DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1 and 4-8 are pending.
Claims 2-3 are cancelled.
Information Disclosure Statement
The references cited in the information disclosure statements (IDS) submitted on 07/20/2023 and 04/26/2024 have been considered by the examiner.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 6-7 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 6 recites:
“wherein the normalization rule is a rule that defines to acquire an upper limit value-of-status value and a lower limit value-of-status value which are an upper limit value and a lower limit value possible for each status value at a time point when each status value is acquired from the device, to decide a position of each status value within a normalization range which is a numerical value range from a predetermined upper limit value to a predetermined lower limit value, based on a ratio of a difference between each status value and the upper limit value-of-status value to a difference between each status value and the lower limit value-of-status value, and to normalize each status value, and
the processing circuitry
acquires a normalized reference value obtained according to the normalization rule by acquiring an upper limit value-of-reference value and a lower limit value-of-reference value which are an upper limit value and a lower limit value possible for each reference value at a time point when each reference value is acquired from the device, and by deciding a position of each reference value within the normalization range, based on a ratio of a difference between each reference value and the upper limit value-of-reference value to a difference between each reference value and the lower limit value-of-reference value, and
according to the normalization rule, acquires an upper limit value-of-diagnosis value and a lower limit value-of-diagnosis value which are an upper limit value and a lower limit value possible for each diagnosis value at a time point when each diagnosis value is acquired from the device, decides a position of each diagnosis value within the normalization range, based on a ratio of a difference between each diagnosis value and the upper limit value-of-diagnosis value to a difference between each diagnosis value and the lower limit value-of-diagnosis value, and normalizes each diagnosis value.” (emphasis added)
It is unclear what Applicant means by “possible” upper limit and lower limit values without reciting objective boundaries of what Applicant means by the “possible” upper limit and lower limit values. Further, it is unclear how a predetermined upper limit value to a predetermined lower limit value may relate to the possible upper limit and lower limit values, if there is any relationship. Appropriate clarification through claim amendment is respectfully requested. For purposes of examination, the claim will be interpreted as: wherein the normalization rule calculates a ratio of a difference between each reference value and a predetermined upper limit value-of-reference value to a difference between each reference value and a predetermined lower limit value-of-reference value to determine each of the plurality of normalized reference values, and calculates a ratio of a difference between each diagnosis value and a predetermined upper limit value-of-diagnosis value to a difference between each diagnosis value and a predetermined lower limit value-of-diagnosis value to determine each of the plurality of normalized diagnosis values.
The claim 7 is rejected under 35 U.S.C. 112(b) for similar reasons as discussed above for the claim 6.
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 and 4-8 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.
(Step 2A, Prong One)
Independent claim 1 recites, “... to acquire a plurality of normalized reference values being values obtained from normalization of a plurality of reference values according to a predetermined normalization rule, the plurality of reference values being a plurality of status values acquired from a device at a plurality of times within a normal estimation period during which the device is estimated to operate normally, each status value indicating an operational status of the device; … to normalize the plurality of diagnosis values according to the normalization rule; and to diagnose the operational status of the device during the diagnosis period, by comparing a median value of the plurality of normalized reference values with a median value of a plurality of normalized diagnosis values obtained from the normalization of the plurality of diagnosis values.”
Under their broadest reasonable interpretation and based on the description provided in the published Specification, such as paragraphs [0117] to [0122], for instance, normalization functions, as claimed, is a process that entails purely mathematical relationships, mathematical formulas or equations, and mathematical calculations.
Under its broadest reasonable interpretation, if a claim limitation covers performance that can be executed in the human mind, but for the recitation of generic electronic devices or generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Under their broadest reasonable interpretation and based on the description provided in the Specification, such as paragraphs [0174] and [0182], for instance, the comparing function is a mental process that can be performed through observation, evaluation and judgement based on a acquired sensor data or image. That is, other than reciting a “processing circuitry” (a generic electronic device or generic computer component), a person may perform, through observation, evaluation and judgement, the comparing function.
Accordingly, the claim recites an abstract idea.
