Self-Sensing Antenna for Soil Moisture: Beacon Approach.

Area of Science:

• Electrical Engineering
• Agricultural Technology
• Sensor Networks

Background:

• Transitioning from the Internet of Things (IoT) to the Internet of Underground Things (IoUT) presents significant antenna design challenges.
• Existing IoUT research often uses standard helical antennas or wideband designs, which may not be optimal for underground environments.
• Soil properties like moisture content affect radio wave propagation, impacting antenna performance and signal strength.

Purpose of the Study:

• To propose and evaluate a narrow-band antenna design optimized for underground soil moisture sensing.
• To improve the reliability and accuracy of soil moisture estimation in IoUT applications.
• To demonstrate the effectiveness of antenna optimization for sensorless soil moisture monitoring.

Main Methods:

• Development of a narrow-band antenna specifically designed for underground deployment.
• Utilizing a LoRa-based system combined with machine learning for soil moisture estimation using signal strength.
• Conducting proof-of-concept measurements and full-wave simulations to analyze antenna performance in varying soil moisture conditions.

Main Results:

• A substantial difference in reflection coefficient (10 dB measured, up to 40 dB simulated) was observed with a 20% increase in soil moisture.
• The narrow-band antenna design demonstrated significantly improved signal level detection compared to standard approaches.
• The optimized antenna facilitates reliable radio sensing for sensorless soil moisture extraction.

Conclusions:

• Optimized narrow-band antennas are crucial for effective soil moisture sensing in IoUT.
• The proposed antenna design enhances the performance of LoRa-based systems for underground applications.
• This approach offers a promising direction for reliable and cost-effective sensorless soil monitoring.