Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Status of the Claims
Claims 1,2,6,11,13-15,17,18 are amended
Claims 1-20 are pending
The rejection under 35 USC 112 is withdrawn
The rejection under 35 USC 101 is maintained
Response to Applicant Remarks
Applicant’s well-articulated remarks have been considered but are unpersuasive for the reasons below.
Regarding the rejection under 35 USC 101, applicant argues that the invention cannot be performed in the human mind. (Applicant’s 6/15/26 remarks, p.11, “The USPTO's eligibility guidance
under 35 U.S.C. 101 states that a claim falls within the mental process category only when the
steps can practically be performed in the human mind or with pen and paper. Here, the claims
require: operation of a physical fluid flow meter installed in a pipe network; aggregation of
statistical data from multiple fluid flow events; communication of the aggregated data to a
remote head-end system; determination of pressure at a remote location using pressure
variations occurring over multiple time windows. Such operations are not practically
performable in the human mind. A human cannot observe and record all fluid flow events
occurring through a utility meter over extended time windows, aggregate statistical
consumption distributions for thousands of consumption events, communicate such data to a
remote head-end system; and determine pressure at the meter using the claimed relationship
between pressure variation and consumption statistics. Accordingly, the claims do not fall
within the "Mental Processes" grouping of abstract ideas.”) The examiner respectfully disagrees.
The examiner takes the position that the claimed operation of a flow meter and aggregation of data is merely a data gathering step. Electronic flow meters capable of gathering and aggregating data for analysis over time are well known and commercially available. (“Sensus ally® Water Meter”, 10/2022, available at https://web.archive.org/web/20221030204403/https://www.xylem.com/en-us/products--services/metrology-equipment-for-utilities/meters/ally-water-meters/). It is the examiner’s understanding that the invention is not an improvement to a flow meter, but rather directed to analysis of flow meter data by a system. At the level claimed, a human could analyze flow data and identify changes in pressure over time.
Applicant also argues that the invention is a technical improvement rather than an abstract idea. (Applicant’s 6/15/26 remarks, p.12, “The claims are directed to a technological improvement in determining pressure
throughout a fluid distribution network without requiring dedicated pressure sensors. The
claims are directed to solving the technological problem of determining pressure at a fluid flow
meter without requiring a dedicated pressure sensor at the meter location. The present
invention uses pressure information from elsewhere in the network, statistical flow-cvent
information collected by the meter, and comparative analysis between different pressure
conditions to estimate pressure at the meter location. This is a technical improvement to fluid
distribution monitoring.”) The examiner respectfully disagrees.
The examiner notes, that although the invention is directed toward a water distribution utility, it nevertheless remains an abstract idea wherein what occurs is collecting data from multiple data sources, analyzing the data, and obtaining results. This general type of invention has clearly been determined by the courts to lie in the realm of abstract ideas. (Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350 (Fed. Cir. 2016), finding an abstract idea although the data analysis related to a power grid).
Regarding the “Step 2B” analysis, applicant argues, “The Office Action has not shown that the claimed combination is well-understood, routine, and conventional, as required for a Step 2B finding. The Office Action has not established that the claimed combination of pressure-window analysis and aggregated fluid-consumption statistics for determining pressure at a remote meter location is well-understood, routine, and conventional.” (Applicant’s 6/15/26 remarks, p.12). The examiner respectfully disagrees.
The examiner has stated that the flow meter and generic computing elements to be additional elements to the claims. In addition, aggregating remote data from electronic flow meters is well known and conventional in the arts. The 2B analysis involves “Evaluating additional elements to determine whether they amount to an inventive concept requires considering them both individually and in combination to ensure that they amount to significantly more than the judicial exception itself…”. (MPEP 2106.05) As the additional elements appear to be known and conventional, the remaining elements are part of the abstract idea and are not patent eligible. (“We may assume that the techniques claimed are “[g]roundbreaking, innovative, or even brilliant,” but that is not enough for eligibility… The claims here are ineligible because their innovation is an innovation in ineligible subject matter. Their subject is nothing but a series of mathematical calculations based on selected information and the presentation of the results of those calculations (in the plot of a probability distribution function). No matter how much of an advance … the claims recite, the advance lies entirely in the realm of abstract ideas, with no plausibly alleged innovation in the nonabstract application realm. An advance of that nature is ineligible for patenting.” SAP America vs. Investpic, (Fed. Cir. 2018))
Regarding the rejection under 35 USC 103, Applicant argues “The pressure estimation of Barker et al. is produced from a hydraulic model, service-node demand values, and network topology. Barker et al. simply uses consumption data as an input to a hydraulic simulation. There is no teaching or suggestion in Barker et al. as to calculating water demand values for service nodes based on aggregation of water consumption data, and estimating water flows and pressures by running a hydraulic model as featured in the present invention.”) (Applicant’s 6/15/26 remarks, p.14). The examiner respectfully disagrees.
