DETAILED ACTION
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 .
Information Disclosure Statement
The information disclosure statements submitted on 3/11/2024 and 11/11/2025 were in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Claim Objections
Claim 2 is objected to because of the following informalities:
In claim 2 line 7, “configured output a signal” should read “configured to output a signal.”
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—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.
Claim 20 is rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
In claim 20 lines 3-4, “while in the learning mode” renders claim 20 indefinite due to lack of antecedent basis for “learning mode.” Claim 19 recites a “learning mode” and also recites steps consistent with the further recitation of “outputs the first message comprising the operating signature” in claim 20, such that it is unclear whether the “the learning mode” in claim 20 should be understood as “a learning mode” or whether claim 20 should depend from claim 19. For purposes of examination, “while in the learning mode” in claim 20 is interpreted as “while in a learning mode.”
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 in each of these claims is directed to the abstract idea judicial exception without significantly more.
Claim 1, substantially representative also of independent claims 10 and 16, recites:
“[a] system configured to monitor electrically powered equipment, the system comprising:
a gateway comprising first processing circuitry and communication circuitry; and
a performance monitoring device comprising:
a sensor configured to:
measure electrical power consumed by the electrically powered equipment; and
output a signal indicative of the electrical power consumed by the electrically powered equipment;
a memory comprising computer readable storage media;
second processing circuitry operatively coupled to the sensor and the memory; the second processing circuitry configured to:
receive the signal;
determine, from the signal, an indication of an operating signature for the electrically powered equipment, wherein the operating signature comprises a plurality of characteristic points;
compare respective characteristic points of the plurality of characteristic points to respective thresholds for each characteristic point stored in the memory;
in response to each characteristic point in the operating signature satisfying each respective threshold for the respective characteristic point, determine whether to output a message to the gateway; and
in response to the determination that no message is warranted, refrain from outputting a message.”
The claim limitations considered to fall within in the abstract idea are highlighted in bold font above and the remaining features are “additional elements.”
Step 1 of the subject matter eligibility analysis entails determining whether the claimed subject matter falls within one of the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: process, machine, manufacture, or composition of matter. Claim 1 recites a system, claim 10 recites a method, and claim 16 recites a device and therefore each falls within a statutory category.
Step 2A, Prong One of the analysis entails determining whether the claim recites a judicial exception such as an abstract idea. Under a broadest reasonable interpretation, the highlighted portions of claim 1 fall within the abstract idea judicial exception. Specifically, under the 2019 Revised Patent Subject Matter Eligibility Guidance, the highlighted subject matter falls within the mental processes category (including an observation, evaluation, judgment, opinion). MPEP § 2106.04(a)(2).
The recited functions:
“monitor electrically powered equipment,”
“determine, from the signal, an indication of an operating signature for the electrically powered equipment, wherein the operating signature comprises a plurality of characteristic points;
compare respective characteristic points of the plurality of characteristic points to respective thresholds for each characteristic point”
“in response to each characteristic point in the operating signature satisfying each respective threshold for the respective characteristic point, determine whether to output a message to the gateway; and
in response to the determination that no message is warranted, refrain from outputting a message,”
may be performed as mental processes.
Monitoring electrically powered equipment may be performed via mental processes (e.g., evaluation of collected data regarding operation of the equipment). Determining, from a sensor-originated signal, an indication of an operating signature for the electrically powered equipment, wherein the operating signature includes multiple characteristic points may be performed via mental processes (e.g., evaluation of information derived from the signal, such as may be displayed, and judgment in ascertaining a characteristics (e.g., over a time and/or electrical metric range) of the equipment operating condition that is or corresponds to the information derived from the signal). Comparing multiple characteristic points to respective thresholds stored in the memory may be performed via mental processes (e.g., comparative evaluation, possible aided by pen-and-paper, of the determined operational characteristics with pre-determined reference threshold values). Determining whether to output a message to the gateway in response to each characteristic point in the operating signature satisfying each respective threshold for the respective characteristic point may be performed via mental processes (e.g., judgment applied to the comparing step). Refraining (a broadest interpretation entailing a decision) from outputting a message in response to the determination that no message is warranted may also be performed via mental processes (e.g., judgment).”
Step 2A, Prong Two of the analysis entails determining whether the claim includes additional elements that integrate the recited judicial exception into a practical application. “A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception” (MPEP § 2106.04(d)).
MPEP § 2106.04(d) sets forth considerations to be applied in Step 2A, Prong Two for determining whether or not a claim integrates a judicial exception into a practical application. Based on the individual and collective limitations of claim 13 and applying a broadest reasonable interpretation, the most applicable of such considerations appear to include: improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)); applying the judicial exception with, or by use of, a particular machine (MPEP 2106.05(b)); and effecting a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)).
Regarding improvements to the functioning of a computer or other technology, none of the “additional elements” including “a gateway comprising first processing circuitry and communication circuitry,” “a performance monitoring device” comprising “a sensor configured to: measure electrical power consumed by the electrically powered equipment; and output a signal indicative of the electrical power consumed by the electrically powered equipment,” “a memory comprising computer readable storage media,” and “second processing circuitry operatively coupled to the sensor and the memory; the second processing circuitry configured to” “receive the signal,” and “memory” that stores characteristic points in any combination appear to integrate the abstract idea in a manner that technologically improves any aspect of a device or system that may be used to implement the highlighted steps or a device for implementing the highlighted steps such as a signal processing device or a generic computer.
Implementing the system to include a gateway comprising processing circuitry and communication circuitry and a performance monitoring device that also includes processing circuitry and memory represents a portion of an ordinary networked/distributed computer processing environment for collecting/providing/processing data in a manner having no particularized functional relation to the steps falling within the judicial exception and therefore constitute insignificant extra solution activity that fails to integrate the judicial exception into a practical application or result in the claim as a whole amounting to significantly more than the judicial exception. Configuring the performance monitoring device to include a sensor that measures consumed electrical power and outputs a corresponding output signal that is received by the processing circuitry of the performance monitoring device represents relatively high-level data collection using ordinary sensing/processing means and having no particularized functional relation to the steps falling within the judicial exception and therefore also constitutes insignificant extra solution activity.
