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
As required by M.P.E.P. ' 609 (C), the applicant's submission of the Information Disclosure Statement dated May 15th, 2025, and January 9th, 2026, are acknowledged by the examiner and the cited references have been considered in the examination of the claims now pending. As required by M.P.E.P. ' 609 C(2), a copy of the PTOL-1449 initialed and dated by the examiner is attached to the instant office action.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-2, 10-12 and 16 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Peng [CN113867142]. Peng teaches sensor control method, device, electronic device and storage medium.
Regarding claims 1 and 16, Peng teaches a method, applied to a data processing device [Peng page 4, bottom 3rd, “…running on a processor…”], wherein the method comprises:
obtaining a first data feature of a first data block [Peng page 3, bottom 3rd, “…obtain the first sensor data…”], wherein the first data block is sampled data [Peng page 3, bottom 3rd, “…sensor data…”], and wherein the first data feature indicates a first change between a plurality of valid data values in the first data block [Peng page 3, bottom 3rd, “…determining the second sensor data relative to the change value of the first sensor data as the data change value…”]; and
determining a first sampling frequency of a second data block based on the first data feature [Peng page 4, middle page, “…determining a first target sampling frequency according to the data change value…” and page 3, middle page, “…adjusting the initial sampling frequency as the target sampling frequency…”] and a sampling frequency constraint condition [Peng page 4, middle page, “…a set threshold value…”], wherein the second data block is to-be-sampled data [Peng page 4, bottom 3rd, “…to effectively ensure the detection effect of the sensor…” and Peng page 8, first lines “…it can self-adaptively adjust the sampling frequency of the sensor, so as to effectively ensure the detection effect of the sensor…”].
Regarding claim 2, as per claim 1, Peng teaches the first data block comprises a plurality of data windows [Peng page 7, middle lines “…t-t1 period…in the time period t1-t2…”], wherein each of the plurality of data windows comprises at least one indicator value [Peng page 7, middle paragraphs “…average value of the sensor data in the current time period…”],
wherein the plurality of data windows comprises a first data window and a second data window [Peng page 7, middle lines “…t-t1 period…in the time period t1-t2…”],
wherein the first data feature indicates data features of the plurality of data windows [Peng page 7, middle paragraphs “…average value of the sensor data in the current time period…”], and wherein obtaining the first data feature comprises:
determining a first valid data value of the first data window [Peng page 3, bottom 3rd, “…analyzing to obtain the first sensor data in the first time range…”] and a second valid data value of the second data window [Peng page 3, bottom 3rd, “…analyzing to obtain the second sensor data in the second time range…”, wherein the second data window is adjacent to the first data window [Peng page 7, middle lines “…t-t1 period…in the time period t1-t2…”( 2 comes next to 1 and 1 comes next to zero thus they are adjacent.)]; and
determining that the first data feature is a first change value between the second valid data value and the first valid data value [Peng page 3, bottom page “…determining the second sensor data relative to the change value of the first sensor data as the data change value…”].
Regarding claim 10, as per claim 1, Peng teaches determining the first sampling frequency based on the first data feature comprises inputting the first data feature into a neural network model to obtain the first sampling frequency, and wherein the neural network model is based on performing model training using the first data feature as a sample and using a second sampling frequency of the first data block as a label of the sample [Peng page 10, bottom paragraph “…sampling frequency prediction model can be according to history sampling frequency of the sensor adjusting recording training to obtain the deep learning model…neural network model and so on…not limiting…”].
Regarding claim 11, as per claim 1, Peng teaches the data processing device is a data transmitting end [Peng page 6, 4th paragraph, “…an acceleration sensor in the electronic device…”], and wherein determining the first sampling frequency based on the first data feature comprises:
obtaining the sampling frequency constraint condition from a data receiving end [Peng page 7, middle “…an acceleration sensor configured in a mobile phone may be used for example, when the mobile phone executes high-power-consumption algorithm work such as inertial navigation, mode recognition, a pedometer, and the like, a sampling frequency with a higher frequency may be needed to meet the requirement of the mobile phone algorithm work, and at this time, the initial sampling frequency may be adjusted according to a data change value to obtain a target sampling frequency…”]; and determining the first sampling frequency based on the sampling frequency constraint condition and the first data feature [Peng page 6, middle lines “…based on the initial sampling frequency, starting the sampling of the sensor, can be starting the sampling…preset time of the sensor…”].
