Patent Application
20140236868
The present invention relates generally to the field of the computerized monitoring and control of irrigation, and more particularly to a system and method that provide range-based soil moisture management calculations and irrigation decision algorithms at a cloud-based computer server, using both non-decision-making and decision-making programmable logic controllers in combination with a client server architecture that uses enhanced modeling for monitoring, analysis, and control and localized environmental data and forecasting.
Water management through the computerized monitoring and control of irrigation is of increasing importance. The cost of water continues to rise because of its growing scarcity and the heightened demands for its use. For example, there is upward trend in commercial water rates in many of the major southern and western U.S. urban markets. Because of political considerations, water for commercial irrigation is often billed at higher rates than water for residential use, making the commercial landscape maintenance business more and more expensive.
To reduce the cost of water used for commercial irrigation, automated, centralized systems have been created to regulate the amount of water used to irrigate specific areas.
These systems rely on automated machine-to-machine (“M2M”) technology, as most irrigation is typically scheduled during night-time hours when no maintenance staff is present on a property to respond to identifiable irrigation system problems. Even if irrigation was done during daylight hours, labor rates and property complexities would never allow human oversight to be a feasible approach for pursuing irrigation best practices management.
However, these systems have many disadvantages, as described below. In general, their use leads to the over-watering that can be seen at most commercial sites today.
Centralized irrigation systems that use clocks alone to regulate watering schedules for specific areas typically represent the full extent of irrigation management tools employed at commercial properties across America today.
In addition, such a system may employ one or more rain sensors 1362 that can shut off irrigation a predetermined time, to reduce overwatering.
These systems have no automated capability for regulation according to other, changing variables than watering time, such as current rainfall in the area, and lack even a remote on/off capability. They are simply turned on for specific amounts of time according to a predetermined estimate of an area's need for water.
Clock-based irrigation systems have major disadvantages. Since water pressure is typically not constant through water pipes and these systems do not take flow readings to determine a pipe's actual output, they cannot accurately determine how much water they are really applying to an area, which is potentially wasteful. They have no way of automatically monitoring the state of repair of their equipment in the field. Moreover, although these systems may have rain sensors 362 that can shut off the controllers for a predetermined time, they typically do not recalculate the irrigation time for the following day based on such changes. As a result of these factors, these systems tend to result in over-watering, for example during rainstorms.
Consistent over-watering is damaging to plants, turf, and surrounding hardscapes such as patios, walls, and walkways and is economically wasteful. It can result in
More advanced smart irrigation systems, including Web-based access systems, use networked smart controllers or related components to schedule irrigation at remote sites, rather than relying on timed schedules alone. Instead, they schedule irrigation based on basic zone factors stored in the smart controller and updated macroclimate factors such as predicted ET. Site factors have to do with characteristics that can influence the need for irrigation, such as plant type, soil type, proximity to heat-absorbing asphalt parking areas, and exposure to prevailing winds.
Server 100 sends the ET numbers over pager network 130 to decision-making controllers at irrigation sites, and the controllers in turn apply the basic zone factors to the ET number (in inches), and modify a pre-set schedule, then open and close valves on water pipes to carry out more efficient watering. Such systems can improve water conservation over clock-based systems, because they can automatically regulate irrigation according to recent weather conditions, and they typically reduce over-watering.
For irrigating an area represented by site 1202, for example, a smart controller 1312 is provided. Site 1202 may be further divided into different sub-zones, such as hydrozone 1222 and hydrozone 2224, which may represent area with different variables, for example different soil types, plant cover, and slope. To permit specific irrigation according to each hydrozone's needs, hydrozone 1222 may be provided with water valve 1342 and rain sensor 1362 and hydrozone 2224 with water valve 2344 and rain sensor 2364.
Smart controller 1312 is equipped with algorithm 1408, which is programmed to calculate water requirements based on data input from elements such as ET data from weather station 1332 through server 100, data about the presence of rainfall in hydrozone 1222 from rain sensor 1362, and data about the presence of rainfall in hydrozone 2224 from rain sensor 2364. Based on these calculations, smart controller 1312 opens or closes valve 1342 for hydrozone 1222 and valve 2344 for hydrozone 2224.