Regarding application of the judicial exception with, or by use of, a particular machine, the additional elements, individually and in combination, are not configured or otherwise implemented a particularized manner of electrical equipment power consumption monitoring.
Regarding a transformation or reduction of a particular article to a different state or thing, claim 1 does not include any such transformation or reduction. Instead, claim 1 as a whole entails collecting/receiving input information (e.g., sensor measurement of power consumption), applying standard processing techniques (e.g., processing via processing circuitry) to the information to determine power consumption information (operating signature having characteristic points compared with threshold values) to further determine whether to output a corresponding message with the additional elements failing to provide a meaningful integration of the abstract idea (determining operating signature, comparing with threshold, and deciding whether to output a message) in an application that transforms an article to a different state. Instead, the additional elements represent extra-solution activity that does not integrate the judicial exception into a practical application. In view of the various considerations encompassed by the Step 2A, Prong Two analysis, claim 1 does not include additional elements that integrate the recited abstract idea into a practical application.
Therefore, claim 1 is directed to a judicial exception and requires further analysis under Step 2B.
Regarding Step 2B, and as explained in the Step 2A Prong Two analysis, the additional elements in claim 1 appears to be generic and well understood as evidenced by the disclosures of Bell (US 2012/0323510 A1) and Davies (US 2021/0288450 A1), each of which teach substantially similar networked processing environments in which sensors are used to obtain equipment power consumption data for processing.
As explained in the grounds for rejecting claim 1 under 103, Bell teaches ““a gateway comprising first processing circuitry and communication circuitry,” “a performance monitoring device” comprising “a sensor configured to: measure electrical power consumed by the electrically powered equipment; and output a signal indicative of the electrical power consumed by the electrically powered equipment,” “a memory comprising computer readable storage media,” and “second processing circuitry operatively coupled to the sensor and the memory; the second processing circuitry configured to” “receive the signal,” and “memory” that stores characteristic points.” Similarly, Davies discloses a monitoring device including a power consumption sensor and processing circuitry for processing signals/data from the sensor (FIG. 1 power plug including sensors 4 and microcontrollers/peripherals 9) in which the overall device is coupled to a gateway for external communication of messages (FIG. 1 comms devices 10 configured to connection to networked entities (not depicted); [0064]).
Therefore, the additional elements, individually and in combination with the other claim elements, do not result in the claim as a whole amounting to significantly more than the judicial exception.
Claim 1 is therefore not patent eligible under 101.
Independent claims 10 and 16 include substantially similar elements that fall within the abstract idea judicial exception as claim 1 and includes no further significant additional elements that integrate the judicial exception into a practical application or result in the claim as a whole amounting to significantly more than the judicial exception.
Therefore, claims 10 and 16 are also not patent eligible under 101.
Claims 2-9 depending from claim 1, claims 11-15 depending from claim 10, and claims 17-20 depending from claim 16 provide additional features/steps which are part of an expanded algorithm that includes the abstract idea of the respective independent claims (Step 2A, Prong One). None of dependent claims 2-9, 11-15, and 17-20 recite additional elements that integrate the abstract idea into practical application (Step 2A, Prong Two), and all fail the “significantly more” test under the step 2B for substantially similar reasons as discussed with regards to the independent claims.
For example, claim 2, substantially representative also of claims 11 and 17, further recites “in response to determining that a respective characteristic point in the operating signature is outside a respective threshold for the respective characteristic point,” as the causal action for implementing the outputting of an electronic message and which may be performed via mental processes (evaluation of characteristic point with respect to threshold) and therefore falls within the mental processes exception. The consequent action “output an electronic message that includes an indication of abnormal behavior for the electrically powered equipment” represents ordinary computer processing (outputting result data) having no particularized combined functional relation to the steps falling within the judicial exception and therefore constitutes insignificant extra solution activity. Claim 2 further recites “wherein the gateway is configured to receive the indication of abnormal behavior and the first processing circuity is configured output a signal that notifies a user of the electrically powered equipment of the abnormal behavior” which represents ordinary data processing (interfacing in a distributed/networked computing environment) function having no significant combined functional relation with other elements that conveys an improvement in technology and therefore also constitutes extra solution activity.
Claim 3, substantially representative also of claim 12, further recites that determining whether to output a message (mental process) further includes “to check whether an interval has expired” and “in response to the interval expiring” as the causal action for implementing the outputting of a “status normal” message, each of which may be performed via mental processes (evaluation and judgment) such that they fall within the mental processes exception. The consequent action “output a "status normal" message to the gateway” (to a server in claim 12) represents ordinary computer processing (outputting result data to network processing entities) having no particularized combinatorial functional relation to the steps falling within the judicial exception and therefore constitutes insignificant extra solution activity.
Claims 4-5, 13-14, and 18, further characterize the nature of the characteristic point of the operating signature (data processed by functions falling within judicial exception), in terms of magnitude variation and time range (claims 4, 13, and 18) and alternatively in terms of occurring at a transition point (claims 5 and 14). Such characterizations do not convey any particularized sensing technique because sensing power consumption levels in an ordinary manner over a time/cycle operating period of electrical equipment will at least incidentally include such variations in levels, such that no particularized sensing/collection techniques are conveyed that would otherwise potentially have a particularized combined functional relation with the other claim elements that reflect any improvement in technology. Claims 4-5, 13-14, and 18 therefore primarily present a characterization of the data that is processed by the steps falling within the judicial exception and therefore do not appear to include any significant additional elements.
Claim 6, substantially representative also of claims 15 and 19, recites the additional element that the performance monitoring device operates in a learning mode for a first time period and in a operational mode in a second time period, which represents ordinary computer processing function (shifting in time between processing tasks) having no significant combined functional relation with other elements that conveys an improvement in technology and therefore constitutes insignificant extra solution activity. Claim 6 further recites that the learning mode includes analyzing the received indication of the operating signature for the electrically powered equipment, which may be performed via mental processes (evaluation) and therefore falls within the mental processes exception. Claim 6 further recites the additional element of outputting a message including the operating signature to the gateway (to a server in claim 15), which represents ordinary computer processing (outputting result data to network processing entities) having no particularized combined functional relation to the steps falling within the judicial exception and therefore constitutes insignificant extra solution activity.
