Design and Implementation of an Internet of Things Based Precision Agriculture System for Maize Growth

Student: Isaac Olumide Faluyi (Project, 2025)
Department of Computer Engineering
Ekiti State University, Ado-Ekiti, Ekiti State

Abstract

This study developed an IoT-based precision agriculture system to optimize maize cultivation byaddressing key challenges of inefficient resource use and low yields. The system integrates soilmoisture (SM150T), NPK nutrient (JXCT-IoT), and environmental sensors (DHT22, DS18B20)with ESP32/ESP8266 microcontrollers, transmitting real-time data via Wi-Fi/ESP-NOW to aFirebase cloud platform for analysis and decision support. Field tests demonstrated a 30%reduction in water usage, 20-25% yield improvement, and reliable monitoring with ±3% soilmoisture accuracy, powered autonomously by a 200W solar system. Results validate the system'seffectiveness in enhancing maize productivity through data-driven irrigation and fertilization,while recommendations include integrating machine learning for predictive analytics, developingself-calibrating sensors, and optimizing costs for smallholder adoption. The study contributes tosustainable agriculture by combining IoT technology with precision farming principles to improveresource efficiency and crop yields in maize cultivation.Keywords: Precision agriculture, IoT farming, smart irrigation, maize cultivation, soilmonitoring, sustainable agriculture, cloud analytics

Keywords
design implementation internet things precision agriculture system maize growth
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