Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
2. This Office Action is in response to the filing with the office dated 12/22/2025.
Claims 1, 4, 11, 14 and 20 have been amended. Claims 1, 11 and 20 are independent claims. Claims 1-20 are presented for examination.
Information Disclosure Statement
3. The information disclosure statement (IDS) submitted on 11/20/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to amendment/arguments
4. Applicant’s arguments with respect to the rejection of claims under 35 U.S.C. § 101 as the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more, have been fully considered. However, Examiner respectfully disagrees with the applicant’s argument. See response to arguments section. The rejection has been maintained.
5. Applicant’s arguments with respect to the rejection of claims under 35 U.S.C. § 102 (a)(i) and 103(a) have been fully considered but are moot because the arguments are directed towards amended claims, thus necessitated the new ground of rejection as presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
Response to 101 amendments/ arguments
6. Applicant’s arguments on page 10 regarding 101 rejection states “the claimed method cannot be performed mentally or with pen and paper because it requires a hardware streaming router capable of operating at real-time throughput, memory-stored ingestion specifications that the router applies directly to the updated improved sensor data, and automated selection and modification of specific time-series database containers, all of which are explicitly tied to a concrete technological architecture for sensor-data ingestion and correction. No human mind can perform hardware-level routing, execute ingestion specifications, or manipulate time-aligned data across parallel time- series databases at real-time speeds. Therefore, the subject matter of independent claim 1 is not similar to alleged abstract idea. Clearly, the above-mentioned features cannot be regarded as certain methods that can be performed in human mind under Prong 1 of Step 2A.
Examiner respectfully disagrees as the limitations “performs ontology processing …”, “routing…”, “generating….”, “transmitting…” are all processes, that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. that under broadest reasonable interpretation, covers performance of the limitation in the mind. These limitations, at the high level of generality as drafted, would encompass a user to receive a sensor data, route/ send/ store the sensor data to a database and overwrite, which is to erase and write part of the sensor data based on the metadata and control the operations and ingest the sensor data based on the ingestion specification stored in a memory, which is mentally performable as an evaluation or judgement. 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, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Applicant’s arguments on page 10 regarding 101 rejection states “Regarding Prong 2 of Step 2A of the 2019 Revised Patent Subject Matter Eligibility Guidance, even if one were to arrive at a conclusion satisfying the Prong 1 of such analysis, assuming arguendo, to which the Applicant does not concede, the Applicant submits that the alleged abstract idea is integrated into a practical implementation. For instance, the subject matter of independent claim 1 can be practically realized in for instance, at least one building such as an industrial building, office building, warehouse, building associated with a plant, and/or the like which may involve one or more assets along with corresponding sensors. In such a building environment, the sensors may generate huge amounts of data in real time. However, at least some of the sensor data may be processed based on first sensor metadata and it may be later determined that the sensor data is to be processed based on second sensor metadata. In view of this, at least some portion of the sensor data processed based on the first sensor metadata may be backfilled with updated data which corresponds to at least some portion of the sensor data processed based on the second sensor metadata. Further, operations of various asset(s) may also be controlled, adjusted, and/or the like as well. See at least at paragraphs [0060], [0063], and [0010] of originally filed Specification. This accounts to a practical implementation”.
Examiner respectfully disagrees with the applicant because, generating sensor data utilizing the sensors to ingest data, store in a database and manipulating data with processor and memory can be programmed with logic and/or mathematical operation to perform the operations, that under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. The amended limitation “the routing comprises applying an ingestion specification…” is applying the rule to ingest and route data to the destination is mere applying the instruction by the computer as a tool. There is nothing in the claim element which precludes the step from practically being performed in the human mind. The combination of these additional elements is no more than mere instructions to apply the exception using series of steps. Accordingly, even in combination, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Examiner notes “at least some portion of the sensor data processed based on the first sensor metadata may be backfilled with updated data which corresponds to at least some portion of the sensor data processed based on the second sensor metadata. Further, operations of various asset(s) may also be controlled, adjusted, and/or the like as well” is not recited in the instant claims.
Applicant’s arguments on page 10 regarding 101 rejection states “ Regarding Step 2B, even if one were to arrive at a conclusion satisfying the Step 2A of such analysis, assuming arguendo, to which the Applicant does not concede, the Applicant submits that elements of amended independent claim 1 provide an inventive concept and amounts to significantly more than the exception itself.
