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 .
This Office Action is responsive to the communication received on 11/29/2023. The claims 1-15 are pending, of which the claim(s) 1 is/are in independent form.
Specification
The disclosure is objected to because of the following informalities:
In para. 0117, line 5: “for example, The” should be “for example, the”.
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
In claims 1- 9 & 13- 15:
“state detection unit”: shown as item 1 in Fig. 28, Spec, paras. 0103 – 0104: state detection unit 30 can also be configured as a device such as a personal computer that includes the reception function and various arithmetic processing functions.
In claims 10- 12: Please refer to fig. 28 & associated texts that mention these limitations.
“a learning unit”: shown as item 31c, para. 0112
“a conjecture result output unit”: shown as item 31e, para. 0115
“a signal output unit”: shown as item 32, para. 0118
In claims 5- 6:
“a vibration suppression structure”: Spec, paras. [038, 041-048], figs. 9- 10: This vibration suppression structure is being described as a mechanical structure having a through-hole or a structure which has its lower part larger than the upper part to shift the center of gravity Cg.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 10- 12 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.
I) Claim 10, recites the same element "a characteristic part and chronological data” in line 3- 4 and also line 10 without clarifying relationship of these elements of lines 3- 4 and in line 10 thereby rendering the scope of the claim indefinite.
For the examination purpose, the element “a characteristic part and chronological data” in line 10 is interpreted as “the [[a]] characteristic part and chronological data”.
II) Regarding claims 11- 12, these claims are also rejected because of their dependency with rejected claim.
III) Regarding claims 10- 12, claim elements “a learning unit”, “a conjecture result output unit”, “a signal output unit” invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function.
Examiner acknowledges that these three units elements are shown in fig. 28 and are being described as sub-sections of the state detection unit with is being described as being implemented in a personal computer for example in para. [0103]. Examiner also notes that the paras. 0112, 0115, & 0118 do describe the functions of these elements in additional details. Nevertheless, these paragraphs and elsewhere in applicant’s disclosure, do not describe how (e.g., using software only, hardware only, combination of both of the personal computer or something else) these functional elements are being implemented. The specification fails to clearly link the structure of the computer with the learning unit, conjecture result output unit, and a signal output unit. Examiner does not dispute that these elements are shown as ”black box” entities in applicant’s fig. 28. However, neither the specification nor the drawing clearly link how these elements are being implemented. Therefore, the scope of these claim elements are unclear.
For the examination purpose, these elements are interpreted as combination of software and hardware used in a general purpose computer such as a personal computer and as mapped below in art rejection section.
Therefore, the claims 10- 12 are indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
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.
Claim 1 & 10- 13 rejected under 35 U.S.C. 101 because the claimed invention is directed to Judicial Exception (“abstract idea”) without significantly more.
As to claim 1,
the claim is reproduced below.
1. A facility state monitoring system comprising:
[a] a sensor node including a sensor configured to output, as sensor data, data indicating a state of a facility as a monitoring target to be monitored, a communication unit configured to transmit the sensor data, and a power supply unit configured to supply power to the sensor and the communication unit, the sensor node being commonly used by a plurality of the monitoring targets;
[b] a receiver configured to receive the sensor data transmitted from the communication unit; and
[c] a state detection unit configured to receive the sensor data received by the receiver, to learn, as learning data, normal states of the monitoring targets based on normal sensor data corresponding to normal operations of the monitoring targets, and in response to the receiver receiving the sensor data transmitted from the sensor node after learning, to compare states of the monitoring targets indicated by the sensor data with the learning data, thereby to detect an abnormality occurrence or symptom in the monitoring targets.
1. Step 1: Yes. The claim is to a system with various structural elements, which is one of the four categories of patent eligible subject matter.