Claims 7 and 8 recite additional elements relating to the second processing circuitry receiving data (characteristic point thresholds for claim 7 and equipment identification in claim 8) from the gateway following the second processing circuitry having output the operating signature message to the gateway. These elements, individually and in combination with the other claim elements, represent ordinary computer processing (transmitting/receiving respective data to achieve distributed processing in a networked environment) having no particularized combined functional relation to the steps falling within the judicial exception and therefore constitute insignificant extra solution activity.
Claim 9 further recites the additional element “wherein the gateway is configured to receive a representative operating signature for the electrically powered equipment from a server,” which represents ordinary computer processing (transmitting/receiving respective data to achieve distributed processing in a networked environment) having no particularized combined functional relation to the steps falling within the judicial exception and therefore constitutes insignificant extra solution activity. Claim 9 further characterizes the nature of the representative operating signature that is processed by the functions falling within the judicial exception and therefore also falls within the judicial exception.
Claim 20 includes substantially the same elements as in claims 7, 8, and 9 and therefore also does not include additional elements that in combination with the other elements in the claim integrate the judicial exception into a practical application or result in the claim as a whole amounting to significantly more than the judicial exception.
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 1-2, 4-5, 10-11, 13-14, and 16-18 are rejected under 35 U.S.C. 103 as being unpatentable over Bell (US 2012/0323510 A1) in view of Davies (US 2021/0288450 A1).
As to claim 1, Bell teaches “[a] system configured to monitor electrically powered equipment (Abstract; FIG. 1 system 100 configured to monitor electrical loads 115), the system comprising:
a gateway (FIG. 1 network 130 in combination with communication interface 141) comprising first processing circuitry ([0033] network/communication interface may include “network card” (inherently circuitry for processing (e.g., translating) communications related data)) and communication circuitry (FIG. 1 network 130 (inherently includes communications circuitry) and communication interface 141; [0033]); and
a performance monitoring device (FIG. 1 power meter 105) comprising:
a sensor (FIG. 1 sensor 143) configured to:
measure electrical power consumed by the electrically powered equipment (FIG. 1 sensor 143 coupled with power line 110 and configured to monitor electrical loads 115; FIG. 2 block 205, [0042] sensor 143 measures power consumption by electrical loads); and
output a signal (FIG. 1 sensor 143 configured to provide sensed data to processor 141; FIG. 2 block 210, [0043] describing post-sensor processing in which sensor obtained measurement are processed (requires outputting by the sensor of a signal indicative of electrical power consumption)) indicative of the electrical power consumed by the electrically powered equipment ([0021] sensor data includes current, voltage, power factor);
a memory comprising computer readable storage media (FIG. 1 memory 142 in which programs such as cognitive module 148 are stored);
second processing circuitry operatively coupled to the sensor and the memory (FIG. 1 processor 141 operatively coupled to sensor 143 and memory 142); the second processing circuitry configured to:
receive the signal (FIG. 1 sensor 143 configured to provide sensed data to processor 141; FIG. 2 block 210, [0043] describing post-sensor processing in which sensor obtained measurement are processed (requires receipt of the signal indicative of electrical power consumption));
determine, from the signal, an indication of an operating signature for the electrically powered equipment ([0011], [0015], [0020], and [0023] monitored signals processed into power consumption data to derive individual and combined load signatures), wherein the operating signature comprises a plurality of characteristic points ([0024] and [0043] signatures reflect time varying patterns (more than one point));
compare respective characteristic points ([0046] power consumption (signature) data may include power consumption itself or operating time of the signature) of the plurality of characteristic points to respective thresholds for each characteristic point ([0012] determination of whether load is operating within one or more desired parameters; FIG. 2 blocks 225 and 230, [0045]-[0046] compare determined power consumption to expected power consumption signature to detect anomaly (the points in the expected signature constitute thresholds and/or as described in [0046] thresholds may be applied in terms of differences generally in relation to the comparison)) stored in the memory (storage of threshold values (e.g., expected signatures) in some form of memory is required for the comparison processing; [0018] data files 145 may store expected power consumption data);
in response to each characteristic point in the operating signature satisfying each respective threshold for the respective characteristic point (FIG. 2 block 235, [0047] determine no abnormal behavior per the threshold comparison at block 230), determine whether to output a message to the gateway (FIG. 2 sequence of block 235 to blocks 215, 220, 250, and 255 including interim determination at block 220 for ultimately determining to provide GUIs and/or reports to recipients that per [0049] may be the user devices and/or central system accessible per FIG. 1 via gateway (network 130 and communication interface 144)).”
Bell does not explicitly teach “in response to the determination that no message is warranted, refrain from outputting a message.” Davies discloses a system/method for monitoring power consumption by electrical equipment (Abstract) that includes conditionally rather than automatically sending output messages relating to the outcome of a comparison between a measured power consumption and a corresponding benchmark (FIG. 4 blocks S6 and S7, transmit information if (conditioned on) fault (threshold condition) detection).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Davies teaching of selective/conditional outputting of information relating to the outcome of a comparison between a measured power consumption and a corresponding benchmark to the system taught by Bell, which teaches generalized conditioning of whether/when to send output messages such that in combination the system is configured to refrain from outputting a message in response to the determination that no message is warranted.
The motivation would have been the facially evident advantage of sending no output message when none is warranted to avoid unnecessary expenditure of processing/networking resources.
As to claim 2, the combination of Bell and Davies teaches “[t]he system of claim 1,
wherein the second processing circuitry is further configured to, in response to determining that a respective characteristic point in the operating signature is outside a respective threshold for the respective characteristic point, output an electronic message that includes an indication of abnormal behavior for the electrically powered equipment (Bell: [0012] and [0028] in response to determining that a load is not operating within one or more desired parameters take control action such as generating an communicating alert message to user device; FIG. 2 blocks 230, 235 and 245, [0046]-[0048]), and
wherein the gateway is configured to receive the indication of abnormal behavior and the first processing circuity is configured output a signal that notifies a user of the electrically powered equipment of the abnormal behavior (Bell: [0028] control actions may include alert message to user device 120 that per FIG. 1 is connected to power meter 105 via communication interface 144 and network 130 (gateway)).”
