Systems and methods for optimizing the efficiency of a watering system through use of a computer network

An interface unit is disclosed for facilitating the optimization of a watering system. The interface unit includes a first interface configured to receive optimization data over a network. A second interface is also included, the second interface being configured for electronic communications with a watering system controller that controls operation of a watering system according to watering instructions stored in the watering system controller. The interface unit also includes a processor, the processor being in electronic communication with the first interface and the second interface. Memory is also included. The memory is in electronic communication with the processor, and is programmed with instructions for using the optimization data to modify the watering instructions.

TECHNICAL FIELD

This invention relates generally to electronic devices, and is more particularly directed toward systems and methods for optimizing the efficiency of a watering system through the use of a computer network that is in electronic communication with an interface unit in electronic communication with a watering system controller.

BACKGROUND

Watering systems, including sprinkler systems, drip irrigation systems, etc., are typically used to supply water to plants, including crops, grass, trees, etc. A watering system typically includes a watering system controller which controls the operation of the watering system. Typically, the controller stores watering instructions which may include one or more watering schedules. The watering schedules may include information such as the time that the watering system is supposed to turn on and the time that the watering system is supposed to turn off. The watering system controller typically also has the capability to physically turn the watering system on and off at the appropriate times via communications with a plurality of electrically controlled water valves.

Both the climate of a particular area (i.e., the weather conditions that characteristically prevail in an area) as well as the immediate weather conditions in an area may affect the amount of water needed by plants in that area. For example, plants in an arid climate typically must be supplied with more water than plants in a moist, temperate climate. However, even plants that are located within an area having a moist, temperate climate may need additional water supplied to them during periods of uncharacteristic drought.

Most people, however, do not take into account weather conditions when deciding how much water to supply to their crops, lawn, etc. Instead, typical users program a particular watering schedule into a watering system controller at the beginning of the growing season. This watering schedule typically remains unchanged during the course of the growing season. However, the amount of water needed by plants may increase or decrease, depending on prevailing weather conditions. Failing to adjust the watering schedule to adapt to changing weather conditions may result in too little water being supplied to plants or in significant amounts of water being wasted.

Computer and communication technologies continue to advance at a rapid pace. Indeed, computer and communication technologies are involved in many aspects of a person's day. For example, many devices being used today by consumers have a small computer inside of the device. These small computers come in varying sizes and degrees of sophistication. These small computers include everything from one microcontroller to a fully-functional complete computer system. For example, these small computers may be a one-chip computer, such as a microcontroller, a one-board type of computer, such as a controller, a typical desktop computer, such as an IBM-PC compatible, etc.

Many appliances, devices, etc., include one or more small computers. These types of small computers that are a part of a device, appliance, tool, etc., are often referred to as embedded systems. The term “embedded system” usually refers to computer hardware and software that is part of a larger system. Embedded systems may not have typical input and output devices such as a keyboard, mouse, and/or monitor. Usually, at the heart of each embedded system is one or more processor(s).

Embedded systems may be used to control or monitor the use of certain resources. For example, embedded systems may be used to control or monitor a watering system controller. Benefits may be realized through the use of embedded systems to control and/or monitor the watering schedule stored in a watering system controller.

SUMMARY OF THE INVENTION

An interface unit is disclosed for communicating with a watering system controller. The interface unit includes a first interface configured to receive optimization data over a network. A second interface is also included that is configured for electronic communications with a watering system controller that controls operation of a watering system according to watering instructions stored in the watering system controller. The interface unit also includes a processor that is in electronic communication with the first interface and the second interface. Memory is also included. The memory is in electronic communication with the processor and is programmed with instructions for using the optimization data to modify the watering instructions.

The memory may be programmed with instructions for transmitting the modified watering instructions over the network to a computation unit. In one embodiment, the watering instructions may take the form of a watering schedule which specifies the length of operation of the watering system. In such an embodiment, the optimization data may take the form of a scaling factor which specifies how the watering schedule should be adjusted. In addition, the optimization data may be calculated based on weather information obtained from a weather database. The weather information may include evapotranspiration data. The scaling factor may be calculated based on a comparison of an anticipated precipitation value for the watering system and evapotranspiration data for the geographic region in which the watering system is located. Alternatively, the scaling factor may be calculated based on a comparison of previous evapotranspiration data and current evapotranspiration data for the geographic region in which the watering system is located.