2. Step 2A, Prong 1: Yes. The claim(s) recite(s) limitations of
“to learn, as learning data, normal states of the monitoring targets based on normal sensor data corresponding to normal operations of the monitoring targets, and
in response to the receiver receiving the sensor data transmitted from the sensor node after learning, to compare states of the monitoring targets indicated by the sensor data with the learning data, thereby to detect an abnormality occurrence or symptom in the monitoring targets” in limitation [c].
Here, the limitation [c] covers performance of the limitation in mind but for the recitation of the generic computer component, namely 1“a state detection unit” (“a personal computer” per para. 0103). Put differently, the limitation(s) shown with bold emphasis, under BRI, are considered an abstract idea based exception because they can be practically performed in human mind at most with the aid of pen and paper. In this instance, to learn various normal states (when the state combinations are small in numbers such as two or three for example) of the at least two targets (e.g., machines), human mind can observe few samples (4- 5 samples of data) that are already made available before him/her and can think of normal values of the monitored target during normal operation as part of the learning based on the sensor data samples. When the newly received data is different than the already learned data profile as part of the comparing states, human mind can judge that there is/are anomaly occurring and can detect an abnormality occurrences in the monitored targets. Please note that if a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components as in this case, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
3. Step 2A, Prong 2: No. This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements shown above without bold emphasis. That is, the limitations [a] – [b] and a state detection unit are additional elements. Here, a self-powered sensor node (due to having a power supply unit) having a sensor and a communication capability is being utilized to collect data from two (“being commonly used by a plurality of the monitoring targets”) monitoring targets. The sensor node can be a camera or something like that can capture images of two locations/machines. The limitation of “a receiver configured to receive the sensor data transmitted from the communication unit” is merely receiving the data that can be transmitted from the sensor node to the a state detection unit hence is a data gathering step recited at high level. Therefore, the limitations [a] to [b] are akin to adding an insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g) or generally linking the use of the judicial exception to a particular technological environment or field of use (namely in a remote monitoring of a production facility) – see MPEP 2106.05(h). The using of the state detection unit is akin to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). Accordingly, the individual/combination of additional elements fail to integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the above abstract idea. The claim is directed to an abstract idea.
4. Step 2B: No. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element(s) of limitations [a] to [b] amounts to no more than adding an insignificant extra-solution activity or generally linking the use of the judicial exception to a particular technological environment or field of use. The limitation of “a state detection unit” is implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Furthermore, the limitations [a] and [b] are well-understood, routine, conventional activity as can be proved by the cited arts. See Cobb (US 20220321585 A1, para. [024]- camera for multiple machines; Matsuzoe (JP2017035025A-- fig. 6 a movable sensor 8 with power supply); Chan (US 20200064446 A1, para. [029]- using mobile sensor devices to track multiple targets) as example evidence. Accordingly, the additional elements when considered separately and in combination do not add significantly more (also known as an “inventive concept”) to the exception. The claim is not patent eligible.
Regarding claims 10- 13, they depend on claim 1 and hence recite the same abstract idea and additional elements set forth above. These claims further add other limitations. In claims 10- 11, the added limitations (other than “a model storage unit configured to store a model of the learning data”) recite various limitations that under BRI cover performance of the limitation in the mind but for the recitation of the generic computer components namely, “a learning unit”, “a conjecture result output unit”, and “a signal output unit”. The limitation of “a model storage unit configured to store a model of the learning data” is merely used as data gathering and storing step hence is akin to adding an insignificant extra-solution activity which is well-understood, routing, and conventional and examiner takes an Official notice to that effect--Berkheimer memo. These various new units of the claims 10-11 are applied as “do it on a computer” to perform an abstract idea. Even considering additional elements individually or in combination, the claims 10- 11 fail to provide a practical application and an inventive step.
As to claims 12- 13, the newly added limitations are additional elements. However, they too are akin to adding insignificant extra-solution activities and are well-understood, routine, and conventional, and examiner takes an Official notice to that effect-Berkheimer memo. Even considering additional elements individually or in combination, the claims 10- 11 fail to provide a practical application and an inventive step. The claims 10- 13 are not patent eligible.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1- 4 & 13- 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cobb et al. (US 20220321585 A1, filing date: 2021-03-31) in view of Matsuzoe (2JP 2017035025 A).