Examiner respectfully disagrees with the applicant because, The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the recitation of generic computing components is still mere instructions to apply the exception under MPEP 2106.05(f) and does not provide significantly more. The of “receiving sensor data”, “transmitting” elements that were identified as insignificant extra-solution activity as mere data gathering and outputting when re- evaluated still does not provide significantly more. Considering the additional elements in combination and the claim as a whole does not change the analysis, and does not amount to significantly more. Thus the claims are abstract.
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.
7. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite receiving sensor data, generating improved sensor data and storing sensor data.
Regarding claims 1, 11 and 20 the limitations “performs ontology processing …”, “routing…”, “generating….”, “transmitting…”, are all processes, that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. that under broadest reasonable interpretation, covers performance of the limitation in the mind. There is, nothing in the claim element precludes the steps from practically being performed by a human mentally or with pen and paper. These limitations, at the high level of generality as drafted, would encompass a user to route/ send/ store the sensor data to a database and overwrite, which is to erase and write part of the sensor data based on the metadata and control the operations, which is mentally performable as an evaluation or judgement. 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, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, he claim recites the additional elements of, the invention being “computer…”, “apparatus….”, :processor”, “memory”, “circuitry”, “computer-readable storage medium” are recited at a high level of generality as generic computer components amount to nothing more than mere instructions to apply the recited abstract idea on a computer, under MPEP 2106.05(f). The additional element of “receiving sensor data”, “generating…”, “routing sensor data”, “transmitting the commands…” amount to mere necessary data gathering for the identified abstract ideas, which is insignificant extra-solution activity Combination of these additional elements is no more than mere instructions to apply the exception using series of steps to perform the mental process Accordingly, even in combination, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The “receiving sensor data”, “generating …”,“routing sensor data”, “transmitting…” elements that were identified as insignificant extra-solution activity as mere data outputting when re-evaluated still does not provide significantly more. Additionally, receiving data over a network (i.e. receiving the identification of the worker nodes) and transmitting data over a network (i.e. providing feedback from the worker node of its state of resources) are both WURC as evidenced by the court decisions in MPEP 2106.05(d)(II) The finding that this element is WURC is expressly supported by Looking to MPEP 2106.05 (d), based on court decisions well understood, routine and conventional computer functions or mere instruction and/or insignificant activity have been identified to include: Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321,120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TU Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQe2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); O/P Techs., /no., v. Amazon.com, Inc., 788 F,3d 1359, 1363, 115 USPQ2d 1090,1093 (Fed. Cir, 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPG2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result-a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink," (emphasis added)}; Insignificant intermediate or post solution activity -See Bilski v. Kappos, 581 U.S. 593, 611 -12, 95 USPQe2d 1001,1010 (2010) (well-known random analysis techniques to establish the inputs of an equation were token extra-solution activity); In Bilski referring to Flook, where Flook determined that an insignificant post-solution activity does not makes an otherwise patent ineligible claim patent eligible. In Bilski, the court added to Flook that pre-solution (such as data gathering) and insignificant step in the middle of a process (such as displaying on user device) to be equally ineffective. The specification and Claim does not provide any specific process with respect to the display output that would transform the function beyond what is well understood. Like as found in Electric Power Group, Bilski, the technical process to implement the input and display functions are conventional and well understood. Considering the additional elements in combination and the claim as a whole does not change the analysis, and does not amount to significantly more. Thus the claims are abstract.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the recitation of generic computing components is still mere instructions to apply the exception under MPEP 2106.05(f) and does not provide significantly more. The of “receiving sensor data”, “generating…”, “routing sensor data”, “transmitting” elements that were identified as insignificant extra-solution activity as mere data gathering and outputting when re- evaluated still does not provide significantly more. Considering the additional elements in combination and the claim as a whole does not change the analysis, and does not amount to significantly more. Thus the claims are abstract.
Claims 2, 12 recite “wherein the improved sensor data is routed to a first container in the second database” is a processes, that under broadest reasonable interpretation, covers performance of the limitation in the mind. There is, nothing in the claim element precludes the steps from practically being performed by a human mentally or with pen and paper and likewise do not provide "significantly more" than the abstract idea for similar reasons as the independent claim. These limitations, at the high level of generality as drafted, would encompass a user manipulate data and store it in a container, which is mentally performable as an evaluation or judgement. 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, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites additional element “database”. Accordingly, the elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application. Thus the claims are abstract.
