Implementation of an IoT-Based Field Monitoring for Smart Agriculture System

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Abstract

Agricultural land monitoring is essential for supporting effective farming activities, particularly in rice cultivation where environmental conditions directly affect crop productivity. In practice, field conditions are still commonly monitored manually, which requires frequent field visits and may lead to delayed responses to environmental changes. This study presents an IoT-based agricultural field monitoring system designed to provide real-time and practical environmental information. The system integrates an ESP32 microcontroller with soil moisture, temperature-humidity, and light intensity sensors, and transmits data wirelessly to a cloud-based Firebase Realtime Database for remote access through a mobile application. The system was developed and evaluated through iterative implementation and functional testing under real field conditions. In addition to real-time monitoring, a simple forecasting feature based on historical data was incorporated to support early decision-making. Experimental results show that the system operates reliably and is positively accepted by farmers, indicating its potential to support practical and scalable agricultural land monitoring.

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