Regarding claim 1, Cobb teaches a facility state monitoring system [“example environment 100 for anomaly detection”] comprising:
[a] a sensor node [“Sensors 121, 122, 123, and 124 are configured to capture machine condition data” or a camera] including (i) a sensor [one or more of the sensor s121-125 installed in the machine 120 of fig. 1] configured to output, as sensor data, data indicating a state of a facility as a monitoring target [machine 120] to be monitored, (ii) a communication unit [network interface that allows to transmit data of the sensor to the detection server 110] configured to transmit the sensor data, and (iii) multiple machines” of the entire process] ([041, 048]),
the sensor node being commonly used [“machine condition data is captured at least partially using one or more cameras that monitor the condition of machines and thereby capture the physical state of the machines”. Therefore, a camera sensor (as part of “one or more” when one camera is used) is shared by multiple machines] by a plurality of the monitoring targets ([047]);
[b] a receiver [network interface such as “network components 350” of the server 110 when the computer 310 is used to implement the server 110] configured to receive the sensor data transmitted from the communication unit ([056]); and
[c] a state detection unit [“anomaly detection server”, e.g., server 110] configured to receive [step 410 of fig. 4 to receive “training analysis vectors” of the monitored machines] the sensor data received by the receiver, to learn [“detection server receives condition data in order to learn and recognize acceptable normal patterns”], as learning data, normal states of the monitoring targets based on normal sensor data corresponding to normal operations of the monitoring targets [“the anomaly detection server applies the same approach to an entire process spanning multiple machines”], and in response to the receiver receiving the sensor data transmitted from the sensor node after learning, to compare states [“a discrepancy exists between the monitoring analysis vectors (whether individually or in sequence or timed sequence) and normal patterns”] of the monitoring targets indicated by the sensor data with the learning data, thereby to detect [Fig. 4, Steps 440-450: “it transmits an alert indicating an anomaly or a potential anomaly”] an abnormality occurrence or symptom in the monitoring targets ([031-032, 039, 041, 057]).
Cobb teaches:
[0057] FIG. 4 is a flowchart of an example method 400 of anomaly detection, such as in the environment of FIG. 1. Anomaly detection server 110 (shown in FIG. 1) is configured to cause processor 111 to receive 410 a plurality of training analysis vectors associated with a monitored machine during a training period from the at least one sensor, wherein each of the training analysis vectors describe a condition of the monitored machine at a corresponding point in time. Anomaly detection server 110 also causes processor 111 to apply 420 the training analysis vectors to a machine learning model to create a trained machine learning model configured to describe normal states in the monitored machine as indicated by training analysis vectors. Anomaly detection server 110 also causes processor 111 to receive 430 a plurality of monitoring analysis vectors associated with the monitored machine during a monitoring period from the at least one sensor, wherein each of the monitoring analysis vectors describe a condition of the monitored machine at a corresponding point in time. Anomaly detection server 110 also causes processor 111 to apply 440 the plurality of monitoring analysis vectors to the trained machine learning model to identify at least one discrepancy indicating an anomalous state in the monitored machine. Anomaly detection server 110 also causes processor 111 to transmit 450 an alert indicating that an anomaly is detected in the monitored machine.
Cobb teaches a sensor node (like a camera 125) receiving sensor data and transmitting the sensor data to the detection server 110using communication network. However, Cobb fails to teach how (with its own power supply or by receiving power from the machine) its camera is able to perform its functions such as to capture sensor data and to transmit data to the server 110.
Cobb may not explicitly teach its sensor node to include a power supply unit configured to supply power to the sensor and the communication unit as claimed and shown with strikethrough emphasis.
