Dragino SE02-LB LoRaWAN Soil Monitoring for Smarter Irrigation, Salinity Control and Field Research

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Farmers

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Coimbatore

Pain Points

Manual soil checks limited visibility into moisture, salinity and changing field conditions.

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Limited Continuous Soil Monitoring

Periodic readings missed rapid soil changes after irrigation, rainfall and changing weather conditions.

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Manual and Infrequent Sampling

Frequent field visits increased effort, delayed decisions and created gaps in recorded soil data.

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Limited IoT and Cloud Access

Existing methods lacked long-range connectivity, remote dashboards and centralized soil data access.

Our Offerings

Deployed LoRaWAN® soil sensors for continuous monitoring, remote access and data-driven irrigation.

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Flexible Dual-Probe Deployment

SE02-LB sensors were installed at selected depths to compare soil conditions across plots and root zones.

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Moisture, Temperature and EC Tracking

The system monitored soil moisture, temperature and EC to assess water availability and salinity.

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Long-Range LoRaWAN® Connectivity

Sensor readings were sent over LoRaWAN® to gateways without wired links or individual cellular connections.

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Cloud Dashboard and Alerts

Live and historical data was displayed on cloud dashboards with alerts for abnormal moisture or EC levels.

SE02-LB sensors were installed at selected depths to compare soil conditions across plots and root zones.

The system monitored soil moisture, temperature and EC to assess water availability and salinity.

Sensor readings were sent over LoRaWAN® to gateways without wired links or individual cellular connections.

Live and historical data was displayed on cloud dashboards with alerts for abnormal moisture or EC levels.
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Our Deployment Our Deployment Our Deployment

Outcomes

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Smarter Irrigation Decisions

Continuous moisture data helped users schedule irrigation based on actual field conditions.

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Early Salinity Detection

Ongoing EC monitoring revealed rising salinity early, supporting timely corrective action.

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Reduced Manual Field Visits

Automated data transmission reduced routine sampling, field effort and manual recording errors.

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Improved Research and Learning

Students and researchers gained reliable field data for practical soil science and IoT studies.

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