Regarding claim 12, as per claim 1, Peng teaches sampling the second data block based on the first sampling frequency to obtain transmission data [Peng page 4, middle page, “…determining a first target sampling frequency according to the data change value…”] and sending the transmission data to the data receiving end [Peng page 14, first big paragraph “…the memory 801 and the processor 802 can be connected to each other through the bus and communicate with each other…” and bottom page 5, “…a server or a central processing unit …”](It would be implied that the sensor data is transmitted to the receiving end.)].
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, 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.
Claims 13-15 and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Peng [CN113867142] in view of Richart et al. [US2021/0226647]. Peng teaches sensor control method, device, electronic device and storage medium. Richart teaches method and system for obtaining and storing sensor data.
Regarding claim 13, as per claim 1, Peng fails to explicitly teach the data processing device is a data receiving end, and wherein the method further comprises: sending the first sampling frequency to a data transmitting end; and
receiving transmission data from the data transmitting end, wherein the transmission data is based on sampling the second data block based on the first sampling frequency.
However, Richart does teach the data processing device is a data receiving end [Richart paragraph 0137, last lines “…The server 130 may subscribe to topics of the sensors 120 and may then receive sensor values or sampled signals.…”], and wherein the method further comprises: sending the first sampling frequency to a data transmitting end [Richart paragraph 0037, first lines “…it is contemplated that a sensor 121 may be acquiring and transmitting its sensor values according to a Nyquist sampling scheme during the Nyquist sampling time window 211, and likewise may be acquiring and transmitting its sensor values according to a compressive sampling scheme during a compressive sampling time window 221…”]; and
receiving transmission data from the data transmitting end, wherein the transmission data is based on sampling the second data block based on the first sampling frequency [Richart paragraph 0034, middle lines “…the server 130 or the message broker 160 would receive one Nyquist sampled signal within a sampling time window, then, by using the time multiplexing compressive sampling schemes, the receiver (here substituted for the gateway 110, server 130 or message broker 160) may receive multiple compressively sampled signals within the same (common) sampling time window…”(The examiner has determined the receiving end will inherently have a transmitting end sending the data to be received.)].
Peng and Richart are analogous arts in that they both deal with sampling data.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Peng’s sensor sampling with Richart’s teachings of receiving and transmitting for the benefit of reducing data transmission overhead between the gateway and the server [Richart paragraph 0049, first lines “…to reduce the data transmission overhead…”].
Regarding claim 14, as per claim 1, Richart teaches sending the sampling frequency constraint condition to the data transmitting end [Richart paragraph 0029, middle lines “…A gateway 110 or a server 130 may determine the compressive sampling scheme for the sensor 121, and may also determine or select the set of M time instants from the total number of N time instants within the sampling time window…”(The examiner has determined the sampling scheme reads on the frequency constraint condition since it functions in the same regard.)].
Regarding claim 15, as per claim 1, Peng teaches analyzing the transmission data to obtain an analysis result of the transmission data [Peng page 9, 3r paragraph, “…the sensor data can be analyzed to obtain the second sensor data, for example, it can analyze the time information corresponding to the sensor data, to obtain the time information t2 matched with the second starting time point, and the time information t matched with the current time point, to obtain the second time range is t2-t time range, and determining a plurality of sensor data between t2-t time range, then it can be used as the second sensor data…”].