Claims 3, 13 recite “wherein the updated improved sensor data is routed to a second container in the second database” is a processes, that under broadest reasonable interpretation, covers performance of the limitation in the mind. There is, nothing in the claim element precludes the steps from practically being performed by a human mentally or with pen and paper and likewise do not provide "significantly more" than the abstract idea for similar reasons as the independent claim. These limitations, at the high level of generality as drafted, would encompass a user manipulate data and store it in a container, which is mentally performable as an evaluation or judgement. 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, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites additional element “database”. Accordingly, the elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application. Thus the claims are abstract.
Claims 4, 14 recite “generating an ingestion specification…” is a processes, that under broadest reasonable interpretation, covers performance of the limitation in the mind. There is, nothing in the claim element precludes the steps from practically being performed by a human mentally or with pen and paper and likewise do not provide "significantly more" than the abstract idea for similar reasons as the independent claim. These limitations, at the high level of generality as drafted, would encompass a user to ingest/ receive data based on some specification/ rule. is a processes, that under broadest reasonable interpretation, covers performance of the limitation in the mind. There is, nothing in the claim element precludes the steps from practically being performed by a human mentally or with pen and paper and likewise do not provide "significantly more" than the abstract idea for similar reasons as the independent claim. These limitations, at the high level of generality as drafted, would encompass a user manipulate data and store it in a container, which is mentally performable as an evaluation or judgement. 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, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional element”. Accordingly, the elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application. Thus the claims are abstract.
Claims 5, 15 recite “wherein the first sensor data processing unit comprises at least one of first ontology circuitry, first normalization circuitry, or first interpolation circuitry and the second sensor data processing unit comprises at least one of second ontology circuitry, second normalization circuitry, or second interpolation circuitry.” is a processes, that under broadest reasonable interpretation, covers performance of the limitation in the mind and/or mathematical process. There is, nothing in the claim element precludes the steps from practically being performed by a human mentally or with pen and paper and likewise do not provide "significantly more" than the abstract idea for similar reasons as the independent claim. These limitations, at the high level of generality as drafted, would encompass a user manipulate data and store it in a container, which is mentally performable as an evaluation or judgement. 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, then it falls within the “Mental Processes” and/or “mathematical process” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites additional element “processing unit”. Accordingly, the elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application. Thus the claims are abstract.
Claims 6, 16 recite “wherein the first ontology circuitry is configured to associate the first sensor metadata with the sensor data” is a processes, that under broadest reasonable interpretation, covers performance of the limitation in the mind. There is, nothing in the claim element precludes the steps from practically being performed by a human mentally or with pen and paper and likewise do not provide "significantly more" than the abstract idea for similar reasons as the independent claim. These limitations, at the high level of generality as drafted, would encompass a user manipulate data based on ontology/ context, which is mentally performable as an evaluation or judgement. 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, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites additional element “circuitry”. Accordingly, the elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application. Thus the claims are abstract.
Claims 7, 17 recite “wherein the second ontology circuitry is configured to associate the second sensor metadata with the sensor data” is a processes, that under broadest reasonable interpretation, covers performance of the limitation in the mind. There is, nothing in the claim element precludes the steps from practically being performed by a human mentally or with pen and paper and likewise do not provide "significantly more" than the abstract idea for similar reasons as the independent claim. These limitations, at the high level of generality as drafted, would encompass a user manipulate data based on ontology/ context, which is mentally performable as an evaluation or judgement. 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, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites additional element “circuitry”. Accordingly, the elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application. Thus the claims are abstract.
Claims 8, 18 recite “wherein the second database is a time series database” is a processes, that under broadest reasonable interpretation, covers performance of the limitation in the mind. There is, nothing in the claim element precludes the steps from practically being performed by a human mentally or with pen and paper and likewise do not provide "significantly more" than the abstract idea for similar reasons as the independent claim. These limitations, at the high level of generality as drafted, would encompass a user manipulate data as timeseries, which is mentally performable as an evaluation or judgement. 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, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements. Accordingly, the elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application. Thus the claims are abstract.
