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Yes—a LoRa antenna buried in soil can help estimate moisture without a dedicated moisture sensor at every measurement point. Water changes the soil’s dielectric properties, which in turn changes radio behavior around the antenna. The method is experimental, however: useful readings depend on calibration for the specific soil, antenna, depth, and installation.
How can a LoRa antenna sense soil moisture?
Soil moisture affects dielectric permittivity—the property that describes how a material responds to an electric field. As water content around a buried antenna changes, the antenna’s electrical environment changes too. That can alter the radio signal’s phase, received signal strength (RSSI), reflection, or impedance.
A LoRa node can use one of those changes as a moisture indicator. It does not directly measure water content: it measures an RF effect and estimates moisture from a calibration that relates the effect to known soil-moisture readings. The Institut Polytechnique de Paris record for Chang et al. (2022) describes using LoRa signal phase readings to obtain information about soil permittivity, and placing LoRa-node antennas in soil to capture those readings.
What does a LoRa sensing setup measure?
Different designs use different RF observables. The best choice depends on the radio hardware and antenna design; a standard LoRa board does not necessarily expose every measurement needed.
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| Observable | What changes can indicate | Practical consideration |
|---|---|---|
| Phase | Changes in the signal’s phase as soil conditions around the antenna change. | Transmitter and receiver timing offsets can obscure the change. Chang et al. (2022) used a low-cost switch and a two-antenna design with a chirp-ratio method to cancel phase offset. |
| RSSI | Changes in received signal strength. | Signal direction is not universal: tests reported that moisture strengthened signals in sand but weakened them in clay. Increasing burial depth generally reduced signal strength. |
| Reflection or impedance | Changes in how the antenna is electrically loaded by the surrounding soil. | Burial changes soil loading and input impedance, so antenna matching matters. A narrow-band self-sensing antenna study reported about a 10 dB reflection change; its simulations showed a change of up to 40 dB when moisture content increased by 20%. |
The reflection figures are results from that antenna study (Škiljo et al., 2022), not a general performance guarantee for LoRa nodes. In particular, its reported simulated change should not be treated as a field measurement.
How accurate is sensor-free LoRa soil sensing?
Chang et al. (2022) reported an average soil-moisture-estimation error of 3.1% using commodity LoRa nodes. The field tests worked with a gateway 100 m away. These results show that radio-based estimation can be useful; they do not establish that every LoRa node, soil, or installation will achieve the same error or range. The reported figure is an average error, not a promise of accuracy at each depth or across different soil types.
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“Sensor-free” means the antenna’s RF response is used for sensing rather than relying on a dedicated moisture probe at each measurement point. It does not remove the need to establish what the radio readings mean for the target site. A reference probe or gravimetric measurements are prudent during calibration and validation.
How to build and calibrate a prototype
- Choose the RF measurement and hardware. Decide whether the design will use phase, RSSI, reflection, or impedance. Confirm that the radio and measurement setup can actually provide the chosen observable; phase sensing may need additional switching and antennas to handle timing offsets.
- Install the antenna in a controlled soil volume. Record its frequency, orientation, depth, enclosure, and matching arrangement. Keep these installation details consistent during calibration because they affect the RF response.
- Collect readings at known moisture levels. Record antenna measurements alongside a trusted reference, such as a calibrated probe or gravimetric measurement. Include the moisture conditions expected at the site rather than relying on one baseline reading.
- Fit and check the relationship. Use the paired radio and reference readings to estimate moisture for the target soil and installation. Check whether the relationship remains useful as moisture changes; do not assume a calibration transfers unchanged to another soil.
- Validate under field conditions. Check performance across the intended depths, temperatures, irrigation states, and soil zones before using estimates to make irrigation decisions.
What hardware and installation did a field system use?
The SOIL field system, described in 2022, used an underground LoRa-Feather, a 900 MHz external omnidirectional antenna kit, a 3.7 V, 2200 mAh lithium-ion battery, and an above-ground hub. Its sensor pairs were installed at 0.15, 0.30, and 0.50 m depths. In one described configuration, the node was buried at 0.30 m, with its antenna oriented horizontally toward a hub about 2 m away; measurements were logged at the hub.
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That system is a useful example of a field layout, not a universal build specification. For a prototype, a LoRa-Feather-class development board, external antenna, battery, and waterproof enclosure can provide a starting architecture. Add a reference moisture probe or another trusted reference during development so that radio-derived estimates can be checked rather than assumed.
What can make readings unreliable?
- Soil texture and salinity: Soil properties affect the dielectric environment and the signal response. Tests have found opposite moisture-related RSSI trends in sand and clay, so a model trained in one soil should not be assumed to work in another.
- Depth and geometry: Burial depth and antenna orientation affect the measured signal. Increasing depth generally reduced signal strength in buried-sensor tests.
- Antenna matching: Soil loading changes input impedance. An antenna that is not suited to its buried environment may behave differently from its intended or calibrated behavior.
- Radio measurement limits: Phase sensing must account for transmitter/receiver unsynchronization; other approaches require hardware capable of measuring the chosen RF quantity.
- Changing field conditions: Temperature, irrigation state, and differences between soil zones can affect the relationship between the RF reading and moisture. Validate across the conditions where the estimates will be used.
When does antenna-based sensing make sense?
It is most compelling when a project can calibrate and validate a particular antenna installation and wants to investigate moisture estimation without a dedicated probe at every point. It is a poor fit for plug-and-play irrigation control based on an uncalibrated LoRa link: signal changes alone do not reveal a universal moisture value. Keep a reference probe in the development process, and retain conventional sensing or field checks wherever an incorrect estimate could lead to harmful irrigation decisions.
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