A variety of networks may be used to carry the optimization data to the interface unit. For example, the network may take the form of a pager network, a cellular network, a global communications network, the Internet, a computer network, and/or a telephone network.

Additionally, the watering system may take a variety of forms. For example, the watering system may take the form of a sprinkler system and/or a drip irrigation system.

A method for communicating with a watering system controller is also disclosed. The method includes receiving optimization data over a network at an interface unit that functions as an interface between the network and a watering system controller that controls operation of a watering system according to watering instructions stored in the watering system controller. The method also includes using the optimization data to modify the watering instructions.

The method may include transmitting the modified watering instructions over the network to a computation unit. In one embodiment, the watering instructions may take the form of a watering schedule which specifies the length of operation of the watering system. In such an embodiment, the optimization data may take the form of a scaling factor which specifies how the watering schedule should be adjusted. In addition, the optimization data may be calculated based on weather information obtained from a weather database. The weather information may include evapotranspiration data. The scaling factor may be calculated based on a comparison of an anticipated precipitation value for the watering system and evapotranspiration data for the geographic region in which the watering system is located. Alternatively, the scaling factor may be calculated based on a comparison of previous evapotranspiration data and current evapotranspiration data for the geographic region in which the watering system is located.

A computation unit for communicating with an interface unit that is in communication with a watering system controller is also disclosed. The computation unit includes a first interface for receiving weather information from a weather database. A processor in electronic communication with the first interface is also provided. The computation unit also includes a memory in electronic communication with the processor, the memory being programmed with instructions for calculating optimization data based on the weather information. A second interface is also provided. The second interface is configured to transmit the optimization data over a network to a first interface unit. The first interface unit functions as an interface between the network and a first watering system controller that controls operation of a first watering system. The first interface unit is configured to use the optimization data to modify watering instructions stored in the first watering system controller.

The second interface may be further configured to receive a copy of the modified watering instructions from the first interface unit over the network. The memory may be configured to store the copy of the modified watering instructions. In one embodiment, the watering instructions may take the form of a watering schedule which specifies the length of operation of the watering system. In such an embodiment, the optimization data may take the form of a scaling factor which specifies how the watering schedule should be adjusted. In addition, the optimization data may be calculated based on weather information obtained from a weather database. The weather information may include evapotranspiration data. The scaling factor may be calculated based on a comparison of an anticipated precipitation value for the watering system and evapotranspiration data for the geographic region in which the watering system is located. Alternatively, the scaling factor may be calculated based on a comparison of previous evapotranspiration data and current evapotranspiration data for the geographic region in which the watering system is located.

The second interface may be further configured to transmit the optimization data over the network to a second interface unit. The second interface unit may function as an interface between the network and a second watering system controller that controls operation of a second watering system. The second interface unit may be configured to use the optimization data to modify watering instructions stored in the second watering system controller. In one embodiment, the same set of optimization data is transmitted to the first interface unit and the second interface unit. Alternatively, a first set of optimization data may be transmitted to the first interface unit, and a second set of optimization data may be transmitted to the second interface unit.

A variety of networks may be used to carry the optimization data from the computation unit to the interface unit. For example, the network may take the form of a pager network, a cellular network, a global communications network, the Internet, a computer network, and/or a telephone network.

A method for communicating with an interface unit that is in communication with a watering system controller is also disclosed. The method includes obtaining weather information from a weather database and calculating optimization data based on the weather information. The method also includes transmitting the optimization data over a network to a first interface unit. The first interface unit functions as an interface between the network and a first watering system controller that controls operation of a first watering system. The first interface unit is configured to use the optimization data to modify watering instructions stored in the first watering system controller.