Claim 9 recite “wherein generating the improved sensor data occurs in real-time” is a processes, that under broadest reasonable interpretation, covers performance of the limitation in the mind. There is, nothing in the claim element precludes the steps from practically being performed by a human mentally or with pen and paper and likewise do not provide "significantly more" than the abstract idea for similar reasons as the independent claim. These limitations, at the high level of generality as drafted, would encompass a user manipulate data in real time as received, which is mentally performable as an evaluation or judgement. 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, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites no additional elements. Accordingly, the elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application. Thus the claims are abstract.
Claims 10, 19 recite “further comprising: receiving second sensor data from the sensor during the second time period; and generating second improved sensor data, wherein generating the second improved sensor data comprises processing the second sensor data in the first sensor data processing unit based at least in part on the second sensor metadata” is a processes, that under broadest reasonable interpretation, covers performance of the limitation in the mind. There is, nothing in the claim element precludes the steps from practically being performed by a human mentally or with pen and paper and likewise do not provide "significantly more" than the abstract idea for similar reasons as the independent claim. These limitations, at the high level of generality as drafted, would encompass a user to receive data and manipulate data and store the data, which is mentally performable as an evaluation or judgement. 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, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, he claim recites the additional elements of, the invention being “computer…”, “apparatus….”, :processor”, “memory”, “circuitry”, “computer-readable storage medium” are recited at a high level of generality as generic computer components amount to nothing more than mere instructions to apply the recited abstract idea on a computer, under MPEP 2106.05(f). The additional element of “receiving sensor data”, “generating…”, “routing sensor data” amount to mere necessary data gathering for the identified abstract ideas, which is insignificant extra-solution activity Combination of these additional elements is no more than mere instructions to apply the exception using series of steps to perform the mental process Accordingly, even in combination, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application. Thus the claims are abstract.
Claim Rejections - 35 U.S.C. § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
10. Claims 1, 8-11 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Sayfan; Gigi (US 20160370338 A1) in view of LEE; Kwang-hyeon (US 20110071365 A1), Paulson; Erik S (US 20220137569 A1), DEY; Sounak (US 20150261863 A1) and in further view of Estrada; Adam (US 11961172 B1)
Regarding independent claim 1, Sayfan; Gigi (US 20160370338 A1) teaches, a computer-implemented method comprising: receiving sensor data from a sensor during a first time period connected to one or more assets (Paragraph [0033] a Period timestamp may be used to indicate the time period in which the sensor readings are generated. Also see Paragraph [0035]. Paragraph [0031] teaches, sensors connected to one or more assets.);
generating improved sensor data, wherein generating the improved sensor data comprises processing the sensor data in a first sensor data processing unit based at least in part on first sensor metadata (Paragraphs [0040], [0041] The sensor data processing system 102 processes the sensor data messages using the sensor metadata information stored in the sensor metadata database 106. More specifically, the sensor metadata information includes identifying information for each sensor, such as the sensor identifier and the associated sensor type. The metadata information further includes calibration data associated with each sensor. The data processor 104 processes the raw sensor data in the generically defined data fields in the sensor data message using the metadata information to apply the correct conversion for the sensor data type and to apply the corresponding calibration data for that particular sensor to the sensor data (Examiner interprets processing of raw sensor data/ correct conversion as improved sensor data));
routing the sensor data to a first database and the improved sensor data to a second database (Paragraph [0037] Returning to FIG. 2, the sensor data processing system 102 includes the message queue 103 for receiving and storing incoming sensor messages, the data processor 104 for processing the sensor messages, the sensor data database 108 for storing raw and processed sensor data. Also see Paragraph [0025] The calibrated sensor data may also be stored in the sensor data database 108 (Examiner interprets calibrated sensor data as improved sensor data (LEE et al teaches first and second database (Paragraph [0037]));
receiving, via a user interface, second sensor metadata during a second time period (Paragraph [0044] the sensor data processing system 102 includes a database (dB) factory 110 which queries the sensor metadata database 106 periodically for changes in any of the metadata tables. When a change in a metadata table is detected, the dB factory 110 sends instructions to the sensor data database 108 to create new data tables or to reconfigure the data tables in accordance with the detected changes in the metadata table. As thus constructed, any additive changes to the sensor data database 108 can be realized by merely making the change to the sensor metadata database 106. The sensor data database 108 can thus be readily reconfigured to accommodate changes in the distributed sensor system, such as to add a new sensor, new sensor type, a new geographic location or a new floor plan of an indoor structure (Examiner interprets receiving second sensor metadata as identifying a change in the sensor metadata periodically/ as a second time period). In embodiments of the present invention, the database factory 110 is a software process being executed on a processor);
retrieving the sensor data from the first database; generating updated improved sensor data, wherein generating the updated improved sensor data comprises processing the sensor data in a second sensor data processing unit based at least in part on the second sensor metadata; routing the updated improved sensor data to the second database (Paragraph [0025], [0027] when calibration data for a sensor is found to be inaccurate later on and new calibration data is generated (i.e., identifying that the sensor metadata has changed), the centralized backend system may regenerate the calibrated sensor data by retrieving the raw sensor data for that sensor and calibrating the raw sensor data again using updated calibration data. In this manner, historic sensor data can be corrected if the calibration data used was found to be inaccurate (i.e., generating updated improved sensor data/ corrected sensor data based on the updated metadata and sending the new calibrated data to the sensor data database) (second database is taught by LEE (Paragraph [0037].