The examiner notes that “calculating water demand values for service nodes based on aggregation of water consumption data “ does not appear to be a claimed element. Accordingly, this is not commensurate with the current scope of the claims.
Applicant also argues “Barker et al. does not teach or suggest determining pressure at a fluid flow meter as
claimed. The Office Action relies on the estimation of water flows and pressures for at least
a portion of the water distribution system of Barker et al. However, the pressure calculations
of Barker et al. occur at hydraulic model locations and service nodes. According to Barker et
al., the service nodes may represent an aggregation of multiple metered consumption points.
Thus, the calculated pressure of Barker et al. is not necessarily pressure at an individual fluid
flow meter. Compared with the present invention, Barker et al. discloses estimating conditions
at modeled nodes of a hydraulic network. Barker et al. estimates pressures at modeled
locations within a hydraulic model. Barker et al. does not disclose determining pressure at an
individual fluid flow meter as featured in the present invention.” (Applicant’s 6/15/26 remarks, p.14). The examiner respectfully disagrees.
Barker clearly discloses sensing pressure at particular meter locations in a network. (Barker, abstract, “The distribution network is divided into zones having an upstream location and a downstream location. An upstream pressure sensor detects the upstream pressure at the upstream location and the downstream pressure sensor detects the detected downstream pressure at the downstream location.”)
Applicant also argues “The cited prior art references as a whole do not disclose recording input pressure
information, wherein the input pressure information allows a determination of a difference
between the input pressure in at least one first considered time-window and the input pressure
in at least one second considered time-window as claimed.” (Applicant’s 6/15/26 remarks, p.14). The examiner respectfully disagrees.
Barker clearly discloses recording input pressure information. (See above). Barker discloses that the analysis of pressure could occurs at particular time intervals. (Barker, claim 8, “wherein the steps of method 1 are repeated after an elapsed time and the sets of probable leak locations are compared to identifying a consistent probable leak location among the sets of probable leak locations over time, wherein the consistent probably leak location is consistent across multiple sets of probable leak locations.”)
Applicant also argues “Barker et al. and Sensus ally® Water Meter do not teach or suggest aggregating, in a
fluid flow meter, at least during at least one first considered time-window and during at least
one second considered time-window, statistical data of a plurality of fluid flow consumption
events and/or fluid volume consumption events as claimed.” (Applicant’s 6/15/26 remarks, p.15). The examiner respectfully disagrees.
Sensusally at least discloses capacity to log a plurality of time data regarding flow.
(Sensus, p.1, “Benefits to you
…
Integral customer data logging of 120 days of hourly data”) It is unclear how the claimed statistical data of fluid flow events would substantially differ from the type of collected data of Sensually.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Regarding independent claims 1,14 the claimed invention recites an abstract idea without significantly more. The claims recites the abstract idea of analyzing water usage which is a mental process. Other than reciting a fluid flow meter and headend system nothing in the claims precludes the steps from being performed mentally. But for the fluid flow meter and headend system the limitations on record input pressure, aggregating statistical data, providing aggregated data, determining pressure is a process that under its broadest reasonable interpretation could be performed by mentally but for the recitation of generic computer elements. The limitations of collecting meter data are considered by the examiner to be extra solution activity. Applicant has not invented of smart fluid metering. The addition of insignificant activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (see MPEP 2106.05 g). If claim limitations, under the broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas.
The judicial exception is not integrated into a practical application. The computers are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using generic computer components. The additional element(s) does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Simply implementing the abstract idea on a generic computer environment is not a practical application of the abstract idea and does not take the claim out of the mental process .
