A system and method to optimize plant growth with minimal labor. The system includes a set of sensors, a set of environment controlling equipment, and a processor programmed to acquire data from the sensors and manage operation of the environment controlling equipment based on the sensed data and operator input. The processor is programmed effectively as an artificial intelligence function that learns from sensed information and prior operator inputs to generate control equipment operating instructions that optimize plant growth. A learning network such as an A.I. enabled learning network may be deployed through the processor to gather sensed information directly and indirectly and instruct actuators of the control equipment, and to gather feedback from the operation of that equipment to observe changes in plant environment conditions through sensor information. That learned information is further developed through automated programming modifications of the deep neural network to refine actuator operations and enhance environment conditions.
