Polygon smart agriculture

What issmart agriculture? Many people are now talking about this, showing beautiful graphs and promising a revolution. But so far, in my opinion, we are only at the initial stage, trying to find the right balance between advanced technologies and practical feasibility. I often see a passion for sensors and drones, but they forget about the most important thing - understanding the needs of a specific field, a specific culture. It's rare that all of these tools actually work as a single, coherent system that solves real problems.

From theoretical schemes to real problems

At the initial stage of working withsmart agricultureWe are faced with a common problem: the desire to implement as many technologies as possible without having a clear understanding of which ones are really needed. For example, the customer really wanted 'smart' irrigation systems, but there was no analysis of soil moisture, type of crops and terrain features. The result is expensive equipment that does not live up to expectations. Why do you need a complex sensor if you can irrigate effectively simply by carefully observing the field and taking into account weather conditions? Essentiallysmart approachdoes not mean automating everything, but optimizing processes based on data.

Sometimes it can be difficult to convince a farmer to invest in new equipment. He is accustomed to traditional methods, and it is difficult for him to assess the potential impact of implementationautomated irrigation control systemsorcrop condition monitoring. Here it is important not just to demonstrate the technical characteristics of the equipment, but to show specific figures: how much water can be saved, how to increase productivity, how to reduce fertilizer costs. We need a simple, understandable model that demonstrates economic efficiency.

Integration experience and emerging difficulties

We worked on several projects where it was necessary to integrate equipment from different manufacturers. This is always a difficult task because the systems are often not compatible with each other. For example, the integration of soil moisture sensors, data from a weather station and an irrigation control system requires the development of proprietary software that will collect and analyze information. Shandong Linyao Intelligent Agriculture Technology Co., Ltd. specializes in such comprehensive solutions, and we constantly face challenges related to interoperability and standardization.

Another problem is data quality. Sensors may give inaccurate readings due to malfunction, improper installation, or the influence of external factors. It is important to have a data quality control system and regularly calibrate equipment. Otherwise, making decisions based on incorrect information can lead to serious consequences.

Example of successful implementation: Optimization of fertilization

In one of the projects, we introduced a crop condition monitoring system and an automated fertilizer application system. We used drones to capture images of fields and then analyzed those images to determine which areas needed additional fertilizer. The fertilizer application system was connected to a central computer and automatically dosed fertilizer based on plant needs. The result is a 15% reduction in fertilizer costs and an 8% increase in yield. This example shows thatsmart agriculturecan actually be cost effective.

It is important to understand that successful implementationsmart technologiesis not just a purchase of equipment, but a comprehensive process that includes analyzing the farmer’s needs, developing an individual solution, integrating equipment and training staff. Without this, all your investments may be in vain.

First failures and lessons learned

Not all projects end successfully. I remember one case where we installed an automatic irrigation control system in a field, which turned out to be too complex for the local staff. They were unable to master the operation of the system, and it remained idle most of the time. We realized that it is important to take into account the level of qualifications of personnel when choosing equipment and develop clear and convenient instructions for them.

We also made a mistake in assessing the impact of weather conditions on the efficiency of the system. We did not take into account that the region often experiences strong winds that interfere with the operation of drones and sensors. It was necessary to develop additional measures to protect equipment from adverse weather factors. This experience shows that it is necessary to take into account all possible factors that may affect the operation of the system.

Conclusion: The path to efficient farming

Polygon smart agriculture– this is not just a fashionable word, but a real trend that changes the idea of modern agriculture. There is still a lot of work ahead, we need to develop technologies, develop standards and train specialists. But I'm sure thatintelligent solutionswill become an integral part of efficient and sustainable agriculture. We, at Shandong Linyao Intelligent Agriculture Technology LLC, continue to move in this direction and are ready to share our experience with other market participants.