As to claim 4, the combination of Bell and Davies teaches “[t]he system of claim 1, wherein a respective characteristic point of the operating signature comprises a sampled data point (Bell: FIG. 1 sensor 143 configured to measure/sample; FIG. 2 block 205 monitor power consumption) in which:
a magnitude of measured power by the sensor varies within a threshold range (Bell: [0010] and [0021] power consumption variable (variations) include current (level/magnitude); [0016] power consumption measurement includes amount of electrical power; [0011]-[0012] determination of whether load is operating within one or more desired parameters/thresholds (effectively describing variation of measured power consumption with respect to threshold such that the measured variable/variation effectively constitutes a threshold range); and
the sampled data point occurs within a threshold range of time in the operating signature (Bell: [0011]-[0012] determination of whether load is operating within one or more desired parameters/thresholds (effectively describing variation of measured power consumption with respect to threshold such that the measured variable/variation effectively constitutes a threshold range; [0023] instantaneous values derived from measurements collected over time; [0028] threshold parameter may be operating time).”
As to claim 5, the combination of Bell and Davies teaches “[t]he system of claim 1, wherein a characteristic point of the operating signature comprises a sampled data point that occurs at a transition point within the operating signature (Bell: [0023]-[0024] signature identification includes detecting transient patterns).”
As to claim 10, Bell teaches “[a] method (Abstract; method implemented by FIG. 1 system 100 configured to monitor electrical loads 115) comprising:
receiving, by processing circuitry of a performance monitoring device (FIG. 1 power meter 105 including processor 141 operatively coupled to sensor 143 and memory 142), an indication of an operating signature for electrically powered equipment from a sensor (FIG. 1 sensor 143 configured to provide sensed data to processor 141; FIG. 2 block 210, [0043] describing post-sensor processing in which sensor obtained measurement are processed (requires outputting by the sensor of a signal indicative of electrical power consumption); FIG. 2 block 210, [0043] describing post-sensor processing in which sensor obtained measurement are processed (requires receipt of the signal indicative of electrical power consumption)),
wherein sensor is configured to measure electrical power consumed by the electrically powered equipment (FIG. 1 sensor 143 coupled with power line 110 and configured to monitor electrical loads 115; FIG. 2 block 205, [0042] sensor 143 measures power consumption by electrical loads), and
wherein the operating signature comprises a plurality of characteristic points ([0024] and [0043] signatures reflect time varying patterns (more than one point));
comparing, by the processing circuitry, respective characteristic points ([0046] power consumption (signature) data may include power consumption itself or operating time of the signature) of the plurality of characteristic points to respective thresholds for each characteristic point ([0012] determination of whether load is operating within one or more desired parameters; FIG. 2 blocks 225 and 230, [0045]-[0046] compare determined power consumption to expected power consumption signature to detect anomaly (the points in the expected signature constitute thresholds and/or as described in [0046] thresholds may be applied in terms of differences generally in relation to the comparison));
in response to each characteristic point in the operating signature satisfying each respective threshold for the respective characteristic point (FIG. 2 block 235, [0047] determine no abnormal behavior per the threshold comparison at block 230), determining whether to output a message (FIG. 2 sequence of block 235 to blocks 220, 250, and 255 depicting interim determination at block 220 for ultimately determining to provide GUIs and/or reports to recipients that per [0049] may be the user devices and/or central system accessible per FIG. 1 via gateway (network 130 and communication interface 144)).”
Bell does not explicitly teach “in response to the determination that no message is warranted, refrain from outputting a message.” Davies discloses a system/method for monitoring power consumption by electrical equipment (Abstract) that includes conditionally rather than automatically sending output messages relating to the outcome of a comparison between a measured power consumption and a corresponding benchmark (FIG. 4 blocks S6 and S7, transmit information if (conditioned on) fault (threshold condition) detection).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Davies teaching of selective/conditional outputting of information relating to the outcome of a comparison between a measured power consumption and a corresponding benchmark to the system taught by Bell, which teaches generalized conditioning of whether/when to send output messages such that in combination the system is configured to refrain from outputting a message in response to the determination that no message is warranted.
The motivation would have been the facially evident advantage of sending no output message when none is warranted to avoid unnecessary expenditure of processing/networking resources.
As to claim 11, the combination of Bell and Davies teaches “[t]he method of claim 10, further comprising in response to determining that a respective characteristic point in the operating signature is outside a respective threshold for the respective characteristic point, outputting, by the processing circuitry, an electronic message indicating abnormal behavior for the electrically powered equipment (Bell: [0012] and [0028] in response to determining that a load is not operating within one or more desired parameters take control action such as generating an communicating alert message to user device; FIG. 2 blocks 230, 235 and 245, [0046]-[0048]), wherein the electronic message causes a notification to a user of the electrically powered equipment of the abnormal behavior (Bell: [0028] control actions may include alert message to user device 120 that per FIG. 1 is connected to power meter 105 via communication interface 144 and network 130).”
As to claim 13, the combination of Bell and Davies teaches “[t]he method of claim 10, wherein a respective characteristic point of the operating signature comprises a sampled data point (Bell: FIG. 1 sensor 143 configured to measure/sample; FIG. 2 block 205 monitor power consumption) in which:
a magnitude of measured power by the sensor varies within a threshold range (Bell: [0010] and [0021] power consumption variable (variations) include current (level/magnitude); [0016] power consumption measurement includes amount of electrical power; [0011]-[0012] determination of whether load is operating within one or more desired parameters/thresholds (effectively describing variation of measured power consumption with respect to threshold such that the measured variable/variation effectively constitutes a threshold range); and
the sampled data point occurs within a threshold range of time in the operating signature (Bell: [0011]-[0012] determination of whether load is operating within one or more desired parameters/thresholds (effectively describing variation of measured power consumption with respect to threshold such that the measured variable/variation effectively constitutes a threshold range; [0023] instantaneous values derived from measurements collected over time; [0028] threshold parameter may be operating time).”
