Smart irrigation system

When you hear “smart irrigation system,” the first thing that comes to mind is expensive sensors and complex algorithms. But in practice, it all starts with a simple question: how much water do plants really need at 5 am at +14°C? We at Shandong Linyao Intelligent Agriculture Technology LLC have gone from installing ready-made solutions to creating hybrid systems that combine local weather data and the behavior of the root system.

Why standard solutions do not work in Russian conditions

In 2019, we tested an imported system with preset climate zones. Three weeks later, a farmer from the Krasnodar region complained about excessive water consumption on the slopes. It turned out that the algorithm did not take into account the water flow with a slope of only 5° - the drip lines worked as on the plain. I had to manually adjust the irrigation map, although the documentation stated 'automatic relief detection'.

We are now inShandong Linyao Intelligent Agriculture Technology Co.,LtdWe use a combination of TDR probes and locally produced rain gauges. Cheap Chinese analogues seemed profitable at first, but their readings fluctuated as soil mineralization changed. We had to develop calibration tables for different types of chernozem.

An interesting point: sometimes 'smart' irrigation requires inexpensive solutions. For example, for vineyards in Crimea, we installed mechanical valves with an electric drive - they can withstand lime deposits that kill imported sensor valves during the season.

How to integrate data without overloading your infrastructure

Our project in the Rostov region showed: farmers are willing to put up with inaccuracies, but not with constant breakdowns. We used radio modules instead of Wi-Fi - communication stability increased by 40%, although we had to independently negotiate the frequencies.

Here's a technical detail that is rarely considered: when installingsmart irrigation systemIt is critical to measure the electrical conductivity of the soil before installation. Once we installed sensors in a salt marsh area, and the system constantly 'saw' a lack of moisture due to distorted readings.

Now on the website https://www.lyzhihuinongye.ru we publish cases with real numbers. For example, for a greenhouse farm near Voronezh, it was possible to reduce water consumption by 30% not through complex algorithms, but simply by dividing irrigation zones by type of substrate.

Equipment that really works for years

After several unsuccessful experiences with 'smart' controllers, we switched to a modular architecture. The main unit remains simple - time relays and float valves, and sensors are connected as needed. This reduces the cost of implementation by 25-30%.

In lineShandong Linyao Intelligent Agriculture Technology Co.,LtdNow there are filters with backwashing that can be cleaned without stopping watering. Trifle? But it was precisely because of downtime during filter cleaning that tomato seedlings in one of the farms died last season.

An important point: we have stopped using common plant databases. For each crop, we draw up an irrigation map experimentally - for example, for blueberries in the Leningrad region, the intervals turned out to be 15% shorter than in the recommendations.

Economics vs. agronomy: which parameter is more important

Often customers ask for 'maximum automation', but in practice it turns out that manual control during critical periods gives better results. We leave the option to redefine the algorithm manually - this reduces the load on the system.

When designingsmart agricultureWe now always take into account the human factor. The last case: in Tatarstan, an agronomist is used to visually assessing soil moisture, so we added not only numbers to the interface, but also a color indication using his method.

An interesting conclusion: sometimes it is cheaper to install an additional backup pump than to improve the load prediction algorithm. Especially in areas with unstable power supply.

What you can't miss when switching to smart irrigation

A mandatory step that many people skip is training technical staff. We have developed three-day courses where we explain not only how to work with the system, but also how to interpret its readings. Newbie mistake: blindly trusting sensors when there are obvious signs of overflow.

One more nuance: when integrating with fertigation systems, you need to separately adjust the electrical conductivity of the solution. Twice faced with the fact thatsmart irrigation systemworked correctly with water, but malfunctioned when supplying fertilizers.

Now we recommend starting with a pilot zone of 2-3 hectares, even for large farms. This allows you to work out the interaction of equipment with specific soils. We use data from such test sites to refine the equipment.

A future that is already being tested in the fields

We are experimenting with forecasting based on satellite images, but it is too early to talk about stable results. This year we are planning to test neural networks to predict plant diseases based on watering patterns.

Based on https://www.lyzhihuinongye.ru, we collect feedback from existing clients - this helps improve controller firmware. For example, last month they added a function for recording wind erosion after complaints from the steppe regions.

Key lesson: there is no universalsmart irrigation system. Each solution requires adaptation to a specific field, culture and even personnel qualifications. Sometimes a simple timer with a couple of sensors is optimal, rather than a complex climate computer.