Regarding claim 17, Peng teaches a data processing system [Peng page 4, bottom 3rd, “…running on a processor…”] comprising:
a memory configured to store instructions [Peng page 14, top of page, “…The memory 801…”]; and
a processor coupled to the memory [Peng page 14, top of page, “…a communication interface 803, for communication between the memory 801 and the processor 802…”] and configured to execute the instructions to cause the data processing [Peng page 14, top of page, “…The processor 802 is used for implementing the sensor control method…”] system to:
obtain a data feature of a first data block [Peng page 3, bottom 3rd, “…obtain the first sensor data…”], wherein the first data block is sampled data [Peng page 3, bottom 3rd, “…sensor data…”], and the data feature indicates a change between a plurality of valid data values in the first data block [Peng page 3, bottom 3rd, “…determining the second sensor data relative to the change value of the first sensor data as the data change value…”];
determine a sampling frequency of a second data block based on the data feature [Peng page 4, middle page, “…determining a first target sampling frequency according to the data change value…” and page 3, middle page, “…adjusting the initial sampling frequency as the target sampling frequency…”] and a sampling frequency constraint condition [Peng page 4, middle page, “…a set threshold value…”], wherein the second data block is to-be-sampled data [Peng page 4, bottom 3rd, “…to effectively ensure the detection effect of the sensor…” and Peng page 8, first lines “…it can self-adaptively adjust the sampling frequency of the sensor, so as to effectively ensure the detection effect of the sensor…”];
sample the second data block based on the sampling frequency to obtain first transmission data [Peng page 11, 3rd paragraph, “…after determining the data change value of the second sensor data relative to the first sensor data, the data change value and the preset threshold value (set threshold can be self-adaptive configuration according to the actual service scene, not limiting) for comparison, if the data change value is less than or equal to the set threshold value, the target sampling frequency can be determined according to the data change value, the target sampling frequency can be referred to as the second target sampling frequency, the second target sampling frequency is less than the initial sampling frequency…”];
Peng fails to explicitly teach send the first transmission data; and receive second transmission data.
Peng fails to explicitly teach send the first transmission data [Richart paragraph 0031, middle lines “…at each of the sampling time instants of a corresponding sampling time window, the sensor would send a sensor value…”]; and
receive second transmission data [Richart paragraph 0034, middle lines “…the gateway 110, the server 130 or the message broker 160 would receive one Nyquist sampled signal within a sampling time window, then, by using the time multiplexing compressive sampling schemes, the receiver (here substituted for the gateway 110, server 130 or message broker 160) may receive multiple compressively sampled signals within the same (common) sampling time window…”].
Peng and Richart are analogous arts in that they both deal with sampling data.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Peng’s sensor sampling with Richart’s teachings of receiving and transmitting for the benefit of reducing data transmission overhead between the gateway and the server [Richart paragraph 0049, first lines “…to reduce the data transmission overhead…”].
Regarding claim 18, as per claim 17, rejected for the same rational as claim 15 above.
Regarding claim 19, as per claim 17, Richart teaches the processor is further configured to execute the instructions to cause the data processing system to obtain the sampling frequency constraint condition based on the analysis result [Richart paragraph 0063, middle lines “…With a well defined periodicity of the Nyquist sampling period (i.e. after the predetermined time at which the dynamics of the data change notoriously) the updated sparsity S(p+1)=k may be defined as the input parameter for the CPPCA method which the gateway 110 may use to extract the projection coefficients…”].
Regarding claim 20, as per claim 17, Richart teaches the sampling frequency constraint condition is a frequency conversion periodicity constraint [Richart paragraph 0056, last lines “…The same sparsifying transform may be set constant over a specific number of Nyquist sampling windows, until it may be actualized again. The actualization may be set periodically or it might be triggered when the distribution of the decomposition components might change above a determined threshold from the previous step…”].
Allowable Subject Matter
Claims 3-9 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Fry et al. [US2022/0222572] Fry teaches monitoring data flow with sensors using constraints in different monitoring windows.
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/ERIC CARDWELL/Primary Examiner, Art Unit 2139
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