Irrigation controller using regression model

• US 6,892,113 B1
• Filed: 07/07/2000
• Issued: 05/10/2005
• Est. Priority Date: 07/07/2000
• Status: Expired due to Fees

• Current Assignee: Smart Irrigation Solutions Incorporated (Quarterhill Inc. (f/k/a Wi-LAN Inc.))
• Original Assignee: Aqua Conserve Incorporated
• Inventors: Addink, John, Addink, Sylvan
• Primary Examiner(s): Picard, Leo
• Assistant Examiner(s): ORTIZ RODRIGUEZ, CARLOS R
• Application Number:
  US10/009,867
• Time in Patent Office: 1,768 Days
• Field of Search: 137/78.2, 137/78.5, 137/624.11, 239/1.11, 239/14.1, 239/63, 239/64, 239/67, 239/69, 340/601, 700/282, 700/283, 700/284
• US Class Current: 700/284
• CPC Class Codes: A01G 25/16 Control of watering
• CPC Class Codes: Y10T 137/86389 Programmer or timer

Abstract

The present invention provides systems and methods in which an irrigation controller uses a regression model to estimate an evapotranspiration rate (estimated ETo), and uses the estimated ETo to affect an irrigation schedule executed by the controller. The regression model is preferably based upon a comparison of historical ETo values against corresponding historical environmental values, with the data advantageously spanning a time period of at least one month, and more preferably at least two months. Data for multiple environmental factors may also be used. The environmental factor(s) utilized may advantageously comprise one or more of temperature, solar radiation, wind speed, humidity, barometric pressure, and soil moisture. Values relating the environmental factor(s) may enter the controller from a local sensor, a distal signal source, or both.

Claims

1. An irrigation controller comprising:

a memory that stores a regression model, wherein the regression model is based upon a set of historical ETo values and a set of corresponding historical values for an environmental factor, the regression model running with optional input from a local sensor;

a microprocessor that applies a current value for the environmental factor to the regression model to calculate a current evapotranspiration rate (estimated ETo), wherein the irrigation controller uses the estimated ETo to determine an irrigation schedule executed by the irrigation controller.

2. The controller of claim 1 wherein the set of historical ETo values spans a time period of at least two days.

3. The controller of claim 1 wherein the regression model is further based upon a second set of historical values for a second environmental factor.

4. The controller of claim 1 wherein the regression model comprises a linear regression.

5. The controller of claim 1 wherein the regression model comprises a multiple regression.

6. The controller of claim 1 wherein the environmental factor is temperature.

7. The controller of claim 1 wherein the environmental factor is solar radiation.

8. The controller of claim 1 wherein the environmental factor is wind speed.

9. The controller of claim 1 wherein the environmental factor is humidity.

10. The controller of claim 1 wherein the environmental factor is barometric pressure.

11. The controller of claim 1 wherein the environmental factor is soil moisture.

12. The controller of claim 1 wherein the environmental factor is selected from a group consisting of temperature, solar radiation, wind speed, humidity, barometric pressure, and soil moisture.

13. An irrigation system comprising an irrigation controller according to claim 1, and said local sensor, which provides a signal corresponding to the value for the environmental factor.

14. An irrigation system comprising an irrigation controller according to claim 1, and a receiver that receives from a distal source a signal corresponding to the value for the environmental factor.