The CEAD technology currently being tested at a cannabis research and development center in Arizona monitors operational and environmental systems including plant nutrition, growth rates, life cycles, and predictive pest outbreaks. In addition, it keeps a log of all movements made by the cultivation team and gathers data in regards to specific feeding and pruning schedules.
The machine learning capabilities take advantage of all of the data to continually expand it’s knowledge base. Initially, the AI system operates off of base assumptions. At the point the machine begins to learn all operational aspects of the cultivation, it then begins to present and suggest a list of options to the cultivator to prevent potential forecasted issues based on the data.
With AI and machine learning, one can now predict the exact density of a particular crop by analyzing specific data, giving the significant advantage of forecasting and preventing common issues, such as mold and fungus due to specific environmental conditions. This would enable a profound new level of control and data analytics for the cannabis space, all from an easy-to-use interface. It would provide a significant platform for interpreting the extreme nuances that relate to each of the thousands of strains being cultivated and give cultivators the ability to further isolate the benefits of the plant.
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