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, with respect to integration of the abstract idea into a practical application, the additional element of a fluid meter and headend system amounts to no more than mere instructions to apply the exception using a generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Also, the additional elements of collecting meter data were considered by the examiner to be extra solution activity above. Applicant has not invented storing, inputting and displaying data. The addition of insignificant activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (see MPEP 2106.05 g; See also the Sensus reference below). Collecting, analyzing and displaying information, and receiving and transmitting over a network are conventional in the computing arts. (MPEP 2106.05h; See also Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350 (Fed. Cir. 2016), The court looked at the character of the claim as a whole, but found the claim directed to the abstract idea of collecting and analyzing data even though the type of data collected was limited to data from an electric power grid.; see also MPEP 2106.05, Alice v. CLS, “. Nearly every computer will include a ‘communications controller’ and ‘data storage unit’ capable of performing the basic calculation, storage, and transmission functions required by the method claims.”). The claims are not patent eligible.
Regarding the dependent claims, these claims are directed to limitations which serve to limit the water usage analysis steps. The subject matter of claims 2/15 (shift in histography), 3/16 (initiating a change in pressure), 4 (aggregating data by a plurality of meters) ,5 (battery powered wireless ultrasonic meter), 6/18 (identify characteristic flows), 7 (identifying maximum flows), 8/19 (fluid pressure equation), 9 (time windows are selected between pressure differences), 10 (identify flow events by filtering consumption events), 11 (reducing data parameters), 12/20 (determine relative change in pressure only if relative change is 10 to 25 percent), 13 (time span between windows of consideration), 17 (plurality of meters appear to add additional steps to the abstract idea, implemented by generic computers. The examiner notes that claim 5 recites a particular flow meter, but this is conventional in the art. (See the Spire reference below). Claims 8/19 recite an equation, but this is also an abstract mathematical concept. These claims neither introduce a new abstract idea nor additional limitations which are significantly more than an abstract idea. They provide descriptive details that offer helpful context, but have no impact on statutory subject matter eligibility.
Therefore the limitations on the invention, when viewed individually and in ordered combination are directed to in-eligible subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1,3,4,7,9,11,13, 14, 15, 16, are rejected under 35 U.S.C. 103 as being unpatentable over
Barker 20180195926 A1 in view of
“Sensus ally® Water Meter”, 10/2022, available at https://web.archive.org/web/20221030204403/https://www.xylem.com/en-us/products--services/metrology-equipment-for-utilities/meters/ally-water-meters/
Regarding Claim 1,
A method for determining a fluid pressure at a fluid flow meter that is installed in a pipe network that is supplied with fluid at at least one of a varying or variable input pressure, wherein the method comprises the steps of:
Barker is directed to a system for detecting leaks in a water network. (Barker, abstract) Barker discloses measuring pressure in the network at multiple points. (Barker, para 0005, “[0005] The typical water distribution system has many distributed consumption points, such as the metered consumption points associated with the various industrial, commercial, and residential customers of the operator of the water distribution system. Hydraulic models include so-called “service nodes” to model the consumption points in the water distribution system. A service node is a physical location within the water distribution network that represents a demand in a hydraulic model, which can be a single demand or an aggregation of multiple demands. As an example, all or a subset of the metered consumption points along a branch 18 may be represented by a corresponding service node in the hydraulic model. The service node would have a modeled physical location at a pipe location in or leading into the involved branch 18. This is distinguishable from the prior art, where a hydraulic file is created not based on water demand and service nodes, but on topology.”; para 0018, “[0018] The present disclosure relates to a method, apparatus, and system for leak detection in a distribution network having consumption meters. The distribution network is divided into zones having an upstream location and a downstream location. An upstream pressure sensor detects the upstream pressure at the upstream location and the downstream pressure sensor detects the detected downstream pressure at the downstream location. A downstream pressure lookup table is used to determine an expected pressure at each downstream location based on a range of hypothetical upstream pressures at the corresponding upstream location and consumption data from the consumption meters. The expected pressure and the detected downstream pressure at each downstream location are compared to determine if the calculated discrepancy exceeds a discrepancy threshold. If the calculated discrepancy exceeds the discrepancy threshold, a leak location lookup table containing a set of potential leak locations based on a range of hypothetical discrepancies at each downstream location is used to determine a set of probable leak locations corresponding to the calculated discrepancy.”)