For irrigating a different area represented by site 2204, with different sub-zones, such as hydrozone 3226 and hydrozone 4228 a separate smart controller 2314 is provided, equipped with a different algorithm 2410 designed for the needs of that area. Again, smart controller 2314 collects through server 100 data from weather station 2334, and from rain sensors 3366 and 4368, calculates appropriate irrigation, and opens or closes valve 3346 for hydrozone 3226 and valve 4348 for hydrozone 4228.
The Hydropoint WeatherTrak® system as described in US Patent Applications 20050119797, 20050143842, and 20050187666 is an example of such a system.
These systems have serious disadvantages, primarily because they are not sufficiently precise enough in the environmental data they collect and the calculations they make for irrigating specific sites. For example, they typically do not monitor or collect the actual volume of water that was applied to an area from a previously generated schedule and these systems do not measure and utilize effective rainfall in the—preventing the generation of an accurate new schedule. These types of irrigation control systems make a unilateral irrigation decision; they decide to irrigate for all or none of the irrigation zones, even though certain zones may not require irrigation. Therefore, these types of systems can only estimate the actual irrigation requirement and apply more water than is required across the multiple irrigation zones they manage. In addition, they typically use prior-day ET for their calculations of daily schedule modifications, although weather conditions may change dramatically not only from day to day but from moment to moment.
They also do not typically identify microclimates within zones sufficiently to efficiently modify pre-set schedules for special requirements in the microclimate. There typically is a water window of only so much water capacity per day in a given area, so that in some cases it would be more efficient to irrigate only those zones that have the greatest need based on the microclimate.
Another major problem is that these systems typically attempt to calculate a daily replacement net irrigation requirement for a zone, based on basic site and environmental factors, rather than calculate an optimal range of soil moisture. Plants actually do better within cycles of wetness and dryness in an appropriate range to cycle air through the soil root zone than they do when kept constantly at a single amount. For example, the Water Management Committee of The Irrigation Association has developed, adopted and publicized “Landscape Irrigation Scheduling and Water Management,” March 2005, which acknowledges the best methods of plant irrigation by watering to a management-defined depletion level (MAD).
As a result of these limitations, although these systems may deliver water more effectively to a given zone than clock-based systems do, they are still only focused to a limited degree on reducing water waste and optimizing irrigation water, which typically makes them more expensive to operate than is possible.
Moreover, these products typically have complicated, difficult-to-use interfaces, which makes them often complex to program, update, and manage and difficult to evaluate for return on investment. For example, decision-making controllers that themselves calculate water requirements and regulate irrigation may need to be updated at times. This updating will typically need to be done at the sites rather than at a central location, which is time consuming, laborious, and expensive. Smart controllers may offer an ability to update their firmware remotely; however, because the algorithms for their processes reside in the controllers, the controllers will always be difficult to update easily and efficiently.
In addition, these systems do not typically monitor the actual flow of water at a site. Instead, they irrigate a site based on a calculation of the system's flow rate from a fixed point in time.
Flow rates, however, may vary for numerous reasons, including systemic problems and leaks, which these systems typically neither monitor nor take into account.
Fluctuations in flow rate can have very significant effects for irrigation. For example, if a zone is scheduled to receive 1000 gallons of water, and the zone's expected flow rate is 100 gpm (gallons per minute), these systems will typically turn on water to that zone for 10 minutes (10 minutes*100 gpm=1000 ga). However, it is very unlikely that the zone will ever run exactly 100 gpm. Because the actual variations of flow rate are not monitored and used to calculate the next day's water needs for the site, either excess watering or potential plant loss will typically result.
Some of the other limitations of these systems are as follows:
Without any leak detection and related automatic shut-down capabilities or soil moisture monitoring capabilities that enable the complete use of water provided by natural rain events, the savings potential from watering strictly to prior-day ET can and likely will be wiped out by one significant line break per year that goes undetected for even a short time. The combination of tenant/customer traffic (pedestrian and vehicular) at commercial sites and high-speed landscaper maintenance techniques virtually ensures that line breaks or other major water wasting system events will occur one or more times each year.
