Development of an Iot-Based Sensor for Real-Time Analysis and Nutrient Management in Maize (zea Mays) Cultivation

Student: Micheal Ayomide Akinjisola (Project, 2025)
Department of Computer Engineering
Federal Polytechnic, Ile-Oluji, Ondo State

Abstract

The development of a smart farm management system enhances productivity and sustainability in maize cultivation. The system integrates an ESP32 microcontroller with an NPK sensor to collect soil nutrient data, which is analyzed using machine learning algorithms for predictive fertilizer recommendations. Data transmission is achieved via the IoT framework to a cloud server, enabling real-time monitoring and decision-making. The primary goal is to optimize fertilizer usage, maximize crop yield, and support sustainable agricultural practices. The IoT-based system provides precise and data-driven insights that improve maize productivity while promoting efficient nutrient management for farmers.

Keywords
IoT Smart Farming Maize Cultivation NPK Sensor Machine Learning Real-Time Analysis Fertilizer Management Precision Agriculture ESP32 Soil Monitoring
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