recording input pressure information, wherein the input pressure information allows a determination of a difference between the input pressure in at least one first considered time-window and the input pressure in at least one second considered time-window;
(Barker, para 0062, “[0062] The leak detection method locates the set of potential leak locations through the principle of correlation. For a single discrepancy determination, the size and location of a potential leak location are interdependent and many combinations may produce the same pressure discrepancy. The set of potential leak locations may be narrowed, or confidence in location accuracy may be improved, by comparing multiple data readings and discrepancy determinations from time periods when the distribution network demands and pressures are significantly different. Specifically, by using multiple reads, infeasible combinations of size and location of leaks are identified and eliminated, increasing confidence and narrowing the set of viable leak locations. Once confidence in the location of a leak reaches a given standard, the Leak Detection System may notify the utility, trigger actions to slow or stop the leak, or activate other measures.”)
providing the aggregated statistical data in at least one of regular intervals and on demand to a head-end system that has access to the input pressure information; and
(Barker, para 0047, “[0047] FIG. 4 illustrates a method 400 performed by a computer apparatus, such as the computer apparatus 30. However, other computer arrangements may be used for carrying out the method 400. Further, one or more steps or operations in the illustrated method 400 may be performed in an order other than the example order suggested by the diagram. Still further, one or more steps may be performed concurrently and/or in conjunction with other processing, and it will be appreciated that all or part of the illustrated processing may be performed on a repeating or looped basis, e.g., responsive to periodically updated field data incoming from the AMR network 26, on a time, periodic basis, such as every ten minutes, every hour, etc.”)
determining, by the head-end system, a fluid pressure at the fluid flow meter based on:
a change in the aggregated statistical data between the at least one first considered time-window and the at least one second considered time-window; and
the difference between the input pressure in the at least one first considered time-window and the input pressure in the at least one second considered time-window.
(Barker, para 0049, “[0049] The method 400 further includes calculating (Block 406) water demand values for each service node 52, based on an aggregation of the water consumption data for all of the water meters 20 that have been automatically associated with the service node 52. Still further, the method 400 includes estimating (Block 408) water flows and pressures for at least a portion of the water distribution system 10, by running the hydraulic model with the calculated water demand values, and performing (Block 410) a control operation for the water distribution system 10. The control operation is performed based on the estimated water flows and pressures, and comprises at least one of leak detection, pumping or storage control, and treatment or flushing control.”)
Barker does not explicitly disclose
aggregating, in the fluid flow meter, at least during the at least one first considered time-window and during the at least one second considered time-window, statistical data of at least one of a plurality of fluid flow events and a plurality of fluid volume consumption events;
Sensus is marketing material for a smart water meter. (Sensus, p.1) Sensus discloses the meter may log customer water data. (Sensus, p.1, “Benefits to you
Control three stages of water flow remotely (on, off, reduced)
Get smart alarms including empty pipe, high flow, reverse flow, low and high pressure and temperature, leak and tamper
Detect leaks to save money and conserve water
Monitor pressure at service connection
Monitor freeze conditions
Improve operational efficiency (fewer truck rolls)
Improve customer service
Product Features
Integrated unit that incorporates an electronic register, integral three-state ball valve, temperature sensor, pressure sensor, and a measuring device encased in an external housing
Shut-off valve has three states—open, closed, and reduced flow
Bulk remote service shut-off/turn-on available with Service Management Application
A 20-year life cycle and a 15-year accuracy warranty
Smart alarms including empty pipe, high flow, reverse flow, low and high pressure and temperature, customer leak and magnetic tamper
All-electronic, programmable, 9-digit register, hermetically sealed with a tempered glass cover
Integral customer data logging of 120 days of hourly data
Integrated two-way communication for AMI”). It would have been obvious to one of ordinary skill in the art before the filing date of the invention to combine Barker with the meter of Sensus with the motivation of improving utility efficiency. Id.
Regarding Claim 3, Barker and Sensus disclose the method of claim 1.
further comprising initiating a known change of the input pressure between the at least one first considered time-window and the at least one second considered time-window.
(Barker, para 0064, “The firmware in operation inputs the pressure sensor and consumption meter data into the downstream pressure lookup table to determine the calculated pressure for a downstream pressure sensor. As an alternative to using the table, the firmware may perform the series of Bernoulli calculations each time.”)