Sayfan et al fails to explicitly teach, first database and second database; wherein the second sensor data processing unit performs ontology processing on the sensor data and the second sensor metadata to identify changes in the second sensor metadata; to overwrite at least a portion of the improved sensor data with the updated improved sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata; and generating one or more commands to control one or more operations of one or more assets associated with the sensor; and transmitting one or more control commands to a control system of the one or more assets to adjust the one or more operations of the one or more assets in real time.
LEE; Kwang-hyeon (US 20110071365 A1) teaches, routing the raw data to a first database and the processed data to a second database (Paragraph [0037] the first database 131 stores raw data of the pieces of blood glucose information and raw data of blood glucose management information corresponding to the pieces of blood glucose information, and the second database 132 stores data obtained by processing, e.g., by referring to the raw data stored in the first database 131. The processed data stored in the second database 132 is prepared by processing data to include the content of the blood glucose data stored in the first database 131);
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al by routing the sensor data to a first database and the improved sensor data to a second database; and routing the updated improved sensor data to the second database, as taught by LEE et al (Paragraph [0037]).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, when calibration data for a sensor is found to be inaccurate later on and new calibration data is generated, the centralized backend system may regenerate the calibrated sensor data by retrieving the raw sensor data for that sensor and calibrating the raw sensor data again using updated calibration data. In this manner, historic sensor data can be corrected if the calibration data used was found to be inaccurate, as taught by LEE et al (Paragraph [0027]).
Sayfan et al and LEE et al fails to explicitly teach, wherein the second sensor data processing unit performs ontology processing on the sensor data and the second sensor metadata to identify changes in the second sensor metadata; overwrite at least a portion of the improved sensor data with the updated improved sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata; and generating one or more commands to control one or more operations of one or more assets associated with the sensor; and transmitting one or more control commands to a control system of the one or more assets to adjust the one or more operations of the one or more assets in real time
Paulson; Erik S (US 20220137569 A1) teaches, receiving, via a user interface, second sensor metadata during a second time period (Paragraph [0081] discloses user input/ feedback for sensor metadata during second period of time. Also see Paragraphs [0093], [0114]);
overwrite at least a portion of the improved sensor data with the updated improved sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata (Paragraph [0117] discloses, overwriting/ filling the gap in the existing graph with the updated sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata. Also see Paragraph [0087], [0093]);
and generating one or more commands to control one or more operations of one or more assets associated with the sensor (Paragraph [0088] discloses generating commands to control the operations of the assets associated with the sensor. Also see Paragraphs [0015], [0047], [0053]).
and transmitting one or more control commands to a control system of the one or more assets to adjust the one or more operations of the one or more assets in real time (Paragraph [0022], [0024] associating the sensor data with the one or more asset nodes includes dynamically controlling an environmental variable of the building, monitoring sensor measurements, and associating the sensor data based on the monitoring (i.e., based on changed reading the adjusting/ controlling operations). Also see [0053]).
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al and LEE et al by overwrite at least a portion of the improved sensor data with the updated improved sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata; and generating one or more commands to control one or more operations of one or more assets associated with the sensor; and transmitting one or more control commands to a control system of the one or more assets to adjust the one or more operations of the one or more assets in real time, as taught by LEE et al (Paragraph [0037]).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, would determine improved and/or optimal control actions for building subsystems 120 based on the inputs, generate control signals based on the improved and/or optimal control actions, and provide the generated control signals to building subsystems 120 as taught by Paulson et al (Paragraph [0059], [0070]).
