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From Guesswork to Field-Level Data
Once sensors, gateways, and a network are in place across the holding, the operation gains visibility that walked inspections and calendar-based routines cannot produce. These are the capabilities the hardware delivers.
Soil Moisture Monitoring
Buried probes report moisture, temperature, and nutrient conductivity at several depths, continuously, from as many points as the field warrants. Instead of one representative figure standing in for a whole block, you get the variation across it. That variation is what variable-rate application and precision agriculture decisions depend on.
Smart Irrigation Control
Pair soil moisture data with LoRaWAN controllers wired into existing valves and pumps. Irrigation then runs against what the root zone is doing rather than a fixed weekly schedule. The same controller logs every cycle, which gives you an abstraction record without anyone keeping a paper log.
Livestock Monitoring
Track herd location, activity, and building conditions across grazing land and housing. Battery-powered trackers and LoRaWAN environment sensors reach the distances a working farm actually spans, including outbuildings and field shelters well away from the yard and its power supply.
Microclimate Monitoring
Air temperature, humidity, rainfall, leaf wetness, and light measured at the crop rather than inferred from the nearest regional weather station. Frost protection, disease pressure, and spray window decisions all improve when the readings come from the block being managed.
Grain Store Monitoring
Temperature and humidity sensors at multiple points through the bulk, reporting while the silo sits closed. Hot spots and moisture migration appear as a trend on a chart rather than as a smell at the next manual check, which is usually weeks later.
Harvest Records
Combine in-field sensor history with store conditions to build a per-block yield record that survives the season. Yield variation stops being an impression formed at harvest and becomes a data set you can set against the soil, water, and weather readings from the same ground.
IoT Products for Agricultural Deployments
IoT in Agriculture Applications by Operation Type
Arable ground, protected cropping, and livestock units measure different things and sit in very different RF environments. The portfolio covers the sensing, connectivity, and control requirements across each of them.
Arable Crops
Soil moisture and temperature at depth across separate field blocks, with machinery and store monitoring alongside. Continuous readings support variable-rate application and give drilling and harvest timing a data trail rather than a recollection. Set against store conditions, the same history builds a per-block yield record that survives the season instead of an impression formed at the weighbridge.
Greenhouses
Dense sensing inside a small footprint: temperature, humidity, CO2, and light, with controllers driving vents, screens, and irrigation. A single LoRaWAN gateway typically covers an entire glasshouse range, including adjacent horticultural tunnels.
Vineyards
Microclimate monitoring at parcel level, where frost risk and ripening vary sharply over short distances and elevation changes. Orchards run the same profile, where per-parcel data supports frost intervention and harvest sequencing that a single site weather station cannot inform.
Dairy Herds
Building temperature and humidity, water trough and feed levels, and animal location across grazing blocks. Sensors run on batteries in buildings with no spare power and no structured cabling.
Poultry Units
Housed production where ventilation, temperature, and air quality sit inside tight tolerances and a control failure escalates within hours. Continuous monitoring with threshold alerts covers the gap between stockperson checks, including overnight. Pig units run the same sensing profile.
Grain Storage
Bulk temperature and humidity through the store, with controllers automating ventilation against measured conditions. Post-harvest readings accumulate into the records that farm assurance and buyer audits ask for.
Potato Stores
Long-term root crop storage holds temperature and humidity inside a narrow band for months, and a drift in either shows up as sprouting or condensation across the whole pile. Sensors through the store drive ventilation and refrigeration against measured conditions rather than a set schedule.
Irrigation Networks
Flow, pressure, borehole and tank levels, and leak detection across distribution runs. LoRaWAN covers dispersed abstraction and storage points without new cabling or a mains connection at each one, which is what makes whole-network water management measurable. Vibration and run-hour sensors on the pumps themselves turn a mid-season failure into a scheduled repair.
Multi-Site Holdings
Blocks held under different tenancies, worked by contractors, spread across a county. One gateway network and one data set covers ground that would otherwise be reported separately, with asset tracking showing which equipment sits where.
Why Farm Decisions Still Get Made on Incomplete Data
Most farms do not lack agronomic knowledge. They lack measurement. The agronomy is sound, the equipment is capable, and the decisions still rest on a handful of readings taken by hand from a few accessible points, days or weeks apart.
Each gap below is a direct consequence of running a holding without continuous field data. The third and fourth are the ones that stop most agricultural IoT projects before a single sensor gets specified.
Readings taken by hand are a snapshot, not a trend
A moisture figure from one probe on one afternoon tells you where that point sat at that moment. It does not show the direction of travel, which is the part that determines what to do next.
Irrigation on a calendar ignores what the soil is doing
Fixed schedules over-water in a wet week and under-water in a dry one. Water, energy, and pumping hours all go out regardless, and the crop absorbs the inconsistency.
Mobile coverage stops where the fields start
Rural cellular coverage across the UK is uneven, and the far corners of a holding are exactly where signal drops. Any monitoring plan that assumes a mobile connection at every sensor fails at the field boundary.
There is no mains power where the sensors need to go
Sensors belong in the middle of a field, at a borehole, or inside a store, none of which have a socket. Hardware that needs regular charging or a power run is hardware that does not get deployed.
Grain in store degrades quietly between checks
A store can sit closed for weeks. Heating and moisture migration develop slowly and are usually found once the damage is already priced into the load.