Regarding Claim 4, Barker and Sensus disclose the method of claim 1.
wherein aggregating the statistical data is performed during the same time-windows by a plurality of fluid flow meters that are installed in the pipe network.
See prior art rejection of claim 1.
Regarding Claim 7, Barker and Sensus disclose the method of claim 1.
wherein the step of aggregating the statistical data comprises identifying maximum fluid flow events.
(Barker, abstract, “The expected pressure and the detected downstream pressure at each downstream location are compared to determine if the calculated discrepancy exceeds a discrepancy threshold. If the calculated discrepancy exceeds the discrepancy threshold, a leak location lookup table containing a set of potential leak locations based on a range of hypothetical discrepancies at each downstream location is used to determine a set of probable leak locations corresponding to the calculated discrepancy.”)
Regarding Claim 9, Barker and Sensus disclose the method of claim 1.
Barker does not explicitly disclose
wherein the at least one first considered time-window and the at least one second considered time-window are selected to be time-windows between which the input pressure typically differs.
(Barker, para 0047, “[0047] FIG. 4 illustrates a method 400 performed by a computer apparatus, such as the computer apparatus 30. However, other computer arrangements may be used for carrying out the method 400. Further, one or more steps or operations in the illustrated method 400 may be performed in an order other than the example order suggested by the diagram. Still further, one or more steps may be performed concurrently and/or in conjunction with other processing, and it will be appreciated that all or part of the illustrated processing may be performed on a repeating or looped basis, e.g., responsive to periodically updated field data incoming from the AMR network 26, on a time, periodic basis, such as every ten minutes, every hour, etc.”)
Regarding Claim 11, Barker and Sensus disclose the method of claim 1.
wherein the step of aggregating the statistical data comprises reducing the amount of data to parameters that are indicative of at least one of characteristic fluid flow events and characteristic fluid volume consumption events.
(Barker, para 0062, “[0062] The leak detection method locates the set of potential leak locations through the principle of correlation. For a single discrepancy determination, the size and location of a potential leak location are interdependent and many combinations may produce the same pressure discrepancy. The set of potential leak locations may be narrowed, or confidence in location accuracy may be improved, by comparing multiple data readings and discrepancy determinations from time periods when the distribution network demands and pressures are significantly different. Specifically, by using multiple reads, infeasible combinations of size and location of leaks are identified and eliminated, increasing confidence and narrowing the set of viable leak locations. Once confidence in the location of a leak reaches a given standard, the Leak Detection System may notify the utility, trigger actions to slow or stop the leak, or activate other measures.”)
Regarding Claim 13, Barker and Sensus disclose the method of claim 1.
wherein there is time span between the at least one first considered time-window and the at least one second considered time-window, wherein the input pressure has or was changed at least one of gradually and stepwise in the time span between the first considered time-window and the second considered time-window.
(Barker, para 0047, “[0047] FIG. 4 illustrates a method 400 performed by a computer apparatus, such as the computer apparatus 30. However, other computer arrangements may be used for carrying out the method 400. Further, one or more steps or operations in the illustrated method 400 may be performed in an order other than the example order suggested by the diagram. Still further, one or more steps may be performed concurrently and/or in conjunction with other processing, and it will be appreciated that all or part of the illustrated processing may be performed on a repeating or looped basis, e.g., responsive to periodically updated field data incoming from the AMR network 26, on a time, periodic basis, such as every ten minutes, every hour, etc.”)
Regarding Claims 14, 15, 16,
See prior art rejections of claims 1,2,3
Regarding Claim 17, Barker and Sensus disclose the method of claim 14.
further comprising at least one further fluid flow meter to provide a plurality of flow meters configured to aggregate statistical data of at least one of a plurality of fluid flow events and a plurality of fluid volume consumption events and to provide the aggregated data in at least one of regular intervals and on demand to the head-end system, wherein aggregating the statistical data is performed during the same time-windows by the plurality of fluid flow meters that are installed in the pipe network.
See prior art rejection of claim 1.