Sayfan et al, LEE et al and Paulson et al fails to explicitly teach, wherein the second sensor data processing unit performs ontology processing on the sensor data and the second sensor metadata to identify changes in the second sensor metadata.
DEY; Sounak (US 20150261863 A1) teaches, wherein the second sensor data processing unit performs ontology processing on the sensor data and the second sensor metadata to identify changes in the second sensor metadata (Fig. 4, Paragraph [0055] sensor ontology defining a relationship between the sensor data, the metadata, and the sensor information may be created…. Further, the sensor ontology created may be stored in the data store 220 in form of a knowledge repository (i.e., identifying the changes in sensor metadata by performing the sensor ontology which is stored in knowledge repository). Also see [0042]).
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al, LEE et al and Paulson et al by providing wherein the second sensor data processing unit performs ontology processing on the sensor data and the second sensor metadata to identify changes in the second sensor metadata, as taught by DEY et al (Paragraph [0055]).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, the sensor and sensing service discovery service may be configured to query the sensor in order to obtain information about factsheet, metadata, and capabilities of the sensor and thereby ensuing reliability of the sensor data. The sensor and sensing service discovery service may help the user 104 to identify the right sensors and their capability using the knowledge repository 308 storing interrelations among entities associated with the sensors and using a defined set of rules for quantitative reasoning for a given use case requirement of the user 104 as taught by DEY et al (Paragraph [0033]).
Sayfan et al, LEE et al and Paulson et al and DEY et al fails to explicitly teach, wherein the routing comprises applying an ingestion specification stored in a memory to the updated improved sensor data for determining routing destinations, and wherein the ingestion specification defines routing rules based on the first sensor metadata and the second sensor metadata.
Estrada; Adam (US 11961172 B1) teaches, wherein the routing comprises applying an ingestion specification stored in a memory to the updated improved sensor data for determining routing destinations, and wherein the ingestion specification defines routing rules based on the first sensor metadata and the second sensor metadata (Col 6, Lines 39- 54 sensor data needs to be routed to different destination systems or databases based on specific criteria. Data ingestor 120 may make decisions on where to route data based on predefined rules or conditions)
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al, LEE et al and Paulson et al and DEY et al by providing wherein the routing comprises applying an ingestion specification stored in a memory to the updated improved sensor data for determining routing destinations, and wherein the ingestion specification defines routing rules based on the first sensor metadata and the second sensor metadata, as taught by Estrada et al (Col 6, Lines 39- 54]).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, data ingestor can be designed to scale and handle large data loads efficiently without impacting platform 100 performance as taught by Estrada et al (Col 6, Lines 61-63).
Regarding dependent claim 8, Sayfan et al, LEE et al, Paulson et al, DEY et al and Estrada et al teach, the computer-implemented method of claim 1.
Sayfan et al further teaches, wherein the second database is a time series database (Paragraph [0045], [0046] the sensor data aggregator 112 performs sensor data aggregation at one or more low aggregation levels. For example, raw sensor data may be received from the sensors in the field on a 1-second interval and processed by the sensor data converter 154 at the 1-second interval. The sensor data aggregator 156 may aggregate the calibrated sensor data for each sensor over one or more low-level time intervals, such as a 1-minute interval and/or a 5-minute interval. In the present description, aggregation of sensor data of a sensor over a given time interval refers to averaging all of the sensor data of a sensor belonging to that time interval. In one example, when sensor data from a sensor is received on a 1-second interval, 1-minute sensor data may be generated by aggregating or averaging all the 1-second sensor data during each 1 minute interval. With aggregated sensor data thus generated at one or more low aggregation levels, the sensor data aggregator 112 can perform high-level sensor data aggregation using the low-level aggregated sensor data stored in the sensor data database 108. For example, 10-minute sensor data may be generated by aggregating or averaging the 1-minute sensor data during each 10 minute interval. In another example, 1-hour aggregated sensor data can be generated from the aggregated 10-minute data for the previous hour) (second database is taught by Lee et al Paragraph [0037]).