As to claim 14, the combination of Bell and Davies teaches “[t]he method of claim 10, wherein a respective characteristic point of the operating signature comprises a sampled data point that occurs at a transition point within the operating signature (Bell: [0023]-[0024] signature identification includes detecting transient patterns).”
As to claim 16, Bell teaches “[a] device (Abstract; FIG. 1 system 100 configured to monitor electrical loads 115) comprising:
a memory comprising computer readable storage media FIG. 1 memory 142 in which programs such as cognitive module 148 are stored); and
processing circuitry operatively coupled to the memory (FIG. 1 processor 141 operatively coupled to sensor 143 and memory 142); the processing circuitry configured to:
receive a signal from sensing circuitry (FIG. 1 sensor 143 configured to provide sensed data to processor 141; FIG. 2 block 210, [0043] describing post-sensor processing in which sensor obtained measurement are processed (requires receipt of the signal indicative of electrical power consumption)), the sensing circuitry configured to:
measure electrical power consumed by electrically powered equipment (FIG. 1 sensor 143 coupled with power line 110 and configured to monitor electrical loads 115; FIG. 2 block 205, [0042] sensor 143 measures power consumption by electrical loads) and
output the signal that includes an indication of an operating signature for the electrically powered equipment (FIG. 1 sensor 143 configured to provide sensed data to processor 141; FIG. 2 block 210, [0043] describing post-sensor processing in which sensor obtained measurement are processed (requires outputting by the sensor of a signal indicative of electrical power consumption)), wherein the operating signature comprises a plurality of characteristic points ([0024] and [0043] signatures reflect time varying patterns (more than one point));
compare respective characteristic points ([0046] power consumption (signature) data may include power consumption itself or operating time of the signature) of the plurality of characteristic points to respective thresholds for each characteristic point ([0012] determination of whether load is operating within one or more desired parameters; FIG. 2 blocks 225 and 230, [0045]-[0046] compare determined power consumption to expected power consumption signature to detect anomaly (the points in the expected signature constitute thresholds and/or as described in [0046] thresholds may be applied in terms of differences generally in relation to the comparison)) stored at the memory (storage of threshold values (e.g., expected signatures) in some form of memory is required for the comparison processing; [0018] data files 145 may store expected power consumption data);
in response to each characteristic point in the operating signature satisfying each respective threshold for the respective characteristic point (FIG. 2 block 235, [0047] determine no abnormal behavior per the threshold comparison at block 230), determine whether to output a message (FIG. 2 sequence of block 235 to blocks 220, 250, and 255 depicting interim determination at block 220 for ultimately determining to provide GUIs and/or reports to recipients that per [0049] may be the user devices and/or central system).”
Bell does not explicitly teach “in response to the determination that no message is warranted, refrain from outputting a message.” Davies discloses a system/method for monitoring power consumption by electrical equipment (Abstract) that includes conditionally rather than automatically sending output messages relating to the outcome of a comparison between a measured power consumption and a corresponding benchmark (FIG. 4 blocks S6 and S7, transmit information if (conditioned on) fault (threshold condition) detection).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Davies teaching of selective/conditional outputting of information relating to the outcome of a comparison between a measured power consumption and a corresponding benchmark to the device taught by Bell, which teaches generalized conditioning of whether/when to send output messages such that in combination the device is configured to refrain from outputting a message in response to the determination that no message is warranted.
The motivation would have been the facially evident advantage of sending no output message when none is warranted to avoid unnecessary expenditure of processing/networking resources.
As to claim 17, the combination of Bell and Davies teaches “[t]he device of claim 16,
wherein the processing circuitry is further configured to, in response to determining that a respective characteristic point in the operating signature is outside a respective threshold for the respective characteristic point, output an electronic message that includes an indication of abnormal behavior for the electrically powered equipment (Bell: [0012] and [0028] in response to determining that a load is not operating within one or more desired parameters take control action such as generating an communicating alert message to user device; FIG. 2 blocks 230, 235 and 245, [0046]-[0048]), and
wherein the electronic message causes a notification to a user of the powered equipment of the abnormal behavior (Bell: [0028] control actions may include alert message to user device 120 that per FIG. 1 is connected to power meter 105 via communication interface 144 and network 130).”
As to claim 18, the combination of Bell and Davies teaches “[t]he device of claim 16, wherein a respective characteristic point of the operating signature comprises a sampled data point (Bell: FIG. 1 sensor 143 configured to measure/sample; FIG. 2 block 205 monitor power consumption) in which:
a magnitude of power measured by the sensing circuitry varies within a threshold range (Bell: [0010] and [0021] power consumption variable (variations) include current (level/magnitude); [0016] power consumption measurement includes amount of electrical power; [0011]-[0012] determination of whether load is operating within one or more desired parameters/thresholds (effectively describing variation of measured power consumption with respect to threshold such that the measured variable/variation effectively constitutes a threshold range); and
the sampled data point occurs within a threshold range of time in the operating signature (Bell: [0011]-[0012] determination of whether load is operating within one or more desired parameters/thresholds (effectively describing variation of measured power consumption with respect to threshold such that the measured variable/variation effectively constitutes a threshold range; [0023] instantaneous values derived from measurements collected over time; [0028] threshold parameter may be operating time).”
Claims 3 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Bell and Davies as applied to claims 1 and 10 above, and further in view of Hosek (US 2007/0067678 A1) and Coady (GB2578332A).
As to claim 3, the combination of Bell and Davies teaches “[t]he system of claim 1,” but neither Bell nor Davies appears to expressly teach “wherein to determine whether to output a message comprises the second processing circuitry:
to check whether an interval has expired; and
in response to the interval expiring, output a "status normal" message to the gateway.”
Sending periodic (regularized time interval) health status messages from an electric equipment monitoring unit to remote processing unit(s) was known in the art prior to the effective filing date. For example, Hosek discloses a system/method for monitoring and diagnosing faults of electric equipment (Abstract; [0054]) that is configured to periodically send health monitoring data to remote functions ([0488] information transmitted may be periodic health monitoring data as well as on-demand information. Examiner notes that “periodic” transmission in contrast to condition-based (e.g., on-demand) inherently entails being performed at timed intervals/expiration times).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Hosek’s teaching of sending periodic (i.e., based on expiration of a regularized time interval) health status messages to a remote processing function to the system taught by Bell as modified by Davies such that in combination the system is further configured such that determining whether to output a message comprises in response to the characteristic points satisfying respective thresholds includes the second processing circuitry checking whether an interval has expired and in response to the interval expiring, outputting a” [health status] “message to the gateway.”