The method may also include receiving a copy of the modified watering instructions from the first interface unit over the network and storing the copy of the modified watering instructions. In one embodiment, the watering instructions may take the form of a watering schedule which specifies the length of operation of the watering system. In such an embodiment, the optimization data may take the form of a scaling factor which specifies how the watering schedule should be adjusted. In addition, the optimization data may be calculated based on weather information obtained from a weather database. The weather information may include evapotranspiration data. The scaling factor may be calculated based on a comparison of an anticipated precipitation value for the watering system and evapotranspiration data for the geographic region in which the watering system is located. Alternatively, the scaling factor may be calculated based on a comparison of previous evapotranspiration data and current evapotranspiration data for the geographic region in which the watering system is located.

The method may also include transmitting the optimization data over a network to a second interface unit. The second interface unit may function as an interface between the network and a second watering system controller that controls operation of a second watering system. The second interface unit may be configured to use the optimization data to modify watering instructions stored in the second watering system controller. In one embodiment, the same set of optimization data is transmitted to the first interface unit and the second interface unit. Alternatively, a first set of optimization data is transmitted to the first interface unit, and a second set of optimization data is transmitted to the second interface unit.

DETAILED DESCRIPTION

It will be readily understood that the components of the embodiments as generally described and illustrated in the Figures herein, could be arranged and designed in a wide variety of different configurations. Thus, the following more detailed description of the embodiments of the system and method of the present invention, as represented in the Figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of the embodiments of the invention.

FIG. 1is a block diagram of an embodiment of a system100for optimizing the efficiency of a watering system110. The watering system110may be any type of watering system, including a sprinkler system, a drip irrigation system, or the like.

The system100also includes a watering system controller112which controls the operation of the watering system110. Typically, the controller112stores watering instructions114which may include one or more watering schedules. The watering schedules may include information such as the time that the watering system10is supposed to turn on and the time that the watering system110is supposed to turn off. The watering system controller112typically also has the capability to physically turn the watering system110on and off at the appropriate times via communications with a plurality of electrically controlled water valves. Watering system controllers112are commercially available.

The system100also includes a weather database116which includes one or more types of weather information for the geographic region118in which the watering system110is located. Weather information may include any information that may affect the amount of water that is supplied to plants in order for them to carry out their metabolic processes. Examples of such weather information include temperature, air pressure, humidity, precipitation, sunshine, cloudiness, winds, etc. In one embodiment, weather information may take the form of a reference evapotranspiration value. Evapotranspiration is the combination of water that is evaporated and transpired by plants as a part of their metabolic processes. It is typically measured in inches. If the daily reference evapotranspiration value for a particular region is, for example, 0.25 inches, this means that plants in that region need, on average, 0.25 inches of water per day in order to effectively carry out their metabolic processes.

Numerous weather stations are positioned in a variety of different locations around the world. These weather stations typically function to gather weather information and store it in weather databases116. Many of these weather databases116are made available to the public. In the embodiment illustrated inFIG. 1, a computation unit120is configured to obtain weather information from the weather database116. This may occur in any number of ways. For example, the computation unit120may take the form of a computer that is connected to the Internet. Software stored on the computation unit120may be configured to retrieve weather information from one or more weather databases116over the Internet. Alternatively, the computation unit120may include a storage device, such as a magnetic disk drive or an optical disk drive. A computer-readable medium containing one or more weather databases116may be used. The computation unit120may be configured to retrieve weather information from a database116stored on the medium. Those skilled in the art will recognize a variety of other ways in which the computation unit120may retrieve weather information from a weather database116.

Based on the weather information obtained from the weather database116, the computation unit120is configured to calculate optimization data, i.e., data which may be used to optimize the efficiency of the watering system10. In one embodiment, the watering instructions114take the form of a watering schedule which specifies the length of operation of the watering system, and the computation unit120stores a copy of the watering schedule. In such an embodiment, the optimization data may take the form of a scaling factor which specifies how the watering schedule should be adjusted. Of course, a scaling factor is just one of many types of optimization data that will be readily recognized by those skilled in the art in light of the teachings contained herein.

The optimization data may be then transmitted to an interface unit122over a network124. The network124may be a pager network, a cellular network, a global communications network, the Internet, a computer network, a telephone network, etc. Those skilled in the art will appreciate many additional networks124that may be used in light of the teachings contained herein.