(Step 2A, Prong Two)
This judicial exception is not integrated into a practical application. In particular, the claim recites the additional limitations of, “processing circuitry … to acquire from the device, the plurality of status values as a plurality of diagnosis values during a diagnosis period during which it is not clear whether or not the device operates normally and which is after the normal estimation period.”
The additional limitation “processing circuitry” as recited in the claim that are configured to carry out the additional and abstract idea limitations may be tools that are used to normalize and compare as recited in the claim, but recited so generically that they represent no more than mere instructions “to apply” the judicial exceptions on or using generic electronic or computer components. Implementing an abstract idea on generic electronic or computer components as tools to perform an abstract idea is not indicative of integration into a practical application. see MPEP 2106.05(f)
The additional limitation “to acquire from the device, the plurality of status values as a plurality of diagnosis values during a diagnosis period during which it is not clear whether or not the device operates normally and which is after the normal estimation period” is an insignificant extra-solution activity under MPEP 2106.05(g), without imposing meaningful limits. The limitation amounts to necessary data gathering. (i.e., all uses of the recited judicial exception require such data gathering or data output).
The claim does not recite an improvement in a technology as set forth in MPEP 2106.04(d) and MPEP 2106.05(a). Accordingly, the additional limitations recited in the claim do not integrate the abstract idea into a practical application.
In view of the foregoing, the additional limitations are not sufficient to demonstrate integration of a judicial exception into a practical application.
(Step 2B)
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
The additional features including “processing circuitry”, as recited in the claim that are configured to carry out the additional and abstract idea limitation may be tools that are used for the functions recited in the claim, but recited so generically that they represent no more than mere instructions “to apply” the judicial exceptions on or using a generic electronic or computer component. Implementing an abstract idea on generic electronic or computer components as tools to perform an abstract idea does not amount to significantly more. See Elec. Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1355 (Fed. Cir. 2016) (“Nothing in the claims, understood in light of the specification, requires anything other than off-the-shelf, conventional computer, network, and display technology for gathering, sending, and presenting the desired information.”)
The additional limitation “to acquire from the device, the plurality of status values as a plurality of diagnosis values during a diagnosis period during which it is not clear whether or not the device operates normally and which is after the normal estimation period” represents a function that is recognized as well-understood, routine, and conventional, for instance, as demonstrated in ABIPROJO et al. (US 2015/0330650 A1) paragraph [0217] (“In FIG. 5A, a technique for normalizing operating parameter data associated with an HVAC system is shown. The technique begins at 1304 where measured operating parameter data is received from the local devices, for example only, the condensing monitor module 316 and the air handler monitor module 322. The technique continues at 1308 where, at the remote monitoring system, the data is analyzed by the processing module 1400. For example, the processing module 1400 identifies a portion of the measured operating parameter data that corresponds to an operating parameter value. At 1312, the processing module 1400 identifies steady-state segments of operating parameter data as described above.”), FUJIKAWA et al. (JP 2019028834 A) Abstract (“To provide an outlier diagnosis device capable of easily and efficiently selecting a system to be inspected without setting an individual threshold value for equipment composed of a plurality of systems. A data extraction unit acquires information on a normal period of a system, extracts data on the normal period of the system as normal period data from a database, and data on the system during a diagnosis period, which is a period to be diagnosed. Is extracted from the database as diagnostic period data.”), and VITULLO (US 2019/0302709 A1) paragraph [0124] (“Still referring to FIG. 6, memory 612 is shown to include a data collector 614, a timeseries database 616, an energy management application 618, and an analytics service 620. Components 614-620 can operate together to obtain timeseries data from building management system devices, such as devices of HVAC systems, airside system, waterside systems, etc.; store the data as a data timeseries; generate a result timeseries based on the data timeseries after performing an analysis on the data timeseries; and transmit the data timeseries and the results timeseries to BMS controller 366 or an external user device. Examples of timeseries data gathering and processing can be found in U.S. patent application Ser. No. 15/644,581 (now U.S. Pat. No. 10,169,486) filed Jul. 7, 2017, the entirety of which is incorporated by reference herein. Components 614-620 can be configured to receive inputs from and/or send outputs to building network 602 and other data sources and provide searching, reporting, and/or command capabilities.”)
Therefore, the additional claimed features do not amount to significantly more and the claim is not patent eligible.