Therefore a need exists for an automated, centralized system that can more finely calculate and regulate the range-based irritation in zone and microclimates, that employs an easier-to-use and more effective interface for monitoring, analyzing, and controlling applications, and that uses a more efficient hardware system.
Such a system can accomplish greater savings in water resources than prior techniques permit, while at the same time ensuring optimum irrigation. The amount of reduction allows use of a business model in which the party providing the system charges customers a percentage of the savings achieved.
The following explanation describes the present invention by way of example and not by way of limitation.
As mentioned above, irrigation systems have not historically been tightly monitored or controlled despite increasing costs and scarcity of the resources such as irrigation water. The current invention provides the benefits of monitoring without requiring a central control room facility, while implementing control strategies that are more economical and effective.
One aspect of the current invention is the use of non-decision-making controllers in combination with a client server architecture that employs irrigation algorithms for monitoring and control. That architecture typically includes a live feedback means such as flow meters and rain buckets that send information back to a server, so that the feedback means can be used to monitor exceptions to a planned control scheme, to adjust control parameters, and to provide a real-time update to system performance. This feedback enables volume-based cycles and soaks of irrigation that are more effective and economical than prior techniques.
This approach has non-obvious and unexpected benefits relative to trends in some industries toward decision-making controllers and distributed control systems.
Another aspect of the current invention is the use of range-based control strategies that take into account both a minimal allowed soil moisture depletion (typically referred to as MAD), and an allowed maximum amount of moisture (Target) that is less than the total volumetric holding capacity (often referred to as Mhc—Maximum Holding Capacity) for the soil. In the case of irrigation systems which utilize MAD to determine watering needs, a range-based approach typically seeks to fill the soil with moisture to the maximum holding capacity (Mhc) of the soil whereas the approach of the current invention creates significant water savings by allowing for and anticipating future rain events that would otherwise not be utilized. When the soil moisture is replenished to Mhc, any rain that follows the irrigation will run off, whereas if the soil moisture is replenished to a Target level above MAD (to avoid plant health issues) and yet less than Mhc, the difference between the target volume and Mhc that is filled by the rain event represents water savings. As illustrated in
Another advantage of utilizing a Target less than Mhc for irrigation scheduling is the potential to mitigate runoff from rain events. Depending on rainfall rates, the total volumetric total of runoff can be reduced by as much as the difference between Mhc (the amount typical irrigation systems water to) and Target (the amount this invention utilizes). Runoff creates significant environmental issues, and this advantage represents an important hedge against this issue. The volume of soil is determined from the surface area of an irrigation zone and a relevant root depth determined from the plant type in that area. The total amount of water that a soil volume can hold is then determined from the soil volume and the holding capacity of a unit volume of the soil. For instance, sandy soils have a different holding capacity than clay soils. The range of soil moisture is then determined from the microclimate factors, including plant type. For example, within each zone the plant type with the highest requirement for water can be determined.
The range is from a minimum, desired soil moisture to avoid excess stress to the plant (MAD), to a maximum desired soil moisture (Target). Once the desired range is established, various control strategies can be adopted, and the execution of those strategies involves directing a desired volume of water to the zone to make a specific adjustment to soil moisture within the range. Some examples of that strategy include not watering the zone every day so long as the soil moisture is within range, not watering on a day if rain is forecasted on the next day, and deliberately cycling the soil moisture between the lower portion of the range and the upper portion of the range. The resulting cycling from these types of strategies can save water while maintaining plant health, and can actually improve plant vigor as opposed to strategies that target maintaining a single set point (Mhc) for soil moisture.
