A soil moisture sensor is a device that continuously measures water in the root zone, so precision agriculture can irrigate when the crop needs it rather than by the calendar. Readings from several depths reach one dashboard wirelessly; below a set threshold a valve or pump opens, closing at the target.
How are irrigation decisions made today?
On many farms, irrigation is still decided by the calendar, by when the neighbour irrigates, or by walking out and feeling the soil. In experienced hands these methods work up to a point, but they cause losses in two directions. One plot gets more water than it needs: water and pump electricity are wasted, and surplus water carries nutrients below the root zone. Another plot has already gone into stress, and by the time anyone notices, yield has taken the hit.
The larger the farm, the bigger the problem. Plots with different soils, slopes or sowing dates do not need the same water, and a single irrigation schedule cannot suit them all.
Walking every plot every day is not realistic. The surface can look dry while the root zone is still moist, or the other way round. A soil moisture sensor replaces that guesswork with measurement.
The cost of irrigating without measuring
Agriculture is by far the largest user of water, which turns every inefficiency into a large-scale loss:
FAO's AQUASTAT data shows that at global level, 69% of freshwater withdrawals go to agriculture, 19% to industry and 12% to municipal use. (FAO AQUASTAT – Water use)
The resource is also shrinking. According to FAO's announcement of the 2025 AQUASTAT Water Data Snapshot, renewable water availability per person fell by a further 7% over the past decade. As water becomes more expensive and more restricted, sending it only to the plots that need it becomes a question of both cost and continuity.
Beyond the water itself, poor irrigation affects the crop. FAO's SDG 12.3.1 Global Food Losses indicator estimates that 13.3% of food was lost between harvest and retail in 2023, with fruits and vegetables showing the highest losses at 25.4%. Irrigation does not cause all of this, but produce from crops that were water-stressed or over-watered carries its quality and shelf-life problems into every later stage. After harvest, cold chain monitoring takes over, tracking product temperature from store to shelf.
The moisture and temperature history from your sensors is also valuable for predicting how much crop the season will bring. We cover the method that combines this data with drone imagery and field sampling in drone crop yield estimation.
How soil moisture sensors work: the main types
Soil moisture sensors measure one of two things: the volumetric water content of the soil, or the soil water tension, meaning how hard the plant must work to draw water. The right choice depends on the crop, the soil and the budget.
| Sensor type | What it measures | Strength | Watch out for |
|---|---|---|---|
| Capacitance (dielectric) | Volumetric water content | Maintenance-free, long battery life, suits wireless nodes | Needs calibration for soil type; salinity can affect readings |
| Tensiometer | Soil water tension | Shows directly how hard the plant must pull water | Needs regular servicing; limited range in very dry soil |
| Resistance-based (gypsum block etc.) | Soil water tension (indirect) | Low cost | Slow response; calibration can drift over time |
Capacitance sensors are the most common choice in precision agriculture projects because they pair easily with wireless sensor nodes. Even so, the type should be decided after a crop and land survey.
Sensor placement: where and how deep?
A sensor is only as useful as its location. An expensive sensor in the wrong place tells you less than a simple one in the right place.
- Divide the land into uniform zones. Areas with the same soil, slope, crop and irrigation line count as one zone, and each zone gets at least one measurement point. A GIS layer holding parcel boundaries, the soil map and irrigation lines on one map makes the split easier; our GIS guide for municipalities shows how organisations build such a layer.
- Choose a representative point. The measurement point should reflect the zone's average, avoiding extremes such as field edges, hollows or the spot right next to an irrigation line. In drip irrigation, sensors sit at a consistent distance from the emitter.
- Monitor the root zone at several depths. Sensors are installed at different depths, for example 10, 30 and 60 cm. The top sensor shows irrigation has started, the middle one that water has reached the roots, and the bottom one whether water is escaping below the root zone.
- Calibrate. Capacitance sensors must be calibrated for soil type; the same reading means different moisture in clay and in sand.
- Set thresholds by crop. The lower threshold that starts irrigation and the upper one that stops it depend on the crop, growth stage and soil, and are tuned during the season with real data.
