Irrigation controller using estimated solar radiation
View Patent ↗An irrigation controller ( 200 ) receives temperature data, and at least partly derives an estimated solar radiation value from the temperature data. A regression model stored in a memory ( 220 ) of the irrigation controller ( 200 ) operates upon a data point from the estimated solar radiation to estimate an evapotranspiration rate, which is used to affect an irrigation schedule executed by the controller ( 200 ). 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 two days, and more preferably at least one month. Data from one or more environmental factors may also be used, including especially estimated solar radiation, temperature, wind speed, humidity, and soil moisture, and so forth. Values relating the environmental factor(s) may enter the controller from a local sensor ( 240 ), a distal signal source, or both.
1. An irrigation controller comprising:
a microprocessor that receives temperature data, and at least partly derives an estimated solar radiation value from the difference between the temperature data collected from a non-shaded temperature sensor and the temperature data collected from a shaded temperature sensor; and
a mechanism that uses the estimated solar radiation value to affect an irrigation schedule executed by the controller.
2. An irrigation system comprising an irrigation controller according to claim 1 , a non-shaded temperature sensor, and a shaded temperature sensor.
3. An irrigation system comprising an irrigation controller according to claim 1 , and a receiver that receives from a distal sensor, temperature signals from which the estimated solar radiation is partly derived.
4. The controller of claim 1 , wherein the mechanism includes a central processing unit that utilizes a regression model that estimates an evapotranspiration rate using a data point related to the estimated solar radiation.
5. The controller of claim 4 further comprising a memory model that stores the repression model, wherein the regression model comprises a linear regression.
6. The controller of claim 4 further comprising a memory model that stores the regression model, wherein the regression model comprises a multiple regression.
7. The controller of claim 4 further comprising a memory model that stores the regression model, wherein the regression model is based at least in part upon a set of historical ETo values, and a set of corresponding historical values for solar radiation.
8. The controller of claim 7 , wherein the set of historical ETo values spans a time period of at least two days.
9. The controller of claim 7 , wherein the regression model is further based upon a second set of historical values for a second environmental factor other than estimated solar radiation.
10. The controller of claim 9 , wherein the second environmental factor is temperature.
11. The controller of claim 9 , wherein the second environmental factor is humidity.
12. The controller of claim 9 , wherein the second environmental factor is wind speed
13. The controller of claim 9 , wherein the second environmental factor is soil moisture.
14. The controller of claim 9 , wherein the second environmental factor is selected from the group consisting of temperature, humidity, wind speed, and soil moisture.
15. An irrigation system comprising an irrigation controller according to claim 9 , and a local sensor that provides a signal corresponding to a value for the second environmental factor.
16. An irrigation system comprising an irrigation controller according to claim 9 , and a receiver that receives from a distal source a signal corresponding to a value for the second environmental factor.