Another aspect of the current invention is more sophisticated modeling. For irrigation, the current invention typically models an irrigation site with over 15 parameters versus a limited number of basic parameters such as ET in prior techniques. In addition to ET, these new parameters may comprise
Another aspect of the invention is a shared savings business model where the vendor provides a system, such as an irrigation system, and the customer only pays the vendor a portion of the savings obtained by using the system. The savings is typically established by comparing historical usage with current usage. This business model permits the customer to begin realizing savings without budgeting capital expenditure, and it begins saving water or other resources immediately. The model encourages the vendor to design and install systems that are economical, robust, and effective. The model is effective for the vendor because the monitoring and control system is highly effective at producing substantial savings.
Another aspect of the invention is the opportunity to rapidly deploy improved control systems to save water for a community. In this example, an entity such as an oil and gas producer may be depleting a resource such as groundwater. That entity can offset the use of the groundwater by sponsoring a water-savings program for another entity. In one example, the first entity contracts with Acequia to deploy its irrigation management systems. Acequia installs and monitors the systems and measures the volume of water savings. This volume is then “credited” to the first entity to offset the waste of groundwater. This model is analogous to “carbon credits” which are an accepted way to reduce emissions of carbon dioxide or greenhouse gases by compensating for or offsetting an emission made elsewhere.
Another advantage of the current invention is the ability to coordinate the control of valves on different main lines. This capability permits existing irrigation applications to be retrofitted with an enhanced control system as described in this specification without reconfiguring zones and valves. For instance a zone may be supplied by both a first controller on a first supply line and a second controller on a second supply line. The amount of water delivered to the zone will depend upon whether the first supply line only is open, the second supply line only is open, or both the first and second supply line are open. In prior art systems, it would be necessary for the first controller to communicate directly with the second controller. In the current invention, both controllers communicate to the server, and the server makes appropriate adjustments to compensate for which supply lines are open.
The following embodiment of the present invention is described by way of example only, with reference to the accompanying drawings, in which:
This embodiment may comprise the following elements:
In other embodiments, the elements for the irrigation system shown above may be used in different operating environments known to those skilled in the art. For example,
In still other embodiments, the system and method of the present invention that are explained in this patent specification for the irrigation industry may be used in other industries that may benefit from centralized regulation, for example the gas industry and the air conditioning industry. As illustrated in
Step 1000 in FIG. 7—Get input data relevant to irrigation at a site 202.
For example, such data may be obtained from an initial survey of the irrigation site 202, shown in
Step 2000 in FIG. 7—Store input data 450 in a database 406.
The input data mentioned in connection with Step 1000 may be stored for further use in database 406, shown in
Step 3000 in FIG. 7—Determine the need for irrigation at a site 202.
These needs are typically a function of the plant type, soil, and environmental factors.
They are automatically determined through proprietary algorithms such as algorithm 3414, shown in
Range based soil moisture management is focused primarily on the water holding capacity of a specific soils' type; environmental factors that impact plant water depletion; and evaporation depletion of soil moisture in the root zone of specific plantings. This management approach is useful where the measurement of soil moisture by instrumentation is too small of an area of measurement to be representative of the entire landscape planting area, even within an individual irrigation zone, and the cost of installing and maintaining the required number of soil moisture instruments would be cost prohibitive. Range based soil moisture management can incorporate algorithms to calculate soil moisture across a localized area in a known root zone soil profile from a knowledge of environmental data and documented soils type characteristics.
Range based soil moisture management is typically used to monitor, analyze and control a stationary, closed-loop sub-surface mainline irrigation system, connected to pressurized and fixed volume water source or sources. Typical system components are described below.
Controllers can be non-decision making controllers, decision making controllers such as Programmable Logic Controller (PLC) devices, or a combination of non-decision making controllers, decision making controllers.
The controllers are connected via hardwire or wireless connection to remote irrigation zone valve and sensors. The controllers are typically networked by hardwire or wireless connection to cloud-based server computers through Internet connectivity. An individual controller may distribute information to other PLC by communication to cloud-based computer server, which in turn transmits information to other Controls.
The system typically includes a server that centralizes the decision making intelligence of monitoring, analysis and control to both non-decision making and decision making PLC. The server connects data storage devices to store specific irrigation zone data; to store historical data; and to store future schedule data.
