AI can reduce the energy consumption of vertical farms by up to 27%

AI can reduce the energy consumption of vertical farms by up to 27%

Energy expenses are one of the major cost components of vertical farming. By using AI to harness the circadian rhythms of plants, vertical farm owners can reduce electricity consumption by up to 27%, further simulating a more natural environment for plant growth. According to the team’s calculations, a 10,000 m2 vertical farm growing romaine lettuce could reduce its energy bill by at least €1.08 million per year.

The term circadian rhythm comes from the Latin expression “circa diem” (“about a day”). The human body operates around a 24-hour cycle, where our bodily functions align with the brain’s master clock, preparing the body for sleep or activating the digestive system during the usual meal times.

And plants too. Linné’s flower clock ensures that most flowers open during the day and close at night. By positioning their leaves upward during the day, many plants capture more sunlight throughout the day, repositioning them for the night cycle.

In scientific terms, the circadian clock regulates several pathways, such as photosynthesis, seed germination, hypocotyl elongation, stomatal movement, flowering, and senescence. Light intensity and temperature are the main aspects of how plants react to their environment. When environmental conditions match the plant’s natural circadian rhythm, it can grow faster and avoid stress.

“In simpler terms, matching the environment with the plant’s internal clock helps maximize plant productivity. While you can’t always create ideal growing conditions in an open field, farms verticals present a perfect simulated growth environment.By introducing AI and computer vision, this environment can be even better adapted to the daily cycles of the plant, resulting in reduced energy costs and improved productivity. growth,” says Toma Zilinskyte, product development manager at Computer Vision start-up EasyFlow.

After segmenting the different parts of the plant, the team used a model of plant and leaf movement for the automated estimation of the circadian period. During a growth cycle, the team measured plant growth, leaf length change and plant branching.

“By constantly monitoring the factory environment with video cameras and using AI video analytics, we developed a pilot version of the classifier model to automatically identify the circadian rhythm of the factory,” says Toma Zilinskyte. .

According to Toma Zilinskyte, such a model can then be used to provide recommendations on plant watering, fertilizing, changing light conditions or introducing additional stimuli.

“Introducing AI would help farm owners produce higher yields and replant faster, which would help reduce energy expenditure by more than a quarter.”

“Studies of the circadian rhythms of plants were at the origin of the next green revolution and led to new developments, including the genetic engineering of plants. Computer vision presents another area where this research can be easily turned into everyday farming practice,” adds Toma.

EasyFlow will showcase its pilot circadian rhythm product titled EasyGrow at the VertiFarm exhibition September 27-29 in Dortmund, Germany.

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