Granted Patent B2

US 12,653,118 · App. 18/679,807 · Granted Jun 16, 2026

Inventor: Sanjay Kumar Rajpoot (Irvine, CA)

Assignee: Plant Culture Systems Inc.

A01G31/00A01G7/02A01G9/14

Abstract

Claims (106)

1 . A method for artificial intelligence software to manage and optimize energy consumption across a nursery and a greenhouse, comprising:

a grid of solar panels that provide solar power;

a solar battery that stores solar power from the grid of solar panels;

wherein there are sensors throughout the 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 the outdoor light measurement sensor will also measure light;

wherein data from the outdoor light measurement sensor is sent to artificial intelligence software;

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.

2 . The method of claim 1 , further comprising:

wherein the sensor sends data to the artificial intelligence software;

wherein the artificial intelligence software utilizes this data and makes adjustments to the conditions in the vertical farm and greenhouse in order to maximize yield of the plants.

3 . The method of claim 1 , further comprising:

a sensor to measure pH of soil the plants are in;

wherein the sensor sends data to the artificial intelligence software;

wherein the artificial intelligence software utilizes this data and makes adjustments to the conditions in the vertical farm and greenhouse in order to maximize yield of the plants.

4 . The method of claim 1 , further comprising:

a sensor to measure humidity in the nursery and greenhouse;

wherein the sensor sends data to the artificial intelligence software;

wherein the artificial intelligence software utilizes this data and makes adjustments to the conditions in the greenhouse in order to maximize yield of the plants.

5 . The method of claim 1 , further comprising:

a sensor to measure ingredients in a nutrient solution in the plants in the nursery and greenhouse;

wherein the sensor sends data to the artificial intelligence software;

wherein the artificial intelligence software utilizes this data and makes adjustments to the conditions in the greenhouse in order to maximize yield of the plants.

6 . The method of claim 1 , further comprising:

wherein the type of artificial intelligence is machine learning.

7 . The method of claim 1 , further comprising:

wherein the type of artificial intelligence is deep learning.

8 . The method of claim 1 , further comprising:

wherein the type of artificial intelligence is neural networks.

9 . The method of claim 1 , further comprising:

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.

10 . The method of claim 1 , further comprising:

wherein the greenhouse allows plants to be grown hydroponically.

11 . The method of claim 1 , further comprising:

wherein the greenhouse allows plants to be grown aquaponically.

12 . The method of claim 1 , further comprising:

wherein the sensors send data to the artificial intelligence software;

wherein the artificial intelligence software utilizes this data and makes adjustments to the conditions in the vertical farm and greenhouse in order to maximize yield of the plants;

wherein the type of artificial intelligence is either machine learning, deep learning or neural networks; 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.

13 . 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.

14 . The method of claim 13 , further comprising:

a grid of solar panels that provide solar power;

a solar battery that stores solar power from the grid of solar panels.

15 . The method of claim 13 , further comprising:

multiple sensors to measure carbon dioxide in both the nursery and greenhouse;

wherein the sensor sends data to the artificial intelligence software;

wherein the artificial intelligence software utilizes this data and makes adjustments to the conditions in the vertical farm and greenhouse in order to maximize yield of the plants.

16 . The method of claim 13 , further comprising:

a sensor to measure pH of nutrient solution the plants are in;

wherein the sensor sends data to the artificial intelligence software;

wherein the artificial intelligence software utilizes this data and makes adjustments to the conditions in the vertical farm and greenhouse in order to maximize yield of the plants.

17 . The method of claim 13 , further comprising:

a sensor to measure humidity in the nursery and greenhouse;

wherein the sensor sends data to the artificial intelligence software;

wherein the artificial intelligence software utilizes this data and makes adjustments to the conditions in the greenhouse in order to maximize yield of the plants.

18 . The method of claim 13 , further comprising:

a sensor to measure ingredients in a nutrient solution in the plants in the vertical farm and greenhouse;

wherein the sensor sends data to the artificial intelligence software;

wherein the artificial intelligence software utilizes this data and makes adjustments to the conditions in the greenhouse in order to maximize yield of the plants.

19 . The method of claim 13 , further comprising:

wherein the type of artificial intelligence utilized by the artificial intelligence software is either machine learning, deep learning or neural networks.

20 . 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.

Assignments (1)

Continuity (2)

References Cited (43)