Vertical Farming Optimization
Make vertical farms even more cost efficient with EasyGrow – circadian rhythms monitoring system.
Vertical farming is an innovative and promising solution that helps to save space and get a harvest all year round, but requires a large amount of energy consumption.
By implementing plant circadian rhythms detection with Machine Vision, we can help to reduce the energy consumption from 10 to 27% yearly, depending on a plant specie.
Why circadian rhythm of Your plants matters?
Circadian rhythm prepares the plants for upcoming challenges by anticipating daily environmental and seasonal changes.
Circadian clock regulates multiple pathways such as photosynthesis, seed germination, hypocotyl elongation, stomatal movement, flowering and senescence.
Plant defense responses such as various biotic and abiotic stresses are also fine tuned by circadian rhythm.
Knowledge of circadian clock machinery will help in the crop domestication as well as will enhance the growth and fitness of plant.
Why us?
Cost efficient
Save about 10 percent of unnecessary costs per year
Maximized yield
Plants are fertilized according to their phases, the harvest is achieved faster
Sustainability
Water and electricity are consumed only as much as the plant really needs
Reduced losses
Plants are monitored so it is easier and faster to replant unsprouted ones
Workflow
The collected data will allow You to make better decisions and optimize farming. The growth process is made more efficient, and the yield is obtained with higher quality and faster, therefore it allows to plant the new crops faster than usual.
EasyGrow can help to optimize vertical farming not only by saving electricity, gas, or other energy sources but also water and fertilizers, thus reducing costs even more.
Infrastructure setup (lights, cameras)
By using segmentation models (segformers), the plant is segmented so that we can see the movement of the plant: measure the movement of the leaves, blooming, the change in the length of the leaves, the spreading of the plant.
This data is converted into numerical values and stored in the database.
According to the numerical values, a classification model is created, which is able to recognize different cycles of the circadian rhythm (by evaluating the numerical values of plant growth and movement).
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