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Removing human errors from tomato growing

When using robots to collect data in greenhouses, it's not just about speed or the consistency of the data collected but also the broader implications: the ability to gather data on a scale that only automation can reach with increased reliability, offering a clearer picture of the greenhouse environment. With this approach in mind, IUNU began developing its robotic platforms. Its first tomato-focused robot in Europe was recently deployed by Priva and installed at the Research and Demonstration Center, Proof, in the Netherlands. There, CEO Adam Greenberg and Program Manager Yoeri van der Laan also demonstrate the role of artificial intelligence (AI) in transforming raw data into actionable cultivation insights.

"We've seen what we can do for greenhouse crops," says Adam, referring to the company's activities in the lettuce market. Over the last few years, IUNU has installed vertical robots that move along the roofs of greenhouse facilities, providing growers with continuous insights into their crops through automated data collection and the Luna platform. After launching their tomato robot last year, they are now helping more and more tomato growers.

The IUNU robots don't simply record environmental parameters like light, CO₂, temperature, and humidity or capture images with their array of cameras. They enable a new level of understanding for growers, says Adam. "By using sensors and imaging systems that operate continuously, the robot generates a steady flow of data, which AI algorithms analyze to detect subtle changes and trends in crop health, growth rates, and environmental conditions. This constant monitoring provides an accurate and comprehensive overview of the crop, enabling growers to make real-time adjustments to optimize performance and improve forecasts."

This is where AI comes into play. Based on existing deployments, IUNU has a large dataset, crucial for creating algorithms that identify potential problems—preferably before they become significant issues.

The system's cameras capture both single images and low-frame-rate video, allowing for plant registration without disruption. Additionally, the cameras are adjustable, enabling users to inspect components without needing to change the setup.

The robot comes in both autonomous and manual versions. The autonomous version operates on a battery on an autonomous platform, while the manual version uses a battery that people can drive on a normal trolley. Designed with narrow dimensions similar to a standard trolley, the robot moves easily between crop rows.

Moving between crops
The robot installed at the Dutch demonstration and research center, Proof, enables visitors to see how its design will allow it to flip its arms and return on the same path, minimizing time and energy spent traversing aisles. This efficient design, coupled with an RFID-based tracking system, provides precise data on each plant's location and status. Operating in shifts from 8 a.m. to 7 p.m., the IUNU robot typically covers 20-25% of a 5-hectare greenhouse area each day. "The aim is not to measure 100% of crops but rather to provide a representative sample for trend analysis and projections," says Yoeri. He explains that growers might, for example, opt to scan every fifth row to ensure a complete overview.

The IUNU lettuce robot has been implemented in various regions, including Europe, the Middle East, and Australia, with a focus on both data reliability and scalability. The collected data feeds directly into IUNU's Luna AI platform, designed to turn raw greenhouse data into insights for decision-making. Through the Intelligent Setpoint Control, it is used to steer and make adjustments toward desired outcomes. It is also adaptable to various greenhouse steering solutions, meaning it can be integrated with existing systems. This compatibility allows data from the robot to be incorporated into dashboards growers already use or shared via API with third-party tools. According to Adam, this approach supports the industry's growing need for interoperability, where information can flow across systems for enhanced decision-making.

Priva trial
One of these systems is the Priva platform, which is why the tomato robot at Proof was purchased by the Dutch company. Last year, Priva formed a partnership with IUNU to focus on AI-driven cultivation. The robot is gathering initial validation data to assess its impact on crop care and harvesting. "What we truly look for is the added value for the grower, ensuring it helps them improve their business," says Dirk Prins with Priva. "The question is whether our solutions combined can strengthen each other."

Predictable and profitable crop
"Being in control of a predictable and profitable crop is the goal to work toward " Dirk adds. "What we see now is the growers themselves being the human intelligence: they take care of crop registration, check the cultivation, and know what to do as the crop develops and is steered. But due to upscaling and diversification of the greenhouses, that's a big challenge and no longer an option. Especially given the pressure on the labor market and the lack of skilled labor available, it's something that requires feedback with more data. What you're looking for are 'green eyes' assisting growers and owners in providing insights on your crop. We see the IUNU system has the potential to do so, as feedback of crop development caused by steering and caused by crop handling."

However, to be truly successful for the grower, the integration with Priva solutions should not just work flawlessly but bring added value, too, Dirk says. Priva has developed a cloud-based system and dashboard that allow growers to integrate third-party solutions, adding specific functions and services they need. "Our system works, their system works, but can they combined bring true added value to a grower? Can they together solve challenges growers deal with?" Dirk explains. This is why Priva decided to buy the robot and use it in their greenhouse trials. "We can test, and optimize integration, and we have our own data sets."

From small portions to big greenhouses
"The Luna system not only automates plant registrations and crop counts but also provides continuous, objective measurements, addressing one of the core challenges in greenhouse management—human error and inconsistency in data collection. With robots, the data becomes both more objective and scalable, moving from weekly spot checks to daily, comprehensive monitoring," Adam concludes. "Traditionally, growers could only check a small portion of crops weekly due to labor constraints, leading to incomplete snapshots of greenhouse conditions. Now, with our robot, a facility can monitor large portions of the crop area daily, resulting in more accurate forecasting and better planning for labor, resource use, and harvest timing. This shift to daily data is particularly impactful for fine-tuning crop steering and other high-precision horticulture techniques, allowing growers to focus their resources more effectively and respond faster to potential issues."

From monitoring and registering, the platform also brings yield prediction within reach for growers—and the possibility to steer toward desired outcomes. In the near future, updates will also enable more direct control over energy use. "Ultimately, the platform enables a shift from reactive to predictive greenhouse management, empowering growers to make informed decisions that align with their unique cultivation goals and challenges."

For more information:
IUNU
[email protected]
iunu.com