The motivation would have been to provide regularized health status updates to remote processing entities to enhance comprehensive equipment monitoring as suggested by Hosek.
While inferred by the broad characterization of “health” data, Hosek does not appear to explicitly teach sending “normal” status messages.
Coady discloses a system/method for determining appliance condition (Abstract) in which the determined state of operation is affirmatively determined as being a normal or abnormal state (Abstract; page 2 lines 3-5 state identified as either normal or abnormal).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Coady’s teaching of determining distinct “normal” state as a monitored state of the equipment to the system taught by Bell as modified by Davies and Hosek, which teaches sending periodic health data to a remote processing function, such that in combination the system is configured for periodically outputting a “status normal” message to the gateway as part of the determination taught by Bell of determining whether to output a message in response to characteristic points satisfying respective thresholds (indicating relatively normal operation).
The motivation would have been to provide regularized updates to remote processing functions that are also involved in monitoring and analysis equipment operation performance to enhance monitoring tracking by verifying normal operations on a continuous basis.
As to claim 12, the combination of Bell and Davies teaches “[t]he method of claim 10,” and Bell further teaches that the output messages may be sent to a server ([0049] reports sent to external recipients include central system; [0036]-[0037] central systems 125 may include a server). However, neither Bell nor Davies appears to expressly teach “wherein determining whether to output a message comprises:
checking, by the processing circuitry, whether an interval has expired; and
in response to the interval expiring, outputting, by the processing circuitry, a "status normal" message to a server.”
Sending periodic (regularized time interval) health status messages from an electric equipment monitoring unit to remote processing unit(s) was known in the art prior to the effective filing date. For example, Hosek discloses a system/method for monitoring and diagnosing faults of electric equipment (Abstract; [0054]) that is configured to periodically send health monitoring data to remote functions ([0488] information transmitted may be periodic health monitoring data as well as on-demand information. Examiner notes that “periodic” transmission in contrast to condition-based (e.g., on-demand) inherently entails being performed at timed intervals/expiration times).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Hosek’s teaching of sending periodic (i.e., based on expiration of a regularized time interval) health status messages to a remote processing function to the method taught by Bell as modified by Davies such that in combination the method includes wherein determining whether to output a message comprises checking whether an interval has expired and in response to the interval expiring, outputting a [health status] message to a server.
The motivation would have been to provide regularized health status updates to remote processing entities to enhance comprehensive equipment monitoring as suggested by Hosek.
While inferred by the broad characterization of “health” data, Hosek does not appear to explicitly teach sending “normal” status messages.
Coady discloses a system/method for determining appliance condition (Abstract) in which the determined state of operation is affirmatively determined as being a normal or abnormal state (Abstract; page 2 lines 3-5 state identified as either normal or abnormal).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Coady’s teaching of determining distinct “normal” state as a monitored state of the equipment to the system taught by Bell as modified by Davies and Hosek, which teaches sending periodic health data to a remote processing function, such that in combination the system is configured for periodically outputting a “status normal” message to the server as part of the determination taught by Bell of determining whether to output a message in response to characteristic points satisfying respective thresholds (indicating relatively normal operation).
The motivation would have been to provide regularized updates to remote processing functions that are also involved in monitoring and analysis equipment operation performance to enhance monitoring tracking by verifying normal operations on a continuous basis.
Claims 6-9, 15, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Bell and Davies as applied to claims 1, 10, and 16 above, and further in view of Tsao (US 2012/0004871 A1).
As to claim 6, the combination of Bell and Davies teaches “[t]he system of claim 1,
wherein the performance monitoring device is configured to operate in a learning mode for a first period of time and in an operational mode for a second duration (Bell: [0028] expected power consumption determined (learning) prior to comparing (operational); FIG. 2 blocks 225 and 230, [0045]-[0046]).”
Neither Bell nor Davies appears to teach that a learning mode includes steps of “analyze the received indication of the operating signature for the electrically powered equipment, output the message to the gateway, and wherein the message to the gateway comprises the operating signature.”
Tsao discloses a system/method for using power monitoring to determine states of electrical appliances (Abstract) that includes remote processing functionality (FIG. 2 variation detection and search module and electric appliance signature database 220; FIG. 6 depicting remote implementation of search module and electric appliance signature database 630) for implementing a learning mode (Abstract describing a process for determining via searching for (learning) reference appliance signatures; FIG. 4 blocks S440 and S450, [0053] and [0056]) that includes analyzing the measured power consumption data (signature) including threshold comparison analysis ([0041] in response to variations in power consumption feature (power consumption data received from a power monitoring device) that exceed a threshold search electric appliance signature database; FIG. 4 block S440, [0054]) and in response to the analysis, implementing the searching using the power consumption data (variation in the power consumption data received from power monitoring device) to find, within a signature database, appliance signatures similar to the power consumption data ([0041] variation detection and search module searches the signature database according to the variation of the power consumption feature to obtain/find similar appliance signatures) in which the module for implementing the comparative threshold analysis and the signature database may be remotely accessible (FIG. 6 search module and electric appliance signature database 630 communicatively coupled with power monitoring device 60 via network 620, [0064]).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Tsao’s teaching of implementing a reference signature discovery/learning mode in which measured power consumption data (signature) is analyzed and further applied in a comparative reference signature database search that is performed within a remote/networked processing structure (requiring receiving the measured power consumption feature data for the comparative search and therefore requiring the measured power consumption data to be transmitted to the remote search function) to the system taught by Bell as modified by Davies in which power consumption processing may be shared in a networked manner via a gateway (Bell: [0036] central systems 125 configured to receive and processing power consumption data) and in which reference/expected signatures may be received from external sources (via gateway access) (Bell: [0027]), such that in combination the system is configured such that in a learning mode, the second processing circuitry is configured to: analyze the received indication of the operating signature for the electrically powered equipment, output the message (measured power consumption signature data) to the gateway, and wherein the message to the gateway comprises the operating signature.
