An AI-driven digital twinning platform to investigate and design viable hydroponic ecosystems for growing food plants while maintaining minimum carbon emissions. The system is powered by the Datastack framework connecting real-time performance data.
Satellite Data Mining
Digital Twin Design
Nebuli Space’s hydroponics ecosystem is a digital twin platform that utilises data streams from satellite images and sensors combined with research data. Such data streams include, for example, the planetary variables of soil water content, land temperature and vegetation biomass.
The satellites capture the soil water content at a 5cm depth with a 100m resolution. This data has previously been proven to be valuable in predicting droughts.
Traditionally, the roots of the plants growing in a hydroponics system are entirely submerged in water. However, our system works like a terrarium which requires minimum external input and does not use water to submerge the roots of plants fully but creates an environment where the water is recycled.
Soil moisture content data from satellites enable us to use minimum resources and predict enough water vapours within the system to allow maximum benefit without fully submerging roots in water. This planetary variable is analysed along with land temperature and vegetation biomass to get the optimal moisture level and temperature.
Alongside the satellite data, other resources, such as data from sensors in an existing hydroponics system, can also be integrated into the Nebuli Space platform. This is particularly helpful if clients wish to design a blueprint for an artificial farming environment (such as that on the moon).
Below are the key areas of interest that we are currently applying into the Nebuli Space platform:
A digital twin for a hydroponic ecosystem to forecast operational scenarios for optimal crop production.
Analyse existing conditions using satellite data (soil water content, land surface temperature and vegetation biomass).
Applying Augmented Intelligence and machine learning models to find optimal conditions which produce minimum carbon emissions.
Design and data models for planet colonisation (made-to-measure/custom environment).
Synthetic data creation for a monitoring system which uses sensors to generate real-time data streams.
Sustainable power sources for the ecosystem.
An intelligent and comprehensive digital twin platform for hydroponic ecosystems that looks at the viable conditions for growing food plants while maintaining minimum carbon emissions and reducing pollution.
We designed the platform to monitor data streams for oxygen and carbon dioxide in the air, artificial light source wavelengths (such as using blue light), the light and dark periods of light and the atmospheric pressure at which the hydroponics system is set up. The platform also integrates data for the nutritional content in water to allow for maximum benefit without using soil.