The interface unit122functions as the interface between the network124and the watering system controller112. The interface unit122is configured to receive optimization data over the network124. The interface unit122is also configured for electronic communications with the controller112. The interface unit122may use the optimization data received from the computation unit120to optimize the efficiency of the watering system110by modifying the watering instructions114stored in the controller112. For example, suppose the watering system110is set to operate for 2 hours. In embodiments where the optimization data includes a scaling factor, suppose that a scaling factor of 0.5 is transmitted to the interface unit122. The interface unit122may then modify the watering instructions114stored in the watering system controller112so that the length of operation of the watering system110is reduced in half, i.e., so that the watering system110only operates for 1 hour. Of course, those skilled in the art will recognize numerous other ways in which the interface unit122may modify the watering instructions114to optimize the efficiency of the watering system110in light of the teachings contained herein.

FIG. 2is a block diagram of an alternative embodiment of a system200for optimizing the efficiency of a watering system110. In the embodiment illustrated inFIG. 1, the optimization data calculated by the computation unit120is transmitted to a single interface unit122. InFIG. 2, however, the optimization data calculated by the computation unit120is transmitted to a plurality of interface units122. The plurality of interface units122illustrated inFIG. 2are located in the same geographic region118, i.e., the weather conditions are substantially similar in the areas in which the interface units122are located. Thus, each interface unit122may receive the same optimization data from the computation unit120.

FIG. 3is a block diagram of another alternative embodiment of a system300for optimizing the efficiency of a watering system110. In the embodiment illustrated inFIG. 3, the plurality of interface units122are located in different geographic regions118, i.e., the weather conditions are not necessarily similar in the areas in which the interface units122are located. Thus, each interface unit122may receive different optimization data from the computation unit120.

FIG. 4is a block diagram of an embodiment of a watering system110. As stated previously, the watering system110may be any type of watering system, including a sprinkler system, a drip irrigation system, or the like. Typically, the watering system110includes a plurality of emitters410, each emitter410being spaced according to its range so as to cover a particular area of land. In a sprinkler system, the emitter410may take the form of a sprinkler. In a drip irrigation system, the emitter410may take the form of a leaky hose, leaky pipe, etc.

Water is typically supplied to the emitters410by water pipes connected to a water supply source through electrically operated valves412. The valves412are configured to open to allow water to flow from the water source to the emitters410, and to close to shut off the flow of water from the water source to the emitters410. The emitters410are typically organized into zones414such that several individual emitters410in a particular area are controlled by a single valve412, with several separately controlled zones414required to cover the entire area of land to be watered. Typically, only one zone414is watered at a time (i.e., only one valve412is open at a time) to ensure sufficient pressure to operate the emitters410in the zone414.

The valves412are typically connected to the watering system controller112. As stated previously, the controller112may include stored watering instructions114for controlling when the watering system110is in operation, i.e., when the valves412are opened and closed.

FIG. 5is a block diagram illustrating one embodiment of the watering instructions114that may be stored within the controller112. The watering instructions114may include one or more watering schedules510. A different watering schedule510may be provided for each zone414. Each watering schedule510may include a zone_ID field512which specifies the zone414to be watered, a start_time field514which specifies the time that watering should begin in the zone414, an end_time field516which specifies the time that watering should end in the zone414, and a duration field518which specifies the total time spent watering in the zone414. The duration field518is equal to the end_time field516minus the start_time field514. Each watering schedule510may also include a system_type field520which specifies the type of watering system110. For example, the system_type field520may indicate whether the watering system110is a sprinkler system, a drip irrigation system, etc. The system_type field520may be useful because precipitation rates differ for different types of watering systems110. As will be explained in greater detail below, the precipitation rate of a watering system110may be used to calculate optimization data, such as a scaling factor.

FIG. 6is a block diagram illustrating one embodiment of a weather database116. The weather database116may include one or more records610. Each record610contains weather information corresponding to a different geographic region118. Each record610may include a region_ID field612, which specifies the geographic region118to which the record610corresponds. Each record610may also include one or more types of weather information for the geographic region118in which the watering system110is located. In the embodiment shown inFIG. 6, the weather information takes the form of reference evapotranspiration values. The reference evapotranspiration value for the geographic region118identified by the region_ID field612may be stored in an ET_data field614. A current_date field616may be provided to specify the most recent date on which the ET_data field614was updated. A previous_date field618may be provided to specify the most recent date prior to the current_date616on which the ET_data field614was updated. A percent_change field620may be provided to specify the percent change between the ET_data field614on the date corresponding to the previous_date field618and the ET_data field614on the date corresponding to the current_date field616.

