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From space with love: the launch of imaging technology into the greenhouse

Rasit Abay

Did you know that technologies used in space science can also be used in high tech greenhouses? That’s right. Our partner Rasit Abay, space situational awareness researcher and founder of Futurifai, is currently exploring how imaging technology can be used for crop registration and yield prediction. With this technology, a grower only needs to take a few photos of his greenhouse, and a machine will be able to help the grower count and measure the health of his crops. This is not a science fiction scenario in the far future; in fact according to Rasit Abay, this exciting technology could already be used by the end of this year.

1. What is imaging technology? Why is it relevant?

“With this technology, a machine can analyze a set of photos and give the grower advice, based on the information those photos provide. This helps the grower take critical decisions about, for example, his irrigation management, lighting, and harvesting. The interesting thing about this technology, is that the machine learns from previous experiences through advanced deep learning algorithms. Every time the machine analyzes a set of photos, the machine gets to know the greenhouse better, and develops customized advice for that specific greenhouse. Different machines in various greenhouses can also interact with each other and learn from each other. In that way, prediction models can be developed to help growers cultivate even more efficiently.”

2. You worked on imaging technology for the space sector first. What made you change to the horticulture sector?

“I believed it was time to introduce technologies from AI space research to the practical challenges of our daily lives. Many people find AI and new technologies quite intimidating and fear it will take away their jobs. I wanted to take away that fear. Technologies are already part of our daily lives and can actually help us with things we do not like to do (for example crop counting). We have robots on assembly lines and autonomous cars, and they all depend on AI and imaging technology to a certain degree. So why not use these technologies to bring fresh and sustainable food to the table? That’s why I decided to transfer my knowledge from space to the horticulture industry and started working with companies like Grodan.”

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3. What are the main challenges of using imaging technology?

“Machine learning is sensitive to data, so the quality and quantity of data is critical. There are many people who call themselves “AI experts”, but they do not have enough AI expertise and / or domain knowledge to transform the raw data to curated data before feeding to the machine. So partner only with experts who have a rich experience with this AI technology and domain expertise. Other than that, I don’t see many risks. I actually think AI and imaging technology will become part of our daily work and will help us make better decisions. By 2023, greenhouses could already be fully autonomous.”

4. If a grower wants to start using imaging technology, what is the first step to take?

“Key is that you can’t just install a machine, and AI will do the work for you. For these machines to work properly, you need “domain knowledge” (for example, define what healthy tomatoes look like). These technologies are expensive, and require serious hardware power. Companies like Grodan and Futurifai have the expertise to insert this domain and hardware knowledge into the software. So my advice is: work together with an expert to install this kind of technology in your greenhouse. Did you know that Grodan is also participating in developing this innovative technology further? It will be part of the e-Gro platform, so keep watching that space!

For more information about Futurifai, please visit: https://futurifai.com/

This story is part of the Gro-Hacks series, in which we ask partners and friends of Grodan about the lessons we can learn from their innovative entrepreneurial stories.

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