Claims 2,10,6,18 are rejected under 35 U.S.C. 103 as being unpatentable over
Barker 20180195926 A1 in view of
“Sensus ally® Water Meter”, 10/2022, available at https://web.archive.org/web/20221030204403/https://www.xylem.com/en-us/products--services/metrology-equipment-for-utilities/meters/ally-water-meters/
In view of Peleg 7920983
Regarding Claim 2, Barker and Sensus disclose the method of claim 1.
wherein the change of the aggregated statistical data is a shift of at least one of one or more characteristic fluid flow peaks and fluid volume consumption peaks … from the at least one first considered time-window to the at least one second considered time-window.
(Barker, para 0064-65, “[0064] The downstream pressure lookup table 528 is generated by applying the Bernoulli calculation described above for each possible combination of each consumption meter 530 reading and upstream pressures at each upstream pressure sensor, such as starting point 516, and described below. Although these variables are continuous, they are physically and practically bound and may be discretized with a step smaller than the accuracy of the sensors and meters. The firmware in operation inputs the pressure sensor and consumption meter data into the downstream pressure lookup table to determine the calculated pressure for a downstream pressure sensor. As an alternative to using the table, the firmware may perform the series of Bernoulli calculations each time.
[0065] The leak location lookup table is generated by using correlation as described above for each possible combination of upstream pressure sensor readings, consumption meter readings, and possible discrepancies between the calculated pressure and detected downstream pressure for downstream sensor or sensors as described above, shown in FIG. 10, and described further below:”; para 0085, “[0085] Furthermore, the set of potential leak locations 920 may be combined with prior data to calculate the size of the leak at step 922 using the Real-Time Hydraulic Model. If the set of potential leak locations and corresponding sizes are determined at step 930 to meet a predetermined confidence standard, the utility may be notified of a leak at step 940. Alternatively, the method may include taking automated actions to stop or slow the leak, or actuate controls to further quantify the leak location or calculated size, for instance by controlling the flow and/or pressure within the distribution network.”)
Barker does not explicitly disclose
in an event histogram
Peleg is directed to a water utility monitoring system. (Peleg, abstract). Peleg discloses classifying water events and displaying results to a user as a graph. (Peleg, Col.11,lns.35-64, “Event Decision and Classification Engine 207 is operative to compare a statistical analysis from the M Anomaly Detectors 206 to determine the overall statistical likelihood of the no-anomaly hypothesis given recent meter readings. The Engine 207 would increase the statistical likelihood of an event based on the detection of multiple anomalies, from the same or different meters and at the same time or over a given time period, that all consistently indicate the occurrence of the event. For example, one anomaly may represent the start of an event and another anomaly may represent a change in the event or the end of the event, and the Classification Engine 207 recognizes those anomalies as being related to a single event. As another example, two anomalies from different meters related to increased flow, in a similar time and from related locations, would both indicate the same event. In one embodiment, heuristics are used to determine the overall statistical likelihood of a meter reading, based on a combination of the statistical likelihood of a reading from the temporal statistical data, and the statistical likelihood of a reading from the spatial statistical data. For example, if the historical statistical data comparison indicates that the meter's current reading is only 15% likely to be so high, but the Spatial statistical data comparison indicates that the meter's current reading is 95% likely to be so high, then the overall reading likelihood may be 75% likely to be so high. See, for example, Koziol, James and Tuckwell, Henry, “A Bayesian Method for Combining Statistical Tests.” Journal of Statistical Planning and Inference 1999: 78(1-2), 317-323, herein incorporated by reference”; Peleg, col.13,lns.14-26, “For example, if the system detects a leak and sends a leak event to 210, the system provides the event data from the event record and the visualization of the data through maps, graphs and the like to show, for example, a comparison of the present, actual values against predicted or past values. For example, one visualization of the event data may be in the form of a graph showing flow rate over time and a highlighted portion of the increase in flow rate indicative of a leak, to help the user focus on important aspects of the event. Sample screenshots for the Event Tracking Interface 210 are shown in FIGS. 11-15.”)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to combine Barker and Sensus with the dashboard of Peleg with the motivation of monitoring water events. Id.
Regarding Claim 10, Barker and Sensus disclose the method of claim 1.
Barker does not explicitly disclose
wherein the step of aggregating the statistical data comprises identifying characteristic fluid flow events by filtering associated characteristic fluid volume consumption events.