FIG. 7is a block diagram of hardware components that may be used in an embodiment of the computation unit120. The computation unit120may be embodied in a computer, as will be appreciated by those skilled in the art. Many different kinds of computers are commercially available.

A CPU710may be provided to control the operation of the computation unit120, including the other components thereof, which are coupled to the CPU710via a bus712. The CPU710may be embodied as a microprocessor, microcontroller, digital signal processor or other device known in the art. The CPU710performs logical and arithmetic operations based on program code stored within the memory714. In certain embodiments, the memory714may be on-board memory included with the CPU710. For example, microcontrollers often include a certain amount of on-board memory.

The computation unit120may also include a network interface716. The network interface716facilitates communication between the computation unit120and other devices connected to the network124, such as the interface unit122. As stated previously, the network124may be a pager network, a cellular network, a global communications network, the Internet, a computer network, a telephone network, etc. The network interface716operates according to standard protocols for the applicable network124.

The computation unit120may also include memory714. The memory714may include a random access memory (RAM) for storing temporary data. Alternatively, or in addition, the memory714may include a read-only memory (ROM) for storing more permanent data, such as fixed code and configuration data. The memory714may also be embodied as a magnetic storage device, such as a hard disk drive. The memory714may be any type of electronic device capable of storing electronic information.

The computation unit120may also include communication ports718, which facilitate communication with other devices. The computation unit120may also include input/output devices720, such as a keyboard, a mouse, a joystick, a touchscreen, a monitor, speakers, a printer, etc.

FIG. 8is a block diagram of hardware components that may be used in an embodiment of an interface unit122. The embodiment of the interface unit122illustrated inFIG. 8includes a CPU810, a network interface816, memory814, communication ports818, and I/O devices820. These components operate similarly to the corresponding components illustrated and discussed previously in connection with the computation unit120.

In addition, the interface unit122also includes a controller interface822. The controller interface822enables electronic communication between the interface unit122and the controller112. The precise configuration of the controller interface822will vary depending on the type of watering system controller112used. Specifications for commercially available watering system controllers112are readily available, and those skilled in the art are capable of determining the necessary configuration of the controller interface822.

Of course, the block diagrams ofFIGS. 7 and 8are only meant to illustrate typical hardware components of a computation unit120and an interface unit122. These diagrams are not meant to limit the scope of embodiments disclosed herein.

FIG. 9is a block diagram illustrating software components of an embodiment of the computation unit120. The computation unit120is programmed with instructions for calculating optimization data based on weather information obtained from the weather database116.

The computation unit may include a database930which includes a plurality of records932. Each record932may include a copy of the watering schedule510associated with a particular watering system110. Each record932may also include an interface_unit_ID field934. The interface_unit_ID field934identifies the interface unit122which is in electronic communication with the watering system110to which the watering schedule510corresponds.

The computation unit120may also include a precipitation calculator910. The precipitation calculator910calculates the amount of precipitation that a watering system110will provide over a given time. In one embodiment, the precipitation calculator910accepts as input the duration and system_type fields518,520from a watering schedule510. Based on the system_type field520, the precipitation calculator910calculates and stores the anticipated precipitation912for that watering system110, i.e., the amount of precipitation that each emitter410within the zone414will provide during the amount of time specified in the duration field518.

For example, suppose that the system_type field520indicates that the watering system110is a sprinkler system. Typically, the precipitation rate for a sprinkler is 2 inches per hour; this value may be used by the precipitation calculator910as an approximation to determine the anticipated precipitation912. Continuing with the example, suppose that the duration field518equals 0.5 hours. The anticipated precipitation912would then be 1 inch (0.5 hours*2 inches per hour). In an alternative embodiment, the watering schedule510may include an additional field that specifies the exact precipitation rate for the particular watering system110with which it is associated.

