Implementation of a wireless sensor network for irrigation management in drip irrigation systems

Area of Science:

• Agricultural Engineering
• Environmental Science
• Computer Science

Background:

• Water scarcity and inefficient irrigation challenge agriculture, especially in semi-arid regions.
• Traditional methods lead to water waste and uneven distribution, reducing crop productivity and sustainability.

Purpose of the Study:

• To investigate the integration of drip irrigation systems with wireless sensor networks (WSNs) for enhanced agricultural water management.
• To develop and test a system for real-time soil moisture monitoring and automated valve control in irrigation.

Main Methods:

• Designed and implemented soil moisture monitoring and valve control nodes for WSN integration.
• Collected real-time data on soil moisture, irrigation water volume (IWV), flowrate, and pipe pressure.
• Conducted field tests in an olive orchard during the irrigation season.

Main Results:

• Validated the system's capability to optimize irrigation scheduling by monitoring soil moisture variations at different depths.
• Achieved precise irrigation water volume application (2,209 m³), stabilized flowrate (approx. 2.8 m³/h), and enabled early anomaly detection through real-time pressure monitoring.
• Demonstrated enhanced irrigation efficiency and water conservation through automated control and data-driven insights.

Conclusions:

• WSNs significantly improve irrigation water management by providing real-time data and remote control.
• The integrated drip irrigation and WSN system offers a viable solution for optimizing water usage and conserving resources in agriculture.
• This technology is crucial for sustainable farming practices, particularly in water-scarce environments.