Peleg is directed to a water utility monitoring system. (Peleg, abstract). Peleg discloses that an event may be explained as consistent with historical usage before treating an event as an anomaly. (Peleg, col.20,lns.54-64, “The predictor and anomaly detectors represented by element 1005 determine whether or not there is a statistically significant reoccurring flow having a similar magnitude each time. In one embodiment, the system compares the periods of increased flow with other historical flow data of the meter or network to determine a nearly-constant increase in the magnitude of flow during reoccurring periods. If the system detects similar magnitudes each time, and this did not occur further in the past, the system proceeds to step 1006 to determine if the event can be explained by another factor.”)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to combine Barker and Sensus with the historical analysis of Peleg with the motivation of monitoring water events. Id.
Regarding Claim 6, Barker and Sensus disclose the method of claim 1.
Barker does not explicitly disclose
wherein the step of aggregating the statistical data comprises identifying repetitive characteristic fluid flow events caused by one or more consumer units that have a at least one of a constant characteristic fluid flow profile and/or a constant characteristic fluid volume consumption profile and a constant characteristic hydraulic resistance profile.
Peleg is directed to a water utility monitoring system. (Peleg, abstract). Peleg discloses that an event may be explained as consistent with identified historical usage before treating an event as an anomaly. (Peleg, col.20,lns.54-64, “The predictor and anomaly detectors represented by element 1005 determine whether or not there is a statistically significant reoccurring flow having a similar magnitude each time. In one embodiment, the system compares the periods of increased flow with other historical flow data of the meter or network to determine a nearly-constant increase in the magnitude of flow during reoccurring periods. If the system detects similar magnitudes each time, and this did not occur further in the past, the system proceeds to step 1006 to determine if the event can be explained by another factor.”)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed to combine Barker and Sensus with the historical analysis of Peleg with the motivation of monitoring water events. Id.
Regarding Claim 18,
See prior art rejection of claim 6.
Claims 5, are rejected under 35 U.S.C. 103 as being unpatentable over
Barker 20180195926 A1 in view of
“Sensus ally® Water Meter”, 10/2022, available at https://web.archive.org/web/20221030204403/https://www.xylem.com/en-us/products--services/metrology-equipment-for-utilities/meters/ally-water-meters/
In view of
Spire Metering, “Ultrasonic Water Meters”, https://web.archive.org/web/20210616173650/https://spiremt.com/ultrasonic-water-meters.html
Regarding Claim 5, Barker and Sensus disclose the method of claim 1.
and the aggregated statistical data is provided by wirelessly transferring the data to the head-end system.
(Barker, para 0039, “For example, the AMR network 26 includes radio frequency communication modules incorporated in or coupled to meters, pressure sensors, flow sensors, etc., for wireless reporting to base stations or other network nodes. A person having ordinary skill in the art will recognize that communication of information throughout the present disclosure may be wired or wireless, including but not limited to cellular, RF, narrow band, Ethernet, and other mechanisms known in the art.”)
Barker does not explicitly disclose
wherein the fluid flow meter is a battery-powered ultrasonic flow meter,
Spire discloses specifications for residential water meters. (Spire, p.1, “Smart Ultrasonic Water Meter
Uniquely developed for domestic water metering applications, the SpireTap™ contains no moving parts and is resistant to normal wear and tear. The meter is designed to be resistant to failure due to harsh environment, solids in water, or magnetic interference. Sensor performance will not degrade over time, maintaining overall system accuracy. The meter body is compact, allowing installation in locations with limited straight run. Meter display includes flow velocity, flow total, working time, leak detection, and other parameters. The field replaceable battery has a ten year service life. The SpireTap is available with NB-IoT wireless technology which allows the water meter readings to be acquired remotely on a smartphone or other internet connected devices such as a computer or tablet.”) It would have been obvious to one of ordinary skill in the art before the filing date of the invention to combine Barker and Sensus with the meter of Spire with the motivation of improving utility. Id.
Allowable Subject Matter
Claims 8,12,19,20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims AND the rejection under 35 USC 101 is overcome.
Conclusion
Relevant art not relied on but made of record include
Cardell, “Using smart meters and data
mining to inform demand
management, 2015,
https://watersensitivecities.org.au/wp-content/uploads/2016/07/TMR_C5-1_Smart_metering_data_mining.pdf
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/ALLEN C CHEIN/Primary Examiner, Art Unit 3627
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