The computation unit120may also include a scaling factor calculator914. As stated previously, the optimization data calculated by the computation unit120may take the form of a scaling factor916which specifies how the length of operation of the watering system110should be adjusted. In one embodiment, the scaling factor calculator914accepts as input the anticipated precipitation912associated with a particular zone414in a particular watering system110, and the ET_data field614associated with the geographic region118in which the watering system110is located. As stated previously, the computation unit120may obtain the ET_data field614from the weather database116.

By comparing the anticipated precipitation912for the watering system110with the ET_data field614, the computation unit120may calculate and store the scaling factor916associated with that watering system110. For example, if the anticipated precipitation912for a zone414within a watering system110is 0.5 and the ET_data field614associated with the geographic region118in which the watering system110is located is 0.25, the watering system110is scheduled to produce twice as much precipitation as is necessary for plants within the geographic region to efficiently carry out their metabolic processes. Thus, the scaling factor916is calculated to be 0.25/0.5=0.5.

FIG. 10is a block diagram illustrating software components of an embodiment of an interface unit122. As stated previously, the interface unit122is configured for electronic communications with a watering system controller112that controls operation of a watering system110. The interface unit122is also programmed with instructions for using optimization data generated by the computation unit120to modify watering instructions114for the watering system110.

The interface unit122may store three variables, a current_zone variable1010, a max_zone variable1012, and a last_updated variable1014. The max_zone variable1012equals the number of zones414within the watering system110associated with the interface unit122. The current_zone variable1010is used to modify watering instructions114for the watering system110, as will be explained below. The current_zone variable1010may be any value between 1 and the value of the max_zone variable1012. The last_updated variable1014equals the last date that the interface unit122received optimization data from the computation unit120and accordingly modified the watering schedule510in the associated controller112.

The interface unit122may also include a schedule retrieval unit1020and a schedule transmittal unit1022. Recall that each interface unit122is in electronic communication with a watering system controller112. The schedule retrieval unit1020is configured to retrieve a copy of the watering instructions114stored in the watering system controller112with which the interface unit122is in electronic communication. In one embodiment, the watering instructions take the form of a watering schedule510, which may be stored in the interface unit122. The schedule transmittal unit1022is then configured to transmit the stored watering schedule510over the network124to the computation unit120.

Although the items ofFIGS. 9 and 10are described as being software components, and the items ofFIGS. 7 and 8are described as being hardware components, it will be appreciated that hardware components may be substituted for various software components, and some hardware components may be achieved through software components.

FIG. 11is a flow diagram illustrating a method1100for determining optimization data. The method1100may be implemented by the computation unit120using the hardware components illustrated inFIG. 7and the software components illustrated inFIG. 9.

In accordance with the method1100, the computation unit120may first receive1102the current watering schedule510for a particular watering system110from the corresponding interface unit122. The watering schedule510may then be stored in the database930. The computation unit120may then calculate1104the anticipated precipitation912for a particular watering system110.

The computation unit120may then obtain1106weather information, such as the reference evapotranspiration value for the geographic region118in which the watering system110is located, from the weather database116. As stated previously, the reference evapotranspiration value may be represented by the ET_data field614in the weather database116. The computation unit120may then compare1108the reference evapotranspiration value (as represented in the ET_data field614) with the anticipated precipitation912to generate a scaling factor916. The scaling factor916may then be transmitted1110to the interface unit122. The computation unit120then waits until it determines112that new weather information (e.g., new reference evapotranspiration data) is available from the weather database116, at which point the method1100repeats itself beginning at step1104.

FIG. 12is a flow diagram illustrating a method1200for using the optimization data generated by the computation unit120to modify a watering schedule510stored in a watering system controller112. The method1200may be implemented by the interface unit122using the hardware components illustrated inFIG. 8and the software components illustrated inFIG. 10.