The server typically provides one or multiple processors to run multiple complex algorithms in near real-time. The system provides network connectivity in near real-time to multiple programmable logic controls; to environmental data recorders and web-based services; and to system users.
The operating system provides resource and interconnectivity to the multiple program layers residing at the server, or at other related servers or virtual servers supporting the complete software suite.
Sensors provide information to the server or controllers including water flow rate; water pressure; and localized environmental data including rainfall accumulation and rate over time duration, root zone soil moisture, temperature, humidity, solar radiation, and wind speed and direction.
The system typically comprises a plurality of irrigation zones which are designed to meet flow and pressure requirements of irrigation application nozzle devices; and to apply supplemental irrigation to plants with common water requirements, and plants residing in common soils type.
Example of range-based soil moisture management and decision algorithm
In this example, the control method utilizes stored prescribed optimum soil moisture range for specific plantings within each irrigation zones from cloud-based computer server data base. If multiple plant types are planted within an individual irrigation zones, the method defaults to the optimum range of the highest water use plants in the irrigation zone.
At step 3000 of
Referring to
At step 3170, the method stores the new root zone soil moisture at the cloud-based computer server storage device.
At step 3210, the method accesses prescribed optimum range data for each irrigation zone from the cloud-based computer server data base to compare new root zone soil moisture value in gallons to the prescribed optimum soil moisture range.
At step 3220, If the new root zone soil moisture value is within or above the prescribed optimum soil moisture range, then the cloud-based computer server decision will be not to apply supplemental irrigation to the individual irrigation zone and the irrigation zones will be removed from scheduling the at next scheduling opportunity.
If the new root zone soil moisture value is below the prescribed optimum range, then the cloud-based computer server will make a decision at step 3230 to apply supplemental irrigation and will include the irrigation zones for scheduling at the next irrigation scheduling opportunity. At step 3240, the server will calculate the volume of water in gallons to be applied during irrigation event by determining at step 3242 the volume required to increase the current calculated root zone soil moisture volume to the highest volume in the prescribed optimum range, then adjusting this calculated volume at step 3244 to meet any deficiencies in delivery of water by the irrigation system, and adjusting at step 3246 the deficiency-adjusted calculated volume by a precipitation probability forecast ratio.
At step 3250, the server compares stored irrigation zone precipitation rate to the stored infiltration rate of the zone soils type, to determine the required number of irrigation cycles to apply the prescribed volume of water over a period of time to optimize the infiltration into the soil root zone area.
At step 3260, the server creates an irrigation schedule for each irrigation zone optimizing the irrigation system mainline volume capacity and minimizing irrigation event run-time.
At step 3300 the server communicates the individual irrigation zone schedules and water source master valves schedules to related controllers.
In an embodiment, the algorithm 3414 used for irrigation calculations may comprise a range-based irrigation algorithm. Such an algorithm calculates the optimum range of irrigation time for the specific plants and conditions at a hydrozone 222, rather than calculating a single amount of moisture to be maintained in the soil.
For example,
The following example shows useful elements for a range-based irrigation algorithm:
Auto Schedule High-Level Calculations
In one example, the range of soil moisture is based on specific crop or plant type within a specific irrigation zone or area. Within the area, a lower limit calculation is made for the soil water volume to be maintained to prevent plant wilt; and a top range limit calculation is made for the maximum soil moisture range for specific plants to grow optimally. These lower limit volumes and top range limit volumes are corrected for irrigation system distribution. The range-based irrigation algorithm is plant specific, and considers the soil moisture holding capacity of specific soil in root zone of specified plants.
Step 4000 in FIG. 7—Send each controller 316 a schedule for irrigation for its hydrozone 222. In an embodiment, an irrigation schedule may be based on total volume constraints, priority of need, and multiple-pass application such as slopes for an individual hydrozone 222, shown in
In this example, a non-decision making PLC has stored on-board memory and logic to accomplish the following:
The controller does not have a decision capacity.