Assets spread across holdings disappear without anyone noticing
Trailers, reels, and implements move between rented blocks and contractors. Without tracking, absence is discovered when the equipment is next needed.
Compliance records get rebuilt from memory after the season
Abstraction volumes, store conditions, and application timings are reconstructed at audit from notebooks and recollection. Sensors that log continuously turn that reconstruction into an export.
Agricultural IoT hardware closes every one of these gaps.
How an Agricultural IoT Deployment Comes Together
Four stages take a holding from manual readings to continuous field data.
Sense
Soil probes, weather sensors, store monitors, level sensors, and trackers measure conditions at the points that matter, on schedules measured in minutes rather than site visits.
Most devices run on internal batteries for years, and solar-powered outdoor controllers cover the positions that need to actuate something as well as measure it. No mains connection is required at the sensor.
Connect
LoRaWAN gateways collect sensor data across the holding and backhaul it over cellular or fixed line from wherever the signal actually is, usually the yard or a building with a mast position.
LoRaWAN is the reason this works on farmland: it carries small packets over long distances at low power, so one gateway covers ground that would need dozens of cellular subscriptions. Where a site needs higher bandwidth, for cameras or edge processing, 4G and 5G industrial routers handle it.
Monitor
Data lands in the platform the operation already uses, whether that is a farm management system, an agronomy platform, or a cloud dashboard. EasyNet Technologies supplies the hardware layer and confirms the devices report correctly into it.
Thresholds and alerts are configured per sensor, so a store heating up or a trough running dry reaches someone while it is still a short job rather than a write-off.
Act
Controllers wired to valves, pumps, vents, and fans act on measured conditions instead of a schedule, either automatically or on confirmation from whoever is responsible.
The same data set produces the abstraction, storage, and assurance records that would otherwise be assembled by hand at the end of a season.
Put Field-Level Data Behind Every Agronomic Decision
Frequently Asked Questions
What is IoT in agriculture?
IoT in agriculture is the use of connected sensors, gateways, and controllers to measure field, crop, livestock, and storage conditions continuously and act on them. Devices measure variables such as soil moisture, temperature, humidity, water flow, and asset location, then transmit readings over low-power networks such as LoRaWAN or cellular to a platform where the data drives irrigation, ventilation, and management decisions. It is the hardware layer underneath smart farming and precision agriculture.
What is precision agriculture?
IoT in agriculture is the use of connected sensors, gateways, and controllers to measure field, crop, livestock, and storage conditions continuously and act on them. Devices measure variables such as soil moisture, temperature, humidity, water flow, and asset location, then transmit readings over low-power networks such as LoRaWAN or cellular to a platform where the data drives irrigation, ventilation, and management decisions. It is the hardware layer underneath smart farming and precision agriculture.
How do I get sensor data from fields with no mobile signal?
This is the most common starting position, and it is a gateway question rather than a sensor question. LoRaWAN sensors do not need mobile coverage; they talk to a gateway you place where coverage does exist, typically on a building in the yard. One gateway can cover several kilometres of open farmland, and only that gateway needs a backhaul connection. Where the yard has no usable signal either, the gateway can backhaul over fixed line instead.
How long do agricultural IoT sensors last on battery?
LoRaWAN sensors are built around multi-year battery life because they transmit small packets infrequently at low power. Actual life depends on reporting interval, temperature, and whether the device also actuates something. Reporting every 15 minutes rather than every minute makes a substantial difference, and for most agricultural variables the slower interval loses nothing useful. For positions that need to actuate as well as measure, solar-powered outdoor controllers avoid the battery question entirely.
What are the risks of IoT in agriculture?
Three are worth planning for. Hardware chosen for a pilot rather than for the environment fails on ingress, temperature range, or battery life once it is left in a field through a winter. Connectivity assumed rather than surveyed means sensors that never report. And data that lands somewhere nobody looks produces cost without decisions. All three are specification problems, which is why the scoping conversation covers coverage, power, and where the data is going before any hardware is ordered.
Is IoT sustainable for agriculture?
The measurable effect is on input efficiency. Irrigating against soil moisture rather than a calendar uses water and pumping energy only when the root zone needs it, and applying nutrients against measured variation puts less product on ground that does not need it. The hardware itself is low-power by design, running for years on internal batteries or solar. The honest limit is that sensors measure and inform; the reduction comes from acting on what they show.
What is the future of IoT in agriculture?
The direction is fewer isolated pilots and more whole-holding networks, because the connectivity problem is the one that has actually eased: LoRaWAN coverage now comes from a gateway on a farm building rather than a subscription per device, which changes the economics of instrumenting a second and third field. Autonomous machinery and aerial imaging sit alongside this and are supplied by specialists in those fields, not by us. What we expect to keep growing is the sensing and connectivity layer underneath all of it, because none of the rest works without measurement it can trust.
Can I connect IoT sensors to irrigation equipment I already own?
Usually, yes. LoRaWAN controllers interface with existing valves, pumps, and fans through dry contacts, pulse inputs, and RS485 or Modbus connections, so the existing irrigation or ventilation equipment stays in place and gains a control and logging layer. Water meters with pulse output can be read without replacing the meter. Where equipment is too old to expose any interface, we will say so during scoping rather than after delivery.