sense -> infer -> decide -> act
Our goal is to facilitate plant growing, using technology to automate repetitive tasks.
Examples: automated irrigation, illumination, nutrient dispensing, etc.
Automation requires data and information about the plant and its environment. To collect data and extract information we need sensors.
soil moisture sensors
light sensors
air temperature and moisture sensors
etc.
Sensor data is used to infer plant conditions. This information feeds into decision making and leads to actions
irrigate - turn ON/OFF a water valve or pump based on the plant's needs of water
illuminate - turn ON/OFF an LED matrix based on the plant's needs of light
nourish and cure - turn ON/OFF a nutrients/medicine dispenser based on the metabolism of the plant
monitor -> act -> manage
Plant growing systems are connected to the Internet and send information to a database. A user interface is used to monitor plant conditions for individual plant growing systems.
Actions can be planned or triggered remotely using the online tool.
The aggregated information about active plant growing systems can be used for planning maintenance, system repairs and upgrades.
learn -> evolve
In the future, plant growing systems will be able to learn from each others, share optimized system parameters, suggest systems improvement.