agriculture applications.