Smart farming gets sold to Indian farmers as drones and satellite dashboards. The version that actually pays on a five-acre orange orchard in Vidarbha or a sugarcane plot in western Maharashtra is much plainer: a few soil moisture probes, a small weather station, a valve that opens on its own and a phone that shows all of it. This article covers what the sensors can tell you, how to get their data out of a field with no signal, how to power them, what a farmer, an FPO or an agri-business can realistically deploy, what it costs as ranges, and where these systems fail.
What each sensor actually tells you
Sensors do not tell you what to do. They tell you what is happening, and someone or something has to turn that into an action. This table lists the ones worth considering and the decision each one supports.
| Sensor type | What it measures | What it helps you decide |
|---|---|---|
| Soil moisture (capacitive) | Water content at a set depth, usually 15 to 45 cm | When to irrigate and when to stop |
| Soil temperature | Temperature at root depth | Sowing timing, germination risk |
| Air temperature and humidity | Microclimate at crop height | Fungal disease risk, spray timing |
| Rain gauge | Rainfall at your plot, not the district | Whether to skip a scheduled irrigation |
| Wind speed and direction | Local wind | Whether to spray today |
| Leaf wetness | How long leaves stay wet | Disease pressure for grapes, pomegranate, orange |
| Water flow meter | Litres passing through a pipe | Whether the pump and valves are doing what the schedule says |
| Tank or well level | Water available | Whether tonight's irrigation will run dry halfway |
| Pump current sensor | Whether the pump is drawing power | Dry running, failed starts, electricity theft |
Soil NPK sensors are widely sold and, in our experience, the low-cost ones are not reliable enough to base fertiliser decisions on. A soil test from a laboratory once a season is cheaper and more trustworthy.
Automated irrigation is the use case that pays
The clearest return on any farm IoT system comes from irrigation. Water, electricity and labour are all spent on it, and all three are wasted when a pump runs on a fixed timer regardless of soil or rain.
A basic setup is a soil moisture probe per zone, a controller that opens a solenoid valve when moisture drops below a threshold and closes it when the target is reached, a rain gauge that cancels the run if it has rained, and a phone app that shows the schedule and lets the farmer override it. Drip and sprinkler systems make this straightforward because the valves already exist. Flood irrigation is harder to automate and the return is smaller.
The thresholds must be set per crop and per soil. The same moisture reading means something different in black cotton soil near Nagpur and in the lighter soils further west. Expect to spend the first season tuning.
Getting data out of the field: LoRaWAN or 4G
The connectivity choice decides most of the running cost and half of the reliability.
| LoRaWAN | 4G (cellular) | |
|---|---|---|
| Range | Several kilometres from one gateway in open farmland | Wherever there is a usable signal |
| Data volume | Tiny packets, a few readings per hour | Anything, including images |
| Power | Sensor nodes run months on a battery | Needs a solid power source, drains batteries fast |
| Monthly cost | None per node; the gateway needs one internet connection | A SIM per node, with rental every month |
| Failure mode | Gateway goes down, every node goes silent | One node loses signal, the rest carry on |
| Best for | Many cheap sensors across a large area | A few important points such as a pump house or a camera |
For a group of fields, one LoRaWAN gateway on a rooftop or a pole with a 4G backhaul is the usual design. It keeps sensor nodes cheap and battery-powered and puts the one expensive connection where there is power and signal. For a single pump controller near the road, a 4G module is simpler.
Power in the field
There is rarely mains power where a sensor needs to be, and where there is, it is on the agricultural supply schedule.
- Sensor nodes: a lithium battery with a small solar panel, sized to survive a week of monsoon cloud.
- Gateway and controller: a larger panel, a proper charge controller and a battery that can run overnight. This is the item most often undersized.
- Valves: latching solenoid valves draw power only when switching, which is what you want on solar.
- Pump control: the pump itself runs on the grid or a solar pump system; the controller only switches a contactor, and it must fail safe so a dead controller does not leave a pump running or a valve stuck open.
Who should deploy what
A single farmer with a drip system on a few acres gets the most from soil moisture probes, a rain gauge and automated valves, with alerts on WhatsApp. Skip the weather station; the district forecast is close enough at first.
An FPO or a group of farmers can share one weather station and one LoRaWAN gateway across many fields, which makes per-farmer cost sensible. A dashboard for the FPO office helps with advisory work and with recording data for schemes and buyers.
An agri-business such as a nursery, a polyhouse operator, a sugar factory's cane department or an exporter has more to gain from data over time: disease models, harvest predictions and traceability records that buyers ask for. This is where machine-learning crop analytics start to earn their keep, and where it makes sense to see our AgriTech industry page.
What it costs, as ranges
Prices vary with the hardware chosen and how many units you buy, so treat these as rough guides.
- A soil moisture node with a LoRa radio, battery and small solar panel: roughly ₹4,000 to 12,000 each.
- A LoRaWAN gateway with 4G backhaul, weather-proofed and on solar: roughly ₹15,000 to 40,000.
- A basic automatic weather station: roughly ₹20,000 to 1 lakh depending on sensors and build quality.
- A valve controller node per zone: roughly ₹8,000 to 25,000, plus the solenoid valves.
- Software: a ready dashboard from a hardware vendor may be included or charged monthly. A custom dashboard with alerts, irrigation logic and reports is a custom web application, roughly ₹2 to 10 lakh, and a farmer-facing mobile app adds to that.
A pilot on a few acres with a handful of nodes and a simple dashboard typically lands between ₹50,000 and 2 lakh. An FPO-scale deployment across many fields runs into several lakh, mostly hardware.
Where field IoT fails
- Dust and heat. Enclosures must be sealed, and electronics rated for 50 degree summers in a metal box in the sun. Cheap boxes crack in two seasons.
- Power. Undersized solar and batteries are the most common cause of silent nodes, especially in July and August.
- Connectivity. A gateway with a single SIM on a network that has no coverage in that village. Test the signal at the gateway location before buying anything.
- Probes moving. Soil probes get pulled out during weeding or ploughing, or the soil around them settles and the reading drifts. Mark them and recalibrate each season.
- Nobody maintains it. Panels need cleaning, batteries need replacing after a few years, and firmware needs updating. Budget for a visit every few months, or it becomes an expensive scarecrow.
- Trust. If the first alerts are wrong, the farmer will stop looking at the app. Run the system alongside the existing routine for a season before letting it control anything.
What we learnt building one
Farmers we worked with needed crop monitoring, automated irrigation and weather prediction. We built an IoT sensor network feeding machine-learning crop analytics and a web dashboard, using Python, Arduino, LoRaWAN, machine learning and React. The hardware was the smaller part of the effort. Most of the work went into making the data trustworthy, handling nodes that vanished for days and came back, and presenting results in a way that a farmer would act on rather than a chart an engineer would admire. We covered the general design of such systems in hardware integration and IoT smart systems and the analytics side in predictive analytics to forecast trends.
Where SailRight fits
We design sensor networks, controllers and the software behind them for farms, FPOs and agri-businesses in Maharashtra, starting with a small pilot rather than a large promise. See our IoT and hardware integration service or describe your fields and crop and we will suggest a realistic first step.
- IoT
- Smart farming
- AgriTech
- LoRaWAN
- Irrigation
- Maharashtra