Matsuzoe relates to a collecting sensor data from the pluralities of the monitoring targets using small numbers of sensors 8 of a facility [“environmental control system”, e.g., “in the plant factory 1… planter 2”, analogous to Cobb’s “in manufacturing and production environments.” of para. 019], and to transmit the collected information to a state detection unit [“The control apparatus 10 controls”, fig. 8] for processing (Figs. 1, 7-9, [006, 023, 044]). More specifically, Matsuzoe teaches a facility state monitoring state comprising:
a sensor node [“a movable sensor unit 8 is disposed on the rail 6”, analogous to camera 125 of Cobb’s fig. 1] including a sensor [“sensor unit 8 includes a sensor unit 37”] configured to output, as sensor data, data indicating a state of a facility as a monitoring target [various sections as shown in figs. 9s of the planter 2 being monitored by the movable sensor 8] to be monitored, a communication unit configured to transmit [“communication unit 41 has a function of transmitting sensor information to the outside”] the sensor data, and a power supply unit [“the sensor unit 8 includes a sensor unit 37, a drive control unit 38, a control unit 39, a power supply unit 40, a communication unit 41,”] configured to supply power to the sensor and the communication unit ([032-039]),
the sensor node being commonly used by a plurality [“one sensor unit 8 is superior in terms of cost and control, it is preferable that one sensor unit 8 is provided for one planter 2”] of the monitoring targets [“the planter 2 is divided into a plurality of sections A to F in the longitudinal direction”, “it is possible to control the environment of the planter 2 for each of a plurality of sections in the direction of the running path”] ([042, 071-072]).
The Matsuzoe teaches:
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It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to (1) combine Matsuzoe and Cobb because they both related to a state detection unit (a monitoring computer) to receive and process monitored sensor data from a sensor node and (2) modify the sensor node (e.g., camera 125) of Cobb to include a power supply unit thereon and also make the sensor node movable as in Matsuzoe. Doing so would allow to operate the camera/sensor of the Cobb without having to receive operating power from the machines 120. Furthermore, doing so would allow to use fewer sensors/cameras to monitor the “entire process spanning multiple machines” thereby saving cost on how many sensors need to be used (Cobb, [041] & Matsuzoe [042]). Accordingly, Cobb in view of Matsuzoe combines to teach each elements and renders invention of this claim obvious to PHOSITA.
Regarding claim 2, Cobb in view of Matsuzoe further teaches the facility state monitoring system according to claim 1, wherein the sensor node is disposed on a mobile object [the housing of the sensor 8 that couples to “a rail (running path) 6 extending along the longitudinal direction“] and is moved along with the mobile object to acquire sensor data indicating the states of the monitoring targets; and wherein the state detection unit is configured to detect the abnormality occurrence or symptom in each of the monitoring targets, thereby to specify a location [“the anomaly detection server generates a “heat map” showing in which location”] where the abnormality occurrence or symptom is detected in the monitoring targets (Matsuzoe [071] & Cobb [039, 047]).
By disposing the sensor node (e.g., a camera 125) on a moving object (rail 6 of Matsuzoe) allows moving it to capture data from multiple machines 120 using the single camera thereby saving the cost (Matsuzoe [042]).
Regarding claim 3, Cobb in view of Matsuzoe teaches the facility state monitoring system according to claim 2, wherein the mobile object is a transport path [“the rail (running path) 6 and the sensor unit 8 may be arranged one by one in each planter 2,”]; and wherein the sensor node is disposed on the transport path and is moved along with the transport path, and the state detection unit is configured to detect the abnormality occurrence or symptom in the monitoring targets based on the sensor data output from the sensor during movement (Matsuzoe, [085] & Cobb [039, 043]).
Regarding claim 4, Cobb in view of Matsuzoe teaches/suggests the facility state monitoring system according to claim 3, wherein the monitoring targets [sections/machines of the planter 2/facility] are included in a production facility and the transport path is used to transport a product [the claim, under BRI, covers every possible product including image/sensor data or a digital product (image) captured by the camera 8] in the production facility; and wherein the state detection unit is configured to detect the abnormality occurrence or symptom in facilities provided from the beginning to the end of manufacturing of the product in the production facility as the monitoring targets (Matsuzoe [072, 082]).