In this example, information is stored in controller on-board memory and logic to accomplish the following:
The controller has the decision capacity, in the event of prolonged loss of connectivity with cloud-based computer server, to retrieve default irrigation zone schedules; and to monitor and store input data from default irrigation zone schedules. The controller can also discontinue irrigation schedules when high flow value is detected; when no flow value is detected; when a rain sensor input value threshold is detected; or when a temperature low limit threshold is detected.
Step 5000 in FIG. 7—Monitor the water flow during irrigation on a user-friendly dashboard interface 418.
Data input from a flow meter 370, shown in
Step 6000 in FIG. 7—Adjust the water flow when necessary.
Employees and customers can use that dashboard interface 418, shown in
Step 7000 in FIG. 7—Calculate the water optimization savings.
This calculation is automatically determined through proprietary algorithms such as algorithm 3414, shown in
The irrigation system and method presented greatly facilitates true best practices irrigation management through the following steps, shown in
Step 8002 in FIG. 10—Programming watering windows at the individual hydrozone level 222, shown in
Step 8004 in FIG. 10—Optimizing mainline capacity to mitigate watering window limitations during peak irrigation periods.
Step 8006 in FIG. 10—Distributing a precisely calculated volume of water to each hydrozone 222 and 224 when operating under automated scheduling program;
An example of how “water use optimization” differs from “water conservation” involves irrigation scheduling techniques during the hot and dry summer months. By scheduling irrigation on heavily sloped areas in multiple short applications rather than a single long application, a planned reduction in water use may not be occurring, but we can ensure that the water applied is actually absorbed into the soil and produces the desired cosmetics rather than mostly running off in to storm drains.
Step 8008 in FIG. 10—Operating automated and manual schedules (time based) simultaneously.
Manual schedules may be needed when flow meters 370 and 372 are not present or are not operational.
Step 8010 in FIG. 10—Developing and storing manual schedules Manual schedules are those schedules created by a user, in lieu of, or simultaneous to, an automatically generated schedule.
In an embodiment, manual schedules are created with the dashboard interface 418, shown in
The Aquador.NET technology by Acequia, Inc. provides the mechanics and platform for the exchange of real-time data and automated processing of business decisions between field irrigation controllers, a server process, and a rich client user interface. The following sections show examples of components used by the Aquador system to accomplish the irrigation system explained above.
In an embodiment, the server 100 is a process application that:
In embodiments, SCADA, MOSCAD or other field irrigation controllers 316 and 318 with external communication capability, may be used. SCADA technology may be used because it is dependent upon receiving raw data, automatically analyzing the data, and executing supervisory control. However, the present invention achieves the real-time distribution of “information” as well. To be more specific, “information” is the result of the analysis of data, and the present invention distributes information to end users as “virtual information objects.”
The SCADA sub-system is independent of the present invention. A simple interface is required to integrate the SCADA sub-system into the present invention's server.
Proprietary firmware is used on the RTUs and the Motorola MOSCAD controllers and is responsible for the following steps, shown in
Step 8012 in FIG. 11—Implementing all messages received from Aquador.NET;
Step 8014 in FIG. 11—Transmitting all active data flows received from all field hardware devices to Aquador.NET;
Step 8016 in FIG. 11—Maintaining a constant communications link with Aquador.NET;
Step 8018 in FIG. 11—Storing all data received from field hardware devices in the event of a communications interruption; and
Step 8020 in FIG. 11—Transmitting all stored data upon restoring any interrupted communications link.
In an embodiment, off-the-shelf and highly tested Siemen's AG cell to IP (cellular to internet) modems may be used for two-way data communications along with direct Ethernet connections.
Master water valves 342 and 344 are placed at the point that each water source enters the irrigation site. These valves 342 and 344 are closed when irrigation is not occurring, to eliminate constant seeping and are closed automatically when a mainline leak/break is detected.
The streaming of real-time data from flow meters 370 and 372 on each mainline facilitates the execution of automated watering schedules, leak detection, detection of stuck valves, and precise watering based on hydrozone-by-hydrozone environmental data.
