Efficient IoT-Based Control for a Smart Subsurface Irrigation System to Enhance Irrigation Management of Date Palm

Area of Science:

• Agricultural Engineering
• Environmental Science
• Computer Science

Background:

• Drought poses a severe threat to global agriculture, increasing the need for improved water management.
• Enhancing water productivity is crucial for sustainable agriculture, especially in arid regions.
• Date palm cultivation is vital in arid areas but highly susceptible to water scarcity.

Purpose of the Study:

• To design and validate a cloud IoT-based controlled subsurface irrigation system (CSIS) for date palms.
• To improve irrigation management by remotely monitoring and controlling water application.
• To compare sensor-based irrigation scheduling (S-BIS) with time-based irrigation scheduling (T-BIS) and traditional surface irrigation (TSI).

Main Methods:

• Developed a fully automated CSIS using an autonomous sensor network to collect climate and soil moisture data.
• Utilized the ThingSpeak cloud platform for data hosting, analysis, visualization, and device control.
• Implemented S-BIS for precise water delivery to the root zone, contrasting it with T-BIS and TSI.

Main Results:

• CSIS with S-BIS reduced applied irrigation water by 64.1% compared to TSI, with annual use of 21.04 m³ per palm.
• Water productivity was significantly higher with S-BIS (1.783 kg m⁻³) and T-BIS (1.44 kg m⁻³) than TSI (0.531 kg m⁻³).
• S-BIS maintained volumetric soil water content near field capacity in the root zone, optimizing conditions for date palms.

Conclusions:

• The designed CSIS with S-BIS offers a highly effective solution for date palm irrigation in arid regions.
• This system positively impacts irrigation water management and enhances date palm fruit yield.
• Cloud IoT technology integrated with subsurface irrigation is key to sustainable agriculture in water-scarce environments.