The interface unit122may first retrieve1202a copy of the watering instructions114stored in the watering system controller112for the watering system110with which the interface unit122is associated. As stated previously, the watering instructions114may take the form of a watering schedule510. The interface unit122may then receive1204optimization data that corresponds to the watering system110with which the interface unit122is associated. In one embodiment, the optimization data may be the scaling factor916. The current_zone field1010in the interface unit122is then set1206equal to 1. In the watering schedule510stored in the interface unit122, the duration field518of the zone414corresponding to the current_zone variable1010is then multiplied1208by the scaling factor916. For example, because the current_zone field1010in the interface unit122is initially set1206equal to 1, the duration field518of zone number1is initially multiplied by the scaling factor916.

The interface unit122then determines1210whether the current_zone variable1010is equal to 1. If the current_zone variable1010does not equal 1, the start_time field514of the zone414corresponding to the current_zone variable1010is set equal to the end_time field516of the zone414corresponding to the current_zone variable1010minus 1. Then the end_time field516of the zone414corresponding to the current_zone variable1010is set1214equal to the start_time field514plus the duration field518. If in step1210it is determined1210that the current_zone variable1010is equal to 1, the method1200skips to step1214.

FIG. 13is a flow diagram illustrating an alternative method1300for determining optimization data. The method1300may be implemented by the computation unit120using the hardware components illustrated inFIG. 7and the software components illustrated inFIG. 9.

The computation unit120first determines1302whether the last_updated variable1014in the interface unit122equals the previous_date field618in the weather database116. If it is determined1302that the last_updated variable1014in the interface unit122does not equal the previous_date field618in the weather database116, the method1300proceeds with steps1102through1110, as described above. The computation unit120then waits until it determines1304that new reference evapotranspiration values are available from the weather database116.

If it is determined1302that the last updated variable1014in the interface unit122equals the previous_date field618in the weather database116, this means that the watering schedule510has been optimized according to the previously available evapotranspiration data. Thus, the scaling factor916may simply be determined by reference to the percent_change field620in the weather database116. The computation unit120then obtains1306the percent_change field620from the weather database116and sets it equal to the scaling factor916. For example, if the current ET_data field614in the weather database116is 25% lower than the previous ET_data field614, the percent_change field620may be equal to 0.75. The scaling factor916may then also be equal to 0.75. The computation unit120then transmits1308the scaling factor916to the interface unit122. The computation unit120then waits until it determines1310that new evapotranspiration data is available. When it is determined1310that new evapotranspiration data is available, the method1300returns to step1306and proceeds as described above.

FIG. 14is a flow diagram illustrating an alternative method1400for using the optimization data generated by the computation unit120to modify a watering schedule510stored in the watering system controller112. The method1400may be implemented in the interface unit122using the hardware components illustrated inFIG. 8and the software components illustrated inFIG. 10.

The method1400is similar to the method1200illustrated inFIG. 1200, except for the following two differences. First, when the interface unit122receives1404the scaling factor916from the computation unit120, the interface unit122also receives1404the current_date field616. Second, after the modified watering schedule510is transmitted1220to the watering system controller112and the computation unit120, the last_updated variable1014in the interface unit122is set1422equal to the current_date field616.

FIG. 15Ais a timing diagram1500A illustrating an embodiment of the watering schedule510. The watering system110illustrated inFIG. 15Ahas three zones414. This number is exemplary only; the watering system110may include any desired number of zones414. According to the watering schedule510shown inFIG. 15A, zone1is set to operate from 8:00 AM until 8:30 AM, zone2is set to operate from 8:30 AM until 9:00 AM, and zone3is set to operate from 9:00 AM until 9:30 AM.

FIG. 15Bis a timing diagram1500B illustrating the watering schedule510ofFIG. 15Aafter being modified by a scaling factor916of 0.5. Zone1is now set to operate from 8:00 AM until 8:15 AM, zone2is now set to operate from 8:15 AM until 8:30 AM, and zone3is set to operate from 8:30 AM until 8:45 AM.

FIG. 15Cis a timing diagram1500C illustrating the watering schedule510ofFIG. 15Aafter being modified by a scaling factor of 1.5. Zone1is now set to operate from 8:00 AM until 8:45 AM, zone2is now set to operate from 8:45 AM until 9:30 AM, and zone3is set to operate from 9:30 AM until 10:15 AM.

Those of skill in the art would understand that information and signals described herein may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, and signals that may be referenced throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.