Spotting at least one and sometimes two tipping rain buckets 390 and 392 on larger sites 202 facilitates the amendment or interruption of in-progress irrigation schedules or the cancellation of irrigation schedules to be executed in the next 24 hours.
Spotting sensors 380, 382, 384, and 386 in strategic locations around each site 222 provides highly useful input data 450 for automatic scheduling, monitoring in displays, and manual adjustments of irrigation. For example, soil moisture probes can provide soil-moisture-audit data to compare to algorithm-derived soil moisture calculations and ensure that sufficient soil moisture is maintained.
For irrigation, the database 406 is simply a data store structured for the specific types of data and information to be stored, in an embodiment, as a result of the selected SCADA industry. For other industries, industry-specific databases are built, as shown in
Technically, the Aquador.NET Virtual Information Broker distributes information between the Aquador.NET Server, such as server 100 shown in
Simply stated, the Aquador.NET Virtual Information Broker allows users to “subscribe” to receive the information needed by the user. Once subscribed, the Virtual Information Broker then delivers the information to the user automatically. The “subscription” itself is transparent to the user, as it is programmatically implemented in the Graphical User Interface (“GUI”) of the Aquador.NET Dashboard.
In an embodiment, the dashboard 418, shown in
There are two primary means of customizing the dashboard:
Modules 503, shown in
Modules are all able to be sized and docked to any number of places within the dashboard 418, by:
The following list shows other typical elements and features of modules 503:
The elements contained in the Tree View, shown in
In an embodiment, the elements of the Tree View comprise
This section provides several examples of user-defined layouts of the dashboard 418, shown in
As shown in
A Map Maker tool lets a user layout a visual display of a physical site. Maps can then be used in the Map Module. Maps used in the Map Module are live maps, meaning they can be zoomed and panned; and the elements on the map, such as controllers, valves, hydrozones, rainbuckets, and flow meters, provide visual clues as to their status real-time. For example, when a valve opens it is animated and changes color.
Objects placed on the map are also interactive, with a context menu. A user right-clicks the object (such as a valve), and selects an action item (such as “Open Valve”).
The Map includes a very sophisticated means of linking objects using Org-Chart like tools to show relationships among them. Such relationships can be created automatically by selecting an object, and, using the context menu, selecting “Find Related Objects.” The related objects are then linked using lines and arrows to highlight both the linkage and direction of link (parent to child, such as Controller to its Valves, or sibling, such as valve to valve).
Multiple types of modules 503, shown in
The Quick Tasks Module, shown in
A Quick Report 556 is a set of predefined reports that give the user a quick snapshot of how things are going on the property. Some “Quick Reports” are displayed in table form, and others in chart form. Most of these reports are live, meaning that the reports are updated as events occur to reflect real-time data.
An A.S. is in charge of monitoring the status and condition of clients C1, C2, and C3, plus property P1 of client C8. For this, he must do the following:
Monday morning the AS runs a copy of the dashboard 418, shown in
To check for any leaks that occurred since Friday, he clicks on the Module Selector icon from the Bubble Bar 514, shown in
All newly loaded Modules appear as undocked, separate windows. The AS docks the Report Module to the top of the dashboard 514, where it appears along side his previous modules as a tab. He then selects the Mainline Leaks report.
Next, he selects all his available clients and properties. The AS has been assigned specific rights to C1, C2, C3 and P1; therefore, these are the only clients and properties available to him. He specifies to run the report showing all events since his last run.
The report indicates 3 mainlines have leaked a significant amount of water. To send this report to his clients, he clicks the Send To Clients button, which displays the list of clients and their contact information, gives him a chance to confirm or modify the recipients, add a message to the body of the email and send the report to the appropriate contacts.
Because this is a routine task for this user, AS will add this report to a Report Group called “Monday Reports.” The settings for this report are saved as well.
To complete the remaining tasks, the user selects the appropriate reports and runs each one, also adding them to the “Monday Reports” group.
The following Monday, AS can simply log in and select the “Monday Reports” group and run all his reports in one action.