The motivation would have been to use the measured power consumption signature data to find a corresponding reference signature for optimal signature comparison in a manner that leverages networked/distributed processing/storage resources to enhance processing and storage efficiency.
As to claim 7, the combination of Bell, Davies, and Tsao teaches “[t]he system of claim 6, wherein, while in the learning mode” “the second processing circuitry is configured to receive the respective thresholds for each characteristic point via the gateway (Bell: [0027] expected/normal power consumption data received from external source to be stored in memory; FIG. 1 network 130 in combination with communication interface 141 forming gateway for external communications).
As combined with the teachings of Tsao for claim 6, in which in which the system is configured to send an output message including the measured power consumption signature for the purpose of determining corresponding reference signatures, the method including Bell’s teaching of using the reference/expected signature for a subsequent comparison performed by the second/local circuitry would include receiving the determined corresponding reference signature (thresholds) “after the second processing circuitry outputs the message comprising the operating signature.”
As to claim 8, the combination of Bell, Davies, and Tsao teaches “[t]he system of claim 6,” and Bell teaches while in the learning mode the second circuitry receiving the expected power consumption signature from an external source via the gateway in which the power consumption signature is functionally associated with and therefore effectively identifies an appliance (Bell: [0027] and [0045] expected/normal power consumption data for an appliance received from external source such as manufacturer to be stored in memory; FIG. 1 network 130 in combination with communication interface 141 forming gateway for external communications).
As combined with the teachings of Tsao for claim 6, in which in which the system is configured to used gateway communications between a local module and remote processing to send an output message including the measured power consumption signature for the purpose of determining corresponding reference signatures, the method including Bell’s teaching of using the reference/expected signature for a subsequent comparison by the second/local circuitry would include receiving the determined corresponding reference signature (effectively identifying an appliance per Bell and per Tsai (Abstract appliance signature identified in accordance with measured power consumption)) “after the second processing circuitry outputs the message comprising the operating signature.”
As to claim 9, the combination of Bell, Davies, and Tsao teaches “[t]he system of claim 8,
wherein the gateway is configured to receive a representative operating signature for the electrically powered equipment (as combined for claim 8, the combination of Bell, Davies, and Tsao teaches the gateway is configured to receive the reference signature)”
“wherein the representative operating signature is based on the identification of electrically powered equipment (Bell: [0027] and [0045] expected/normal power consumption data for (corresponds to) an appliance received from appliance manufacturer or historical data for the particular load/appliance), and
wherein the representative operating signature includes the respective thresholds for each characteristic point (Bell: [0045] expected power consumption forms a baseline; [0046] measured power consumption information compared to expected power consumption to detect anomaly (expected power consumption defines threshold(s)).”
Bell further teaches that the processing/storage entities connected via gateway to the second circuitry may include a server ([0036]-[0037] central systems 125 assisting with processing functions may include a server).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Bell’s teaching of using a server as a networked (connected via gateway) component in the system connected via gateway to the second circuitry to the system taught by Bell as modified by Davies and Tsao to including receiving reference signatures corresponding to and therefore effectively identifying electrical equipment from a remote source such that in combination the remote source (e.g., Tsao’s remote search module and electric appliance signature database 630 in FIG. 6) is configured to be implemented via a server such that the gateway is configured to receive a representative operating signature for the electrically powered equipment from a server.
Such a combination would amount to selecting a known design option for implementing distributed computer processing and storage to achieve predictable results.
As to claim 15, the combination of Bell and Davies teaches “[t]he method of claim 10, further comprising:
functioning in a learning mode for a first period of time and functioning in an operational mode for a second duration (Bell: [0028] expected power consumption determined (learning) prior to comparing (operational); FIG. 2 blocks 225 and 230, [0045]-[0046]).”
Bell further teaches outputting messages to a server ([0049] reports sent to external recipients include central system; [0036]-[0037] central systems 125 assisting with processing functions may include a server), but neither Bell nor Davies appears to teach that a learning mode includes steps of “analyzing, by the processing circuitry, the received indication of the operating signature for the electrically powered equipment, and outputting the message to a server, wherein the message to the server comprises the operating signature.”
Tsao discloses a system/method for using power monitoring to determine states of electrical appliances (Abstract) that includes remote processing functionality (FIG. 2 variation detection and search module and electric appliance signature database 220; FIG. 6 depicting remote implementation of search module and electric appliance signature database 630) for implementing a learning mode (Abstract describing a process for determining via searching for (learning) reference appliance signatures; FIG. 4 blocks S440 and S450, [0053] and [0056]) that includes analyzing the measured power consumption data (signature) including threshold comparison analysis ([0041] in response to variations in power consumption feature (power consumption data received from a power monitoring device) that exceed a threshold search electric appliance signature database; FIG. 4 block S440, [0054]) and in response to the analysis, implementing the searching using the power consumption data (variation in the power consumption data received from power monitoring device) to find, within a signature database, appliance signatures similar to the power consumption data ([0041] variation detection and search module searches the signature database according to the variation of the power consumption feature to obtain/find similar appliance signatures) in which the module for implementing the comparative threshold analysis and the signature database may be remotely accessible (FIG. 6 search module and electric appliance signature database 630 communicatively coupled with power monitoring device 60 via network 620, [0064]).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Tsao’s teaching of implementing a reference signature discovery/learning mode in which measured power consumption data (signature) is analyzed and further applied in a comparative reference signature database search that is performed within a remote/networked processing structure (requiring receiving the measured power consumption feature data for the comparative search and therefore requiring the measured power consumption data to be transmitted to the remote search function) to the system taught by Bell as modified by Davies in which power consumption processing may be shared with a server in a networked manner via a gateway (Bell: [0036] central systems 125 configured to receive and processing power consumption data; [0036]) and in which reference/expected signatures may be received from external sources (via gateway access) (Bell: [0027]), such that in combination the system is configured such that in a learning mode the method includes analyzing the received indication of the operating signature for the electrically powered equipment, outputting the message (measured power consumption signature data) to a server, and wherein the message to the server comprises the operating signature.
