An auto-validation method for a complete IoT pivot irrigation model based on the Penman-Monteith equation

Area of Science:

• Agricultural Engineering
• Internet of Things (IoT)

Background:

• Pivot irrigation systems aim to increase farmland cultivation without escalating water consumption.
• Existing systems face challenges in crop water requirement determination, IoT integration, data interpretation, and validation.

Purpose of the Study:

• To present a comprehensive IoT pivot irrigation model with an auto-validation method.
• To address challenges in IoT pivot irrigation, including sensor errors and data interpretation.
• To develop a benchmark framework for evaluating pivot irrigation systems.

Main Methods:

• Developed a complete IoT pivot irrigation model incorporating an auto-validation mechanism.
• Utilized the Penman-Monteith equation for the auto-validation process.
• Established a benchmark framework for system evaluation.

Main Results:

• The proposed auto-validation method protects the pivot system from sensor errors.
• The model successfully addresses identified challenges, offering a comprehensive IoT solution.
• Experimental validation using grass demonstrated significant improvements over traditional irrigation.

Conclusions:

• The developed IoT pivot irrigation model with auto-validation is effective for optimizing water usage.
• The benchmark framework provides a standardized approach for future research and development.
• The system enhances agricultural productivity and offers a viable solution for modern farming.