Computer Vision to Boost Packaging Efficiency for Greenhouse Vegetables
Ivanisovo greenhouse complex has deployed a video analytics system to automate operational control on its packaging lines. The platform combines TRASSIR video surveillance technology with Matller computer vision algorithms.
High-quality packaging in greenhouse farming is a critical part of the production chain. It helps preserve product quality by protecting vegetables and greens from damage, moisture loss, environmental exposure, and pathogenic microorganisms. Packaging also simplifies transportation, storage, and stacking, reducing logistics costs. Just as importantly, branded packaging improves product recognition and supports consumer demand. That makes packaging efficiency a strategically important factor for controlled-environment agriculture.
Seeing Every Detail of Production Operations
Ivanisovo greenhouse complex, located in the city of Elektrostal in the Moscow region, deployed an automated operations tracking system on its packaging lines using TRASSIR video surveillance and Matller computer vision algorithms. Traditionally, greenhouse operators measured only the collective output of a shift or work team. That approach made it impossible to evaluate the workload of individual workstations or the efficiency of specific operations. The company needed to understand how workloads were distributed among employees and identify the root causes of operational losses.
“We could see the final shift result, but we could not accurately determine where productivity losses occurred or which operations became bottlenecks. Management decisions were often based on observation and the experience of supervisors,” said Nikita Makarov, project manager at Ivanisovo greenhouse complex.
To make precise operational decisions, the company needed objective data covering all processes. The pilot project was launched on three active packaging lines. The system had to account for multiple operations, constantly changing shift compositions, and continuously updated workflow data. After just two months of using the system, the company reported higher efficiency across production operations. Overall packaging productivity increased by as much as 20%.
Process Analytics and Faster Responses to Deviations
The greenhouse complex gained the ability to analyze internal packaging workflows using digital operational data. That matters both for process analysis and for workforce management.
“Enterprises need transparent and reproducible operational tracking that can serve as a reliable foundation for production management and compensation systems,” said Alexey Alekseyev, head of the AIoT division at TRASSIR.
The company has now begun collecting information about every operation performed on the line within a dedicated analytical environment. This becomes especially important during seasonal demand swings, when workloads on production lines and employees can change sharply. Shift managers can monitor real-time conditions at workstations and respond immediately to deviations.
“Once digital operational analytics appears, discussions become much more concrete: you can clearly see deviations, understand the causes of performance declines, and identify real opportunities for improving efficiency,” said Alena Marchenko, project manager at Matller.
“Projects like this should not be viewed as simple IT deployments. Technology provides the data, but the real effect appears when a company changes its management practices and begins systematically working with production analytics,” said Nikita Makarov, project manager at Ivanisovo greenhouse complex.
A New Management Model
Full transparency of production operations, even when shift sizes and line workloads change, helps digitize not isolated production segments but the entire greenhouse production process. The computer vision system is used to analyze operations and identify problematic areas.
“Notably, the project required ongoing management work rather than a one-time launch. In other words, this is not a ‘boxed product,’ but a digital tool that must become part of day-to-day production practice,” emphasized Alena Marchenko, project manager at Matller.
The video analytics project at Ivanisovo greenhouse complex demonstrates how agricultural producers can increase labor productivity and improve operational efficiency without major capital investment. That is especially relevant amid labor shortages and expensive borrowing conditions. Russian AIoT and video analytics solutions are helping address those challenges through computer vision, data analysis, and measurable management processes.
Today, greenhouse fruit and vegetable production is one of the most technologically advanced sectors of Russian agriculture and among the fastest adopters of digital technologies. Going forward, the new packaging video analytics system will be integrated with smart farming systems. That will make it possible to monitor not only production and harvesting, but also packaging, transportation, warehousing, storage, and delivery processes. Over time, such platforms could find demand not only in Russia but also in other countries developing greenhouse agriculture and looking for affordable end-to-end management systems.
