Optimal Deployment of WSN Nodes for Crop Monitoring Based on Geostatistical Interpolations

Area of Science:

• Agricultural Engineering
• Precision Agriculture
• Environmental Monitoring

Background:

• Accurate soil moisture monitoring is crucial for optimizing potato crop yields and water management.
• Traditional methods can be costly and labor-intensive, limiting spatial and temporal resolution.
• Wireless Sensor Networks (WSNs) offer a scalable and cost-effective solution for field-scale environmental monitoring.

Purpose of the Study:

• To develop and validate an integrated method for estimating soil moisture in potato crops using a low-cost wireless sensor network (WSN).
• To determine the optimal number and placement of WSN nodes for accurate soil moisture characterization.
• To provide a cost-benefit analysis of the proposed WSN strategy for spatio-temporal soil moisture analysis.

Main Methods:

• Implementation of an 11x11 node wireless sensor network (WSN) across a potato crop field.
• Application of the Kriging interpolation technique to generate soil moisture estimation maps from WSN data.
• Experimental validation using a perfect mesh approach to identify optimal node density and placement.

Main Results:

• The study identified that 25 WSN nodes were optimal and sufficient for characterizing soil moisture in potato crops.
• The proposed method achieved estimation errors of less than 2% for soil moisture.
• A strategy for selecting the number of WSN nodes was developed, correlating node count with margin of error.

Conclusions:

• A low-cost WSN with optimal node configuration provides accurate and reliable soil moisture estimation for potato crops.
• The developed strategy enables efficient spatio-temporal analysis of soil moisture, supporting precision agriculture practices.
• The findings offer a practical and cost-effective solution for farmers to improve water management and crop productivity.