Regarding claim 13, Cobb in view of Matsuzoe further teaches the facility state monitoring system according to claim 1, comprising: a storage unit [“memory 112,”] configured to be communicable with the sensor node, wherein the storage unit is configured to receive the sensor data and store the sensor data in association with information corresponding to the reception time of the sensor data (Cobb [048] & Matsuzoe [056]).
Regarding claim 14, Cobb in view of Matsuzoe further teaches the facility state monitoring system according to claim 1, wherein the sensor node includes a composite sensor [“sensor unit 37 is configured to include, for example, a temperature sensor 44, a humidity sensor 45, and a CO 2 sensor 46.” A single sensor unit 37 has multiple sensors disposed thereon and can be called composite/mixed sensor under BRI] provided with a plurality of the sensors; and wherein the state detection unit is configured to perform a composite [checking multiple parameters such as humidity, temperature, force etc.] processing by using the sensor data output from the sensors and to detect the abnormality occurrence or symptom in the monitoring targets (Cobb Fig. 3 & Matsuzoe, [035]).
Regarding claim 15, Cobb in view of Matsuzoe further teaches the facility state monitoring system according to claim 14, wherein the sensor node includes: a plurality of wireless sensor substrates including at least one of a plurality of the sensors; the communication unit disposed on at least one of the wireless sensor substrates [the housing where “temperature sensor 44, a humidity sensor 45, and a CO 2 sensor 46” are attached on the sensor unit 37]; and the power supply unit having a polyhedral shape (interpreted as having a 3D shape like a cub per dictionary meaning) [“power supply unit 40 has a function of supplying electric power” means it is a solid 3D structure], wherein the sensor node has a polyhedral shape in which the wireless sensor substrates are disposed on one or more of faces of the polyhedral shape of the power supply unit (Cobb Fig. 1; Matsuzoe Fig. 6, 9 [034- 035, 038]).
Claim(s) 10- 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cobb in view of Matsuzoe, and further in view of Sasaki et al (US 20210096532 A1). The combination of Cobb, Matsuzoe, and Sasaki is referred as CMS hereinafter.
Regarding claim 10, Cobb in view of Matsuzoe further teaches/suggests the facility state monitoring system according to claim 1, wherein the state detection unit includes: (server 12, fig. 1);
a learning unit [“processor is also configured to apply the training analysis vectors to a machine learning model to create a trained machine learning model”] configured to learn, as learning data, at least one of a characteristic part and chronological data included in the sensor data for each component in each of the monitoring targets based on the sensor data corresponding to the normal operation of the monitoring target ([0008, 057]);
a model storage unit [storage used to store “deemed to be sufficiently trained” model] configured to store a model of the learning data.
While Cobb in view of Matsuzoe teaches its server 110 to calculate the abnormality by comparing the received sensor data with the learned data to output a detection result (Cobb, para. 041), it still does not teach determining of a quantized degree of deviation from the learning data as claimed. Thus, Cobb in view of Matsuzoe fails to teach the detection unit to include:
a conjecture result output unit configured to calculate, in response to the receiver receiving the sensor data transmitted from the sensor node after the learning, an abnormality degree as a quantized degree of deviation from the learning data in at least one of a characteristic part and chronological data represented by the sensor data; and a signal output unit configured to compare the abnormality degree with a predetermined threshold value to thereby detect the abnormality occurrence or symptom in the monitoring targets, and to output a detection result but this deficiency is cured by Sasaki.
