IoT-Enabled Smart Soil Monitoring System via Campus Wi-Fi and MySQL Server with Interactive Geospatial Analytics for Agricultural Automation

Abstract

Precision agriculture requires automated, high-resolution soil health diagnostics to optimize irrigation schedules, fertilizer management, and overall crop productivity. Conventional laboratory soil testing methods are labor-intensive, costly, and lack real-time spatial accessibility. This paper presents an integrated Internet of Things (IoT) multi-parameter soil monitoring platform designed specifically for agricultural automation. The system utilizes a 7-in-1 Modbus RS485 soil probe integrated with an ESP32 microcontroller to capture seven physical and chemical parameters simultaneously: volumetric moisture content, temperature, pH, electrical conductivity (EC), nitrogen (N), phosphorus (P), and potassium (K). Data payloads are transmitted over campus-wide Wi-Fi infrastructure using HTTP POST requests to a central MySQL relational database and rendered dynamically on an interactive Web-GIS geospatial analytics dashboard. Empirical evaluation across 32 georeferenced field samples at Universiti Teknikal Malaysia Melaka (UTeM) demonstrated high system stability, robust database logging, and precise spatial mapping capabilities. Statistical analysis revealed a bimodal moisture distribution across land-use types and an preliminary linear correlation observed at the test site between total macronutrients (NPK) and electrical conductivity (r = 0.9988, p < 0.001). Operating at Technology Readiness Level 4 (TRL 4), this work aligns directly with United Nations Sustainable Development Goals (SDG 2: Zero Hunger; SDG 15: Life on Land) by providing a scalable blueprint for automated soil diagnostics.