Independent claim 8 is not patent eligible for similar reasons, as explained above, for independent claim 1.
Dependent claims 4 and 6-7 are directed to further defining the abstract idea as recited in independent claim 1.
Dependent claim 5 recites acquiring limitations that are directed to insignificant extra-solution activities of gathering data, and recite diagnosing limitation that is directed to further defining the abstract idea as recited in independent claim 1.
Claim Rejections - 35 USC § 103
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, 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, 4-5 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over ABIPROJO et al. (US 2015/0330650 A1) (“Abiprojo”), in view of Kamamann et al. (US 2014/0008132 A1) (“Kamamann”).
Regarding independent claim 1, Abiprojo teaches:
A diagnosis apparatus comprising: (Abiprojo: [0020] “Another monitoring system for a heating, ventilation, or air conditioning (HVAC) system of a building is provided and includes a monitoring server, located remotely from the building. The monitoring server is configured to (i) receive operating parameter data from a monitoring device at the building that measures an operating parameter of the HVAC system, (ii) generate a plurality of data clusters from the operating parameter data, each data cluster corresponding to operating parameter data generated during steady-state operation of the HVAC system, (iii) calculate an average operating parameter value for each data cluster, (iv) calculate normalized operating parameter values based on normalizing the average operating parameter values for the data clusters over a predetermined normalization time period, (v) performing a trend analysis of the normalized operating parameter values by comparing each normalized operating parameter value with previous normalized operating parameter values, determining a trend for the normalized operating parameter values associated with each normalized operating parameter value, and associating a trend confidence level with each normalized operating parameter value, (vi) determine whether an air filter of the HVAC system needs to be replaced based on the trend analysis, and (vii) generate a notification based on the determination indicating that the air filter needs to be replaced.”)
processing circuitry; (Abiprojo: [0049] “A server of the monitoring system includes a processor and memory. The memory stores application code that processes data received from the air handler monitor and condensing monitor modules and determines existing and/or impending failures, as described in more detail below. The processor executes this application code and stores received data either in the memory or in other forms of storage, including magnetic storage, optical storage, flash memory storage, etc. While the term server is used in this application, the application is not limited to a single server.”)
to acquire a plurality of normalized reference values being values obtained from normalization of a plurality of reference values according to a predetermined normalization rule, the plurality of reference values being a plurality of status values acquired from a device at a plurality of times within a normal estimation period during which the device is estimated to operate normally, each status value indicating an operational status of the device; (Abiprojo: [0020] as discussed above) (Abiprojo: [0042] “As used in this application, the term HVAC can encompass all environmental comfort systems in a building, including heating, cooling, humidifying, dehumidifying, and air exchanging and purifying, and covers devices such as furnaces, heat pumps, humidifiers, dehumidifiers, and air conditioners. HVAC systems as described in this application do not necessarily include both heating and air conditioning, and may instead have only one or the other.”) (Abiprojo: [0217] “In FIG. 5A, a technique for normalizing operating parameter data associated with an HVAC system is shown. The technique begins at 1304 where measured operating parameter data is received from the local devices, for example only, the condensing monitor module 316 and the air handler monitor module 322. The technique continues at 1308 where, at the remote monitoring system, the data is analyzed by the processing module 1400. For example, the processing module 1400 identifies a portion of the measured operating parameter data that corresponds to an operating parameter value. At 1312, the processing module 1400 identifies steady-state segments of operating parameter data as described above.”) (Abiprojo: [0220] “At 1332, the processing module 1400 normalizes the values within each data cluster. The processing module 1400 generates a normalized data value corresponding to each of the data clusters. For example, the processing module 1400 may determine an average value for each data cluster. Alternatively, the processing module 1400 may normalize data within each of the data clusters. The processing module 1400 may further generate a combined normalized data value corresponding to related data clusters as described above. At 1336, the processing module 1400 stores the normalized data values and returns to 1304.”) (Abiprojo: [0221] “In FIG. 5B, a technique for diagnosing a fault in an air filter within an HVAC system is shown. The technique begins at 1104, where an initial baseline and threshold are established during an initialization period. For example, the processing module 1400 establishes an initial baseline and threshold based on a trajectory analysis of the normalized data values. This may occur during the commissioning of a new monitoring system, which may be either in a new HVAC system or a retrofit installation. The normalized data values are analyzed over a predetermined initialization period of time, for example an initial 2 week period after the HVAC system is initiated or installed. During the predetermined initialization period, the normalized data values are analyzed to establish an average operating parameter value for the HVAC system.”) [The time during the period of determining the baseline reads on “a plurality of times within a normal estimation period”. The measured operating parameter data during period of determining the baseline reads on “a plurality of reference values”. The normalized operating parameter values during the period of determining the baseline read on “a plurality of normalized reference values”. The operating parameter data associated with the comfort system reads on “a plurality of status values acquired from a device”. The technique for normalizing operating parameter data reads on “a predetermined normalization rule”.]
