Method and process for artificial intelligence to manage and optimize energy consumption across vertical farming and greenhouse hydroponic combined cycle agriculture

A method for artificial intelligence software to manage and optimize energy consumption across vertical farming and a greenhouse, comprising:

• wherein there are sensors throughout a nursery and the greenhouse;
• wherein there are internal sensors in the greenhouse;
• wherein the internal sensors measure air temperature, water temperature, time that lighting is on or off, flow rate, amount of carbon dioxide, humidity, nutrient solution, electrical conductivity of the nutrient solution and pH all within the greenhouse;
• wherein the nursery and greenhouse include an ability to change temperature;
• wherein heating and cooling is managed per type of plant and stage of growth;
• wherein internal sensors sense environmental conditions in the greenhouse and nursery;
• wherein there is an outdoor light measurement sensor;
• wherein the outdoor light measurement sensor will measure photosynthetic active radiation (“PAR”) outdoors;
• wherein other sensors will measure light;
• wherein data from the outdoor light measurement sensor is sent to artificial intelligence software;
• and
• wherein the artificial intelligence software determines how much light various plants in the hydroponic greenhouse needs in order for those plants to maximize the yield from those plants;
• wherein the solar battery sends battery percentage data to the artificial intelligence software;
• wherein the artificial intelligence software balances power going directly from the grid of solar panels to heating, cooling and pumps, and is balanced with charging the solar battery;
• and
• wherein the artificial intelligence software optimizes using sunlight for solar power and optimizes energy consumption in the greenhouse.

A method for artificial intelligence software to manage and optimize energy consumption across vertical farming and a greenhouse, comprising:

• wherein there are sensors throughout the vertical farm and greenhouse;
• are internal sensors in the greenhouse;
• wherein the internal sensors measure air temperature, water temperature, time that lighting is on or off, flow rate, amount of carbon dioxide, humidity, nutrient solution, electrical conductivity of the nutrient solution and pH all within the greenhouse;
• wherein the nursery and greenhouse include an ability to change temperature;
• wherein heating and cooling is managed per type of plant and stage of growth;
• wherein internal sensors sense environmental conditions in the greenhouse and nursery;
• wherein there is an outdoor light measurement sensor;
• wherein the outdoor light measurement sensor will measure photosynthetic active radiation (“PAR”) outdoors;
• wherein other sensors will measure light;
• wherein data from the outdoor light measurement sensor is sent to artificial intelligence software;
• and
• wherein the artificial intelligence software determines how much light various plants in the hydroponic greenhouse needs in order for those plants to maximize the yield from those plants;
• and
• wherein some of the changes the artificial intelligence software are made to both the vertical farm and the greenhouse include:
• controlling liquid pumps to change flow rates of water or other liquids, and
• controlling lights to change lighting,
• wherein the solar battery sends battery percentage data to the artificial intelligence software;
• wherein the artificial intelligence software balances power going directly from the grid of solar panels to heating, cooling and pumps, and is balanced with charging the solar battery;
• and
• wherein the artificial intelligence software optimizes using sunlight for solar power and optimizes energy consumption in the greenhouse.