Intelligent pest monitoring equipment main buyer country

When I see a request aboutintelligent pest monitoring equipment main buyer country, I always want to clarify - are we talking about equipment for farmers or systems for agricultural holdings? In Shandong Lingyao, we initially relied on large farms, but life has shown that small farmers in Kazakhstan, for example, are more willing to take basic models with remote notification. Although in Europe the demand is different - they are willing to pay for integration with weather stations.

Why Russia has become a key market

In 2022, through the website lyzhihuinongye.ru, we received the first large order from the Krasnodar Territory - 15 sets of IP traps with automatic cutworm detection function. The client initially wanted a European analogue, but our engineer suggested customization for local pest species. We re-flashed it for the meadow moth - it turned out that this is the main problem in the Voronezh region.

I still remember how I had to redo the humidity sensors - in the Rostov region it turned out that at +35°C the cameras malfunctioned. I had to shield the cases and install additional coolers. Local agronomists said: 'You have equipment for a temperate climate, but we have dust and sand.' Now all models for the Russian Federation are tested in steppe zones.

Now 60% of exports go to the Russian Federation - not because it is cheaper, but because we have learned to make systems for specific regions. A locust tracking module was added for the Stavropol region, and enhanced protection against rodents was added in Tatarstan. By the way, the Kazakh market is adopting this approach - last month they delivered a batch to the Kostanay region with modifications for local turtle bugs.

Technical nuances that are not written about in the specifications

Our systemintelligent monitoringinitially I used Chinese sensors, but for Russian fields I had to switch to German sensors - they work more stably with differences from -20°C to +40°C. Although the cost increased by 15%, there were three times fewer refusals. It is especially important for grain farms in the Trans-Ural region - there the monitoring season begins with snow.

The most difficult thing is not recognizing pests, but calibrating them for different lighting conditions. In the Belgorod region, image processing algorithms had to be completely changed - it turned out that morning fogs “clog” the AI ​​model. I had to make separate settings for the forest-steppe zone.

Batteries are a separate headache. The advertisement says about 6 months of battery life, but in reality, at -30°C in the Novosibirsk region, the batteries run out in 2 months. We had to develop insulated heated boxes - yes, they are more expensive, but clients are not left without data during the critical period.

Integration with other systems - where we went wrong

At first they thought thatmain buyerswill want autonomous solutions. But large agricultural holdings like Miratorg required integration with their platforms. We had to completely rewrite the API - Russian ERP systems use outdated data exchange protocols. We spent six months adapting to 1C.

Another mistake is that they did not take into account the certification requirements. In 2021, we had to urgently obtain FSB certificates in cryptography - it turned out that data on field protection is considered strategic information. Fortunately, Shandong Linyao LLC already had experience working with government agencies on land reclamation projects.

Now we immediately test all new developments for compatibility with popular systems in the Russian Federation - from GLONASS trackers to Geoscan drones. By the way, there were difficulties with the latter - their software does not work well with Chinese chips, so we had to change the processor supplier.

Practical implementation cases

Last year, 28 monitoring stations were installed for a network of greenhouses in the Voronezh region. After 3 months, the client complained about false alarms - it turned out that spiders were entwining the lenses with cobwebs. We had to develop anti-web shields - a simple solution, but they don’t write about it in textbooks.

And in the Stavropol region they encountered vandalism - local teenagers dismantled the sensors 'for spare parts'. Together with the client, we had to develop a physical protection system - from Faraday cages to camouflaged installations in false stork nests. Reduced losses by 80%.

The most successful project is in Tatarstan, where we connectedsmart equipmentwith a drip irrigation system. When chafer larvae were detected, watering was automatically reduced - wet soil attracts pests. Potato yields increased by 12% without chemical treatment.

Evolution of customer requirements

If in 2020 they asked about basic functions - the number of cameras, communication range, nowbuyer's main countryThe Russian Federation requires predictive analytics. They want to not only detect pests, but also predict outbreaks 10-14 days in advance. We had to connect weather data from Roshydromet and a neural network to analyze long-term observations.

The demand for mobile solutions unexpectedly increased - not stationary stations, but portable complexes for visiting agronomists. They made a stripped-down version with a tablet and a portable camera - it turned out to be in demand in small farms in the Leningrad region.

Now we are testing the system for the vineyards of Crimea - there they need special recognition accuracy (phloxenum, leaf roller). Local technologists say that European analogues do not work well with Crimean grape varieties - the foliage is too thick. You may have to add thermal imagers.

Prospects and limitations

The main barrier is not the price, but a lack of trust in automation. Many agronomists prefer personal inspection of fields - they have to prove thatmonitoring equipmentdoes not replace a specialist, but expands his capabilities. We conduct demo days with trips to the fields - after they see the report with an accuracy of 94%, they usually agree to a test period.

The raw materials crisis has hit the supply chain - microchips have become 40% more expensive, but Russian customers are willing to pay for quality. Interestingly, in 2023, orders from oil and gas regions increased - Yamal, Khanty-Mansi Autonomous Okrug. They use our systems to monitor vegetation around deposits.

The next step is to integrate pest data with Shandong Lingyao LLC's automatic irrigation and fertilization systems. There is already a pilot in the Saratov region - when certain types of insects are detected, the composition of the feeding is automatically adjusted. It’s still a bit raw, but the potential is huge.