to acquire from the device, the plurality of status values as a plurality of diagnosis values during a diagnosis period during which it is not clear whether or not the device operates normally and which is after the normal estimation period; to normalize the plurality of diagnosis values according to the normalization rule; and (Abiprojo: [0217] as discussed above) (Abiprojo: [0222] “The processing module 1400 determines an initial baseline and threshold based on the average operating parameter value. For example only, the processing module 1400 at 1104 sets the initial baseline equal to the average operating parameter value from the predetermined initialization period and sets the initial threshold relative to the baseline. The technique continues at 1108, where normalized data values are selected. The technique continues at 1112 where, at the remote monitoring system, the data is analyzed by the processing module 1400.”) [The period after the initialization period reads on “a diagnosis period”. The measured operating parameter data after the initialization period being normalized reads on “a plurality of diagnosis values … to normalize …”.]
to diagnose the operational status of the device during the diagnosis period, by comparing a … value of the plurality of normalized reference values with a … value of a plurality of normalized diagnosis values obtained from the normalization of the plurality of diagnosis values. (Abiprojo: FIG. 5B) (Abiprojo: [0222] as discussed above) (Abiprojo: [0228] “When at 1120 the deviation was not a sudden change in the operating parameter, the processing module 1400 proceeds to 1128. At 1128, the processing module 1400 determines whether a rate of change of normalized data values is greater than a rate of change threshold and is progressing in the direction of the filter developing dirt. The processing module 1400 determines a rate of change over a predetermined period. For example only, the processing module 1400 determines a rate at which the current draw is changing over the previous 5 consecutive days. It is understood the processing module 1400 may determine a rate of change over any suitable time period.”) (Abiprojo: [0232] “At 1132, the processing module 1400 determines whether the normalized data value is greater than a predetermined threshold. For example, the predetermined threshold may be the initial threshold set at 1104. The predetermined threshold may be the adapted threshold set at 1124. Alternatively, depending on the component, the processing module 1400 may determine at 1132 whether the normalized data value is less than the predetermined threshold.”) [The average normalized data values read on “a … value of the plurality of normalized diagnosis values”, and the corresponding thresholds based on the baseline read on “a … value of the plurality of normalized reference values”.]
Abiprojo does not expressly teach: a … value is a median value.
Kamamann teaches:
a … value is a median value. (Kamamann: [0053] “According to the invention, a minimum number of measurements, for example more than 20 measurements, are performed for the "engine torque" measured physical variable. From the measured values which are acquired therefrom it is then respectively possible to determine the engine torque, for example by means of statistical methods such as the formation of mean values or the median method. Alternatively, the engine torque is determined directly as a measured variable. In addition, loads which are subject to tolerance are calculated and are then considered statistically. Finally, the load of the motor vehicle can be calculated from the engine torque.”) (Kamamann: [0054] “The median denotes here a boundary between two halves, as illustrated in FIG. 3. In statistics, the median halves a distribution (according to FIG. 3 the median is located on the zero line). Compared to the arithmetic mean, also referred to as the average, the median has the advantage of being robust with respect to outliers (extremely different values).”)
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Abiprojo and Kamamann before them, to modify the … value or the average values of the normalized data value, to incorporate using median values in place of the average values.
One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to do this modification because it would allow for minimizing outlier values to affect the resulting value. (Kamamann: [0054] “The median denotes here a boundary between two halves, as illustrated in FIG. 3. In statistics, the median halves a distribution (according to FIG. 3 the median is located on the zero line). Compared to the arithmetic mean, also referred to as the average, the median has the advantage of being robust with respect to outliers (extremely different values).”)