A FAO helps people at the irrigation sites, such as clients, property managers, and landscape maintenance field personnel, who call in to perform tasks on the site. The FAO is called numerous times by various users, and she may be asked to:
The FAO has two Dashboard Windows open on her multi-monitor computer system 120, shown in
When a user for client C1 calls in to open hydrozone 3 on their property P2, she selects the Manual Operations module, navigates to property P2, highlights the Zone Valve in the list of displayed valves, right-clicks and selects “Open . . . ” from the context menu.
Shortly after processing this command, the dashboard 418 receives and displays the notification that hydrozone 3 opened up. The hydrozone itself changes color on the dashboard 418 to show the new status, and the log view ads a human readable text description row to indicate the action.
In the second Dashboard Monitor, the FAO has the Map Module showing full-screen. When the caller asks her for the location of the Flow Meter, she opens the map, illustrated in
The map loads from the server 100, shown in
She then tells the caller where to find it based on the map details.
The present invention provides clear advantages over prior techniques.
Using non-decision making controllers at irrigation sites and placing irrigation algorithms at the server lever, offers several advantages. The server becomes a virtual information broker for independent dashboards, and its software can also be installed on customer servers for use with other systems. It secures links and distributes information to each independent dashboard, as needed per user, user type, user rights and momentary user needs. Moreover, controllers can be updated efficiently from central locations and could even be mobile, on trucks for example. In addition, the system can be adapted easily for other industries besides irrigation.
However, with the present invention, shown in
The dashboard provides effective monitoring of events at irrigation sites. It can automatically sense and stop significant system leaks when they occur by sending commands to close valves. Or it can send alerts to customers who can then stop the leaks. The system can also be used to display data to users through dashboards at multiple locations, so they can make decisions. In addition, by monitoring and managing the soil moisture content percentage before, during and after rain events occur, the system can take full advantage of natural rain events to optimize irrigation. As a result, water savings per property may be well in excess of 50%-70%.
Another aspect of the invention is a shared savings business model where the vendor provides a system, such as an irrigation system, and the customer only pays the vendor a percentage of the savings obtained by using the system. The savings is typically established by comparing historical usage with current usage. This business model permits the customer to begin realizing savings without budgeting capital expenditure, and it begins saving water or other resources immediately. The model encourages the vendor to design and install systems that are economical, robust, and effective. The model is effective for the vendor because the monitoring and control system is highly effective at producing substantial savings.
Another aspect of the invention is the opportunity to rapidly deploy improved control systems to save water for a community. In this example, a first entity such as an oil and gas producer may be depleting a resource such as groundwater. That entity can offset the use of the groundwater by sponsoring a water-savings program for a second entity, for example in exchange for the market value of the resource. In one example, the first entity contracts with a vendor to deploy the vendor's irrigation management systems for the second entity. The vendor installs and monitors the systems and measures the volume of water savings. This volume is then “credited” to the first entity to offset the waste of groundwater. For example, the first entity can utilize the water savings at the second entity as an offset of water overuse on the first entity's own project, or for an environmental stewardship advertisement campaign.
This model is analogous to “carbon credits” which are an accepted way to exchange conservation-related credits among entities.
The previous extended description has explained some of the alternate embodiments of the present invention. It will be apparent to those skilled in the art that many other alternate embodiments of the present invention are possible without departing from its broader spirit and scope.
It will also be apparent to those skilled in the art that different embodiments of the present invention may employ a wide range of possible hardware and of software techniques. For example, the communication among computers could take place through any number of links, including wired, wireless, infrared, or radio ones, and through other communication networks beside those cited, including any not yet in existence.
Furthermore, in the previous description the order of processes, their numbered sequences, and their labels are presented for clarity of illustration and not as limitations on the present invention.
This is a Continuation-in-part application of U.S. patent application Ser. No. 12/717,621 filed on Mar. 4, 2010 which is a Divisional application of U.S. patent application Ser. No. 12/506,614 which is a Continuation-in-part application of U.S. application Ser. No. 11/451,037 filed on Jun. 2, 2006.