- Add weather data. The site's own temperature, humidity, rainfall and wind data allow irrigation to be postponed after rain and evaporation losses to be estimated.
Turning sensor data into decisions
Once the sensors are in, the real value comes from learning to read the curves. Right after irrigation, moisture at the top depth rises quickly; if the middle depth also rises within a few hours, water has reached the roots. If the bottom sensor climbs sharply as well, the irrigation run is too long and water is draining below the root zone, and splitting the same volume into shorter, more frequent runs is usually more efficient. Conversely, if the middle depth does not respond at all, water is not reaching the roots.
The "staircase" pattern through the day is another useful signal: moisture falls step by step during daylight hours while the crop draws water, then holds steady overnight. The steepness of those steps shows the crop's water use at that stage and helps set the irrigation interval. If the steps flatten while moisture is still low, the crop may be starting to suffer stress. Rather than spotting such deviations by eye, you can turn them into automatic alerts with anomaly detection.
The goal of the first season is less full automation than learning these patterns and settling thresholds for your own land. In the second season, once thresholds are reliable, switching irrigation control to automatic gives far more dependable results; we cover that step, including valves, pumps and line pressure, in irrigation automation and remote monitoring. End-of-season plot reports show which zones were over- or under-irrigated and feed directly into next year's plan.
From field to dashboard: wireless links
Most of a field has no power or internet, so sensor nodes run on batteries and send data over low-power wireless networks. A single LoRaWAN gateway covering several kilometres may serve the whole farm; NB-IoT needs no gateway wherever the operator's network reaches. How sensors, network and dashboard are chosen together is covered in our guide to choosing a remote monitoring platform.
The Ericsson Mobility Report notes that technologies such as NB-IoT and Cat-M continue to be rolled out worldwide for low-cost devices that need long battery life. Coverage depends on terrain and obstacles, so the choice should be made by measuring on site; we compare the options in our LoRa vs NB-IoT vs cellular guide.
Enclosures must also withstand dust, water and sun; our IP rating explainer shows why a sensor buried in soil and exposed to irrigation water calls for IP67. All our sensor, connectivity and field-device guides are gathered in the IoT & Hardware hub.
The same sensor and network infrastructure serves livestock too; we explain heat and health tracking with collars, pedometers and barn climate sensors in our guide to the livestock monitoring system.
The same measurement logic matters even more under cover, where root-zone moisture is managed alongside air temperature, humidity and CO2. We cover the chain from sensor to vents and fertigation in our guide to smart greenhouse automation.
Smart irrigation is often a farm's first digital step, but not its only one. We explain the order in which records, herd and post-harvest layers are added in our guide to farm digital transformation.
How we handle this at Digital Bridge
In our precision agriculture IoT and smart irrigation projects we design the sensor network for your land, build the wireless infrastructure and commission irrigation control. Soil moisture, pH and soil temperature sensors are placed at depths that cover the root zone, and a micro weather station measures the site's own climate. When moisture drops below the threshold a valve or pump opens and closes again at the target level; scheduling rules can shift irrigation to hours with lower evaporation or to a cheaper electricity tariff. The moisture status of every plot and any fault alerts appear in the mobile app; every action is logged, and water use per plot is reported at the end of the season.
Because the same team develops the sensors, the data transmission devices and the dashboard (see our IoT product development process for the stages), there is no gap in responsibility between field installation and software; our hardware capability is described on the device manufacturing and IoT page. Several farms or pump stations can be followed from one dashboard using our remote monitoring platform. If you also want aerial views of the whole farm, we can combine the project with our drone data processing service; our drone NDVI analysis guide explains how to read crop health maps alongside soil moisture data. For other solutions for farming businesses, see our agriculture and livestock page.
The technical feasibility study for hardware projects is free of charge. We do not sell ready-made packages: after a land survey you receive a written proposal covering scope, phases and cost. We work in every province of Türkiye, which suits agribusinesses and international food companies sourcing from several regions of the country.
Next step
To get started, sketch a rough map dividing your land into zones by soil, crop and irrigation line, and note how often and for how many hours each zone was irrigated last season. That sketch tells you how many measurement points you need and where the first sensors should go. Request a land survey and we will check the sketch with you in the field.