Smart Irrigation System for Rice Farming - AI-IoT-Based SDIS Dataset

Overview

The Smart Irrigation System for Rice Farming dataset published on Mendeley Data in July 2025 presents sensor data and control decisions from an AI-IoT-based Smart Drip Irrigation System (SDIS) specifically optimized for rice cultivation.

System Design

• SDIS developed considering local agronomic characteristics specific to rice plant growth requirements and water management.
• Integration of AI algorithms for irrigation decision-making based on real-time sensor inputs and predictive models.
• IoT-enabled architecture allowing remote monitoring and control of irrigation infrastructure.

Dataset Features

• Soil Moisture: Real-time measurements from capacitive or resistive soil moisture sensors at root zone depth.
• Weather Data: Temperature, humidity, rainfall, and solar radiation affecting evapotranspiration rates.
• Irrigation Events: Timestamps, duration, and volume of water delivered through the drip system.
• Growth Stage Information: Rice plant phenological stages (vegetative, reproductive, ripening) affecting water requirements.
• Control Decisions: AI-generated irrigation scheduling decisions based on multi-parameter inputs.

Key Innovations

• Adaptation of drip irrigation technology specifically for flooded rice systems, traditionally managed with continuous flooding.
• Machine learning models trained on local agronomic data to optimize water use efficiency while maintaining yield.
• Integration of weather forecasting data for proactive irrigation scheduling.
• Consideration of soil type, field topography, and drainage characteristics in irrigation algorithms.

Use Cases

• Precision agriculture research: Evaluating water-saving irrigation strategies for rice cultivation in water-scarce regions.
• AI model development: Training and validating machine learning models for crop-specific irrigation scheduling.
• IoT system optimization: Designing robust and energy-efficient sensor networks for agricultural applications.
• Climate adaptation: Developing irrigation strategies for rice farming under changing rainfall patterns and water availability.