Sasaki relates to using a monitoring device (computer 2 of fig. 1) for detecting a sign of malfunction in the monitored mechanical equipment 1 based on the data captured by one or more sensors 10 (Fig. 1, [001]) Specifically, Sasaki teaches a facility state monitoring system [“malfunction prediction apparatus 2 includes a controller 20”, analogous to Cobb’s anomaly detection server 110] comprising a state detection unit configured to receive the sensor data, wherein the state detection unit including: (Fig. 1, [046]);
a learning unit configured to learn, as learning data [“the learning data 303 is a data set of the feature value data 302 generated from collection data”], at least one of a characteristic part and chronological data included in the sensor data [“collection portion 201 collects sensor data from the sensor group 10”] for each
component in each of the monitoring targets based on the sensor data corresponding
to the normal operation of the monitoring target [“mechanical equipment 1”] ([056-058]);
a conjecture result output unit [“A calculation portion 205 calculates a deviation degree 306 from the normal state of the mechanical equipment 1”] configured to calculate, in response to the receiver receiving the sensor data transmitted from the sensor node after the learning, an abnormality degree [“deviation degree”] as a quantized degree of deviation from the learning data in at least one of a characteristic part and chronological data represented by the sensor data; and a signal output unit configured to compare [“In the case where all of calculated deviation degrees are equal to or greater than a determination threshold, determines that there is a sign of malfunction”] the abnormality degree with a predetermined threshold value to thereby detect [“there is a sign of malfunction”] the abnormality occurrence or symptom in the monitoring targets, and to output a detection result ([062-065, 088-089]).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to (1) combine Sasaki and Cobb in view of Matsuzoe because they both related to state detection server learning the sensor data of the monitored target to identify abnormalities and (2) modify the Cobb in view of Matsuzoe’s server to include a conjecture result output unit and a signal output unit as in Sasaki. The motivation for doing so would be to increase precision of abnormality determination in the system of Cobb in view of Matsuzoe (Sasaki, [0110]). Furthermore, doing so would allow to evaluate by how much the condition of the monitored machines of the Cobb have changed from the start of the use or from the previous maintenance operation(s) (Sasaki [090]).
Regarding claim 11, CMS further teaches the facility state monitoring system according to claim 10, wherein the conjecture result output unit is configured to calculate, as the abnormality degree, a subsequently assumed abnormality degree in addition to a current abnormality degree at which the sensor data is received; and wherein the signal output unit is configured to detect the abnormality occurrence based on the current abnormality degree and to detect the abnormality symptom based on the subsequently assumed abnormality degree (Cobb [047], Sasaki [088-089]).
Regarding claim 12, CMS further teaches the facility state monitoring system according to claim 10, comprising: a display device configured to display a detection result that is detected by the state detection unit and is output from the signal output unit (Cobb [047] & Sasaki [069]).
Claim(s) 5- 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cobb in view of Matsuzoe, and further in view of Sakuma (JP 2001317687 A, Publication Date: 2001-11-16). The combination of Cobb, Matsuzoe, and Sakuma is referred as CMS2 hereinafter.
Regarding claim 5, Cobb in view of Matsuzoe teaches the facility state monitoring system according to claim 2, wherein the sensor node includes a camera to capture sensor data (Cobb [024]). Cobb in view of Matsuzoe’s camera is exposed to the wind but fails to discuss how it can solve the problem of camera/sensor shaking/vibration due to wind exposing on the moving sensor (modified camera of Cobb).
