Artificial Intelligence applications into Aerobloom
IoT will use sensors to measure the environmental conditions, water quality, and energy consumption of the Aeroponics facilities. IoT will use actuators to control the devices, such as feeding, lighting, ventilation, irrigation, and harvesting.
Machine learning and processing of multi-faceted collected data will be used to
increase yield efficiencies and reduce environmental impact and reduce natural
The collected Data will be processed by the AI engine to determine the combination of highest yields, and most efficient management of resources.
Our knowledgeable team will institute the AI guidance and provide additional human feedback to verify intended results, and give the non-sensor data to the AI engine in order to provide the highest yields.
Aerobloom will use predictive analytics as determined by A.I. processing to determine efficient plant growth. Operational equipment Predictive analytics will also reduce downtime and maintenance cost. This will allow nearly uninterrupted plant growth. The predictive nature will also allow optimal schedules for required maintenance, with maintenance shifts and skips when predictive analytics dictates.