The motivation would have been to use the measured power consumption signature data to find a corresponding reference signature for optimal signature comparison in a manner that leverages networked/distributed processing/storage resources to enhance processing and storage efficiency.
As to claim 19, the combination of Bell and Davies teaches “[t]he device of claim 16,
wherein the processing circuitry is configured to operate in a learning mode for a first period of time and in an operational mode for a second duration (Bell: [0028] expected power consumption determined (learning) prior to comparing (operational); FIG. 2 blocks 225 and 230, [0045]-[0046]).”
Neither Bell nor Davies appears to teach that a learning mode includes steps of “analyze the received indication of the operating signature for the electrically powered equipment, output the message to a computing device external to the device, and wherein the message comprises the operating signature.”
Tsao discloses a system/method for using power monitoring to determine states of electrical appliances (Abstract) that includes remote processing functionality (FIG. 2 variation detection and search module and electric appliance signature database 220; FIG. 6 depicting remote implementation of search module and electric appliance signature database 630) for implementing a learning mode (Abstract describing a process for determining via searching for (learning) reference appliance signatures; FIG. 4 blocks S440 and S450, [0053] and [0056]) that includes analyzing the measured power consumption data (signature) including threshold comparison analysis ([0041] in response to variations in power consumption feature (power consumption data received from a power monitoring device) that exceed a threshold search electric appliance signature database; FIG. 4 block S440, [0054]) and in response to the analysis, implementing the searching using the power consumption data (variation in the power consumption data received from power monitoring device) to find, within a signature database, appliance signatures similar to the power consumption data ([0041] variation detection and search module searches the signature database according to the variation of the power consumption feature to obtain/find similar appliance signatures) in which the module for implementing the comparative threshold analysis and the signature database may be remotely accessible (FIG. 6 search module and electric appliance signature database 630 communicatively coupled with power monitoring device 60 via network 620, [0064]).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Tsao’s teaching of implementing a reference signature discovery/learning mode in which measured power consumption data (signature) is analyzed and further applied in a comparative reference signature database search that is performed within a remote/networked processing structure (requiring receiving the measured power consumption feature data for the comparative search and therefore requiring the measured power consumption data to be transmitted to the remote search function) to the device taught by Bell as modified by Davies in which power consumption processing may be shared in a networked manner via a gateway (Bell: [0036] central systems 125 configured to receive and processing power consumption data) and in which reference/expected signatures may be received from external sources (via gateway access) (Bell: [0027]), such that in combination the device is configured such that in a learning mode, the processing circuitry is configured to analyze the received indication of the operating signature for the electrically powered equipment, and output the message (measured power consumption signature data) to a computing device external to the device, wherein the message comprises the operating signature.
The motivation would have been to use the measured power consumption signature data to find a corresponding reference signature for optimal signature comparison in a manner that leverages networked/distributed processing/storage resources to enhance processing and storage efficiency.
As to claim 20, as best understood and interpreted in view of the grounds for rejecting claim 20 under 112(b), the combination of Bell and Davies teaches “[t]he device of claim 16,
wherein the message is a first message,
wherein, while in the learning mode (Bell: [0028] expected power consumption determined (learning) prior to comparing (operational); FIG. 2 blocks 225 and 230, [0045]-[0046])” “the processing circuitry is configured to receive” “the respective thresholds for each characteristic point (Bell: [0027] expected/normal power consumption data received from external source to be stored in memory; FIG. 1 network 130 in combination with communication interface 141 forming gateway for external communications); and
an identification of the electrically powered equipment (Bell: [0027] and [0045] expected/normal power consumption data for (corresponding to) an appliance received from external source such as manufacturer to be stored in memory).”
Neither Bell nor Davies appears to teach that a learning mode includes steps of “after the processing circuitry outputs the first message comprising the operating signature,” the processing circuitry is configured to receive “a second message from an external server” that includes the thresholds and identification information.
Tsao discloses a system/method for using power monitoring to determine states of electrical appliances (Abstract) that includes remote processing functionality (FIG. 2 variation detection and search module and electric appliance signature database 220; FIG. 6 depicting remote implementation of search module and electric appliance signature database 630) for implementing a learning mode (Abstract describing a process for determining via searching for (learning) reference appliance signatures; FIG. 4 blocks S440 and S450, [0053] and [0056]) that includes analyzing the measured power consumption data (signature) including threshold comparison analysis ([0041] in response to variations in power consumption feature (power consumption data received from a power monitoring device) that exceed a threshold search electric appliance signature database; FIG. 4 block S440, [0054]) and in response to the analysis, implementing the searching using the power consumption data (variation in the power consumption data received from power monitoring device) to find, within a signature database, appliance signatures similar to the power consumption data ([0041] variation detection and search module searches the signature database according to the variation of the power consumption feature to obtain/find similar appliance signatures) in which the module for implementing the comparative threshold analysis and the signature database may be remotely accessible (FIG. 6 search module and electric appliance signature database 630 communicatively coupled with power monitoring device 60 via network 620, [0064]).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Tsao’s teaching of implementing a reference signature discovery/learning mode in which measured power consumption data (signature) is applied in a comparative reference signature database search that is performed within a remote/networked processing structure (requiring receiving the measured power consumption feature data for the comparative search and therefore requiring the measured power consumption data to be transmitted to the remote search function) to the device taught by Bell as modified by Davies in which power consumption processing may be shared in a networked manner via a gateway (Bell: [0036] central systems 125 configured to receive and processing power consumption data) and in which reference/expected signatures may be received from external sources (via gateway access) (Bell: [0027]), such that in combination the system is configured such that the learning mode includes steps of “after the processing circuitry outputs the first message comprising the operating signature,” the processing circuitry is configured to receive “a second message from an external server” that includes the thresholds and identification information.
The motivation would have been to use the measured power consumption signature data to find a corresponding reference signature for optimal signature comparison in a manner that leverages networked/distributed processing/storage resources to enhance processing and storage efficiency.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW W BACA whose telephone number is (571)272-2507. The examiner can normally be reached Monday - Friday 8:00 am - 5:30 pm.
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/MATTHEW W. BACA/Examiner, Art Unit 2857
/ANDREW SCHECHTER/Supervisory Patent Examiner, Art Unit 2857
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