Sakuma relates to a sensor node (camera 22) being attached with a structure (“tripod holder”) that prevents shaking of the sensor node while using the sensor node (Abstract, fig. 1). Specifically, Sakuma teaches a system comprising a sensor node including a sensor [“camera 22”] configured to output, as sensor data, data indicating a state of a facility as a monitoring target to be monitored (Fig. 1),
wherein the sensor node includes a vibration suppression structure3 [“storing a weight member in the holder main body”, “camera equipment and the like are accommodated in the pocket 16 as a weight member. By doing so, the holder main body 12 is tensioned by the weight of the weight member, and the weight is transferred to each leg piece 3a via the hook fitting 11 and the suspension ring 8. The center of gravity of the camera tripod 1 is positioned downward, and the lower end of each leg piece 3c strongly presses the ground 2 so that the camera tripod 1 is stabilized. Therefore, vibration of the camera tripod 1 due to wind or the like is prevented, and image blurring of the camera 22 is prevented.”] to suppress vibrations different from vibrations of the monitoring targets (page 5, Claim 1).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to (1) combine Sakuma and Cobb in view of Matsuzoe because they both related to using a movable sensor node to capture sensor data and (2) modify the sensor node of Cobb in view of Matsuzoe to include vibration suppression structure of Sakuma. Doing so would prevent problem of vibration due to wind or the like causing camera/sensor shake (Sakuma, page 5). Accordingly, the combination of Cobbe, Matsuzoe, and Sakuma (CMS2) teach each element of the claim and renders invention thereof obvious to PHOSITA.
Regarding claim 6, CMS2 teaches the facility state monitoring system according to claim 5, wherein the vibration suppression structure shifts the center of gravity of the sensor node downward [“weight member, and the weight is transferred to each leg piece 3a via the hook fitting 11 and the suspension ring 8., The center of gravity of the camera tripod 1 is positioned downward, and”] from the center of the sensor node in a vertical direction (Sakuma, page 5).
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over combination of CMS2 (as in claim 5) in view of Tsun et al. (US 20020078986 A1).
Regarding claim 7, CMS2 teaches The facility state monitoring system according to claim 5 including a vibration suppression structure to suppress vibration in the movable sensor node as set forth above.
However, CMS2 fails to teach such vibration suppression structure to also include a through-hole penetrating the sensor node in a direction corresponding to a direction of a wind flowing against the sensor node.
Tsun relates to a umbrella cover for wind-stable umbrella. Specifically, Tsun teaches a moving body including a vibration suppression structure to suppress vibrations, wherein the vibration suppression structure includes a through-hole [“allowing the wind to blow through the wind passage 54”] penetrating the moving body in a direction corresponding to a direction of a wind flowing against the moving body ([022-024]).
Both Tsun and CMS2 are analogous art because they are from similar problem solving area, namely minimizing the shaking with blowing air to a moving body. It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the sensor node of the CMS2 by incorporating a through-hole penetrating the sensor node in a direction corresponding to a direction of a wind flowing against the sensor node as in Tsun and to obtain the invention as specified in the claim. The suggestion/motivation for doing so would have been to allow the strong wind impacting on the moving sensor node of the CMS2 to quickly move out from impacting the movable sensor node thereby minimizing unstability that can be caused by the blowing air (Tsun [024]).
Allowable Subject Matter
Claim 8- 9 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Specifically, the claims 8- 9 recite novel and non-obvious subject matter over prior arts of the record.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
1) Scheuermann et al. (US 20230214747 A1) teaches an air-borne unmanned autonomous vehicle (UAV), the path along which the mobile sensor platform moves while collecting data ([0153]).
2) Chan et al. (US 20200064446 A1) teaches provides a cooperative, cost-effective and highly accurate system using mobile sensor devices to track multiple targets ([029]).
3) Kane (US 20220200854 A1) teaches a system comprising a sensor node [movable sensor arrays 100A-H] to collect sensor data of an assembly line and a state detection unit [server 120] to receive the sensor data (Fig. 1, [025]).
Contacts
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/SANTOSH R POUDEL/ Primary Examiner, Art Unit 2115
1 See, Spec, para. 0103 that states “the reception unit 20 and the state detection unit 30 can also be configured as a device such as a personal computer that includes the reception function and various arithmetic processing functions.”
2 Note: For convenience, the JP 2017035025 A document along with its machine translation to English are attached as the single FOR and the cited paragraphs are from the attached FOR document.
3 See spec, para. 040 that states “the vibration suppression structure may be configured so that, in the vertical direction, the lower part of the housing 14 is formed of a material with a large mass per unit volume” as in Sakuma’s system.