Regarding claim 4, Abiprojo and Kamamann teach all the claimed features of claim 1. Abiprojo further teaches:
wherein the processing circuitry selects a diagnosis result notification message from among a plurality of diagnosis result notification messages each of which indicates a diagnosis result, depending on a difference between the median value of the plurality of normalized diagnosis values and the median value of the plurality of normalized reference values, and outputs the selected diagnosis result notification message. (Abiprojo: [0143] “In response to changes in measured values corresponding to an operating parameter, the processing module 1400 determines whether to generate an alert indicating to the customer that performance of the HVAC system has degraded. Further, the processing module 1400 may selectively recommend and/or instruct the customer to repair and/or replace components within the HVAC system based on the monitored changes in the operating parameter.”)
Regarding claim 5, Abiprojo and Kamamann teach all the claimed features of claim 1. Abiprojo further teaches:
wherein the processing circuitry acquires operational environment information indicating an operational environment of the device at a time point when a reference value corresponding to each of the plurality of normalized reference values is acquired from the device, acquires operational environment information indicating an operational environment of the device at a time point when each of the plurality of diagnosis values is acquired from the device, and diagnoses the operational status of the device during the diagnosis period, a normalized diagnosis value and a normalized reference value each of whose operational environment information indicates a common operational environment. (Abiprojo: [0045] “The air handler monitor and condensing monitor modules monitor operating parameters of associated components of the HVAC system. For example, the operating parameters may include power supply current, power supply voltage, operating and ambient temperatures of inside and outside air, refrigerant temperatures at various points in the refrigerant loop, fault signals, control signals, and humidity of inside and outside air.”) (Abiprojo: [0062] “The monitoring service may allow the customer and/or contractor to remotely monitor and/or control HVAC components, such as setting temperature, enabling or disabling heating and/or cooling, etc. In addition, the customer may be able to track energy usage, cycling times of the HVAC system, and/or historical data. Efficiency and/or operating costs of the customer's HVAC system may be compared against HVAC systems of neighbors, whose buildings will be subject to the same or similar environmental conditions. This allows for direct comparison of HVAC system and overall building efficiency because environmental variables, such as temperature and wind, are controlled.”)
Regarding independent claim 8:
The claim recites similar limitations as corresponding claim 1 and is rejected using the same teachings and rationale.
It is noted that any citations to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the reference should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. See MPEP 2123.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
FUJIKAWA et al. (JP 2019028834 A) describes providing an outlier diagnosis device capable of easily and efficiently selecting a system to be inspected without setting an individual threshold value for equipment composed of a plurality of systems. A data extraction unit acquires information on a normal period of a system, extracts data on the normal period of the system as normal period data from a database, and data on the system during a diagnosis period, which is a period to be diagnosed. Is extracted from the database as diagnostic period data. The index calculation unit calculates performance indexes for the normal period and the diagnosis period for each system based on the normal period data and the diagnosis period data, respectively. The deterioration degree calculation unit calculates the degree of deterioration indicating the degree of deterioration of the performance index in the diagnosis period with respect to the normal period for each system. The inspection determination unit determines the system to be inspected among all the systems based on the calculated deterioration degree and a predetermined threshold value.
VITULLO (US 2019/0302709 A1) describes a building system including one or more memory devices configured to store instructions that, when executed on one or more processors, cause the one or more processors to determine an average of a minimum half of sorted energy consumption values for a first time period and determine an average of a maximum half of sorted energy consumption values for a second time period. The instructions also cause the processor to determine a ratio of the average of the minimum half of sorted energy consumption values for the first time period to the average of the maximum half of sorted energy consumption values for the second time period, compare the calculated ratio to an adaptively tunable threshold value and activate a system responsive to the calculated ratio exceeding the adaptively tunable threshold value.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL W CHOI whose telephone number is (571)270-5069. The examiner can normally be reached Monday-Friday 8am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kenneth Lo can be reached at (571) 272-9774. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL W CHOI/Primary Examiner, Art Unit 2116
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