Regarding dependent claim 9, Sayfan et al, LEE et al, Paulson et al, DEY et al and Estrada et al teach, the computer-implemented method of claim 1.
Sayfan et al further teaches, wherein generating the improved sensor data occurs in real-time (Paragraph [0023] In embodiments of the present invention, the centralized backend system 102 implements the sensor data processing system and method to handle the large amount of incoming real-time sensor data arriving in real-time (Examiner interprets improved sensor data as processed raw sensor data)).
Regarding dependent claim 10, Sayfan et al, LEE et al, Paulson et al, DEY et al and Estrada et al teach, the computer-implemented method of claim 1.
Sayfan et al further teaches, further comprising: receiving second sensor data from the sensor during the second time period; and generating second improved sensor data, wherein generating the second improved sensor data comprises processing the second sensor data in the first sensor data processing unit based at least in part on the second sensor metadata (Paragraph [0044] the sensor data processing system 102 includes a database (dB) factory 110 which queries the sensor metadata database 106 periodically for changes in any of the metadata tables. When a change in a metadata table is detected, the dB factory 110 sends instructions to the sensor data database 108 to create new data tables or to reconfigure the data tables in accordance with the detected changes in the metadata table. As thus constructed, any additive changes to the sensor data database 108 can be realized by merely making the change to the sensor metadata database 106. The sensor data database 108 can thus be readily reconfigured to accommodate changes in the distributed sensor system, such as to add a new sensor, new sensor type, a new geographic location or a new floor plan of an indoor structure (Examiner interprets receiving second sensor metadata as identifying a change in the sensor metadata periodically/ at a second time period). In embodiments of the present invention, the database factory 110 is a software process being executed on a processor).
Regarding independent claim 11, Sayfan et al teaches, an apparatus comprising at least one processor and at least one memory coupled to the at least one processor, wherein the at least one processor (Paragraph [0011]) is configured to: receive sensor data from a sensor connected to one or more assets during a first time period (Paragraph [0033] a Period timestamp may be used to indicate the time period in which the sensor readings are generated. Also see Paragraph [0035]);
generate improved sensor data, wherein generating the improved sensor data comprises processing the sensor data in a first sensor data processing unit based at least in part on first sensor metadata (Paragraphs [0040], [0041] The sensor data processing system 102 processes the sensor data messages using the sensor metadata information stored in the sensor metadata database 106. More specifically, the sensor metadata information includes identifying information for each sensor, such as the sensor identifier and the associated sensor type. The metadata information further includes calibration data associated with each sensor. The data processor 104 processes the raw sensor data in the generically defined data fields in the sensor data message using the metadata information to apply the correct conversion for the sensor data type and to apply the corresponding calibration data for that particular sensor to the sensor data (Examiner interprets processing of raw sensor data/ correct conversion as improved sensor data));
routing the sensor data to a database and the improved sensor data to a database (Paragraph [0037] Returning to FIG. 2, the sensor data processing system 102 includes the message queue 103 for receiving and storing incoming sensor messages, the data processor 104 for processing the sensor messages, the sensor data database 108 for storing raw and processed sensor data. Also see Paragraph [0025] The calibrated sensor data may also be stored in the sensor data database 108 (Examiner interprets calibrated sensor data as improved sensor data (LEE et al teaches first and second database (Paragraph [0037])).
receiving, via a user interface, receive second sensor metadata during a second time period (Paragraph [0044] the sensor data processing system 102 includes a database (dB) factory 110 which queries the sensor metadata database 106 periodically for changes in any of the metadata tables. When a change in a metadata table is detected, the dB factory 110 sends instructions to the sensor data database 108 to create new data tables or to reconfigure the data tables in accordance with the detected changes in the metadata table. As thus constructed, any additive changes to the sensor data database 108 can be realized by merely making the change to the sensor metadata database 106. The sensor data database 108 can thus be readily reconfigured to accommodate changes in the distributed sensor system, such as to add a new sensor, new sensor type, a new geographic location or a new floor plan of an indoor structure (Examiner interprets receiving second sensor metadata as identifying a change in the sensor metadata periodically/ as a second time period). In embodiments of the present invention, the database factory 110 is a software process being executed on a processor);
retrieve the sensor data from the first database; generate updated improved sensor data, wherein generating the updated improved sensor data comprises processing the sensor data in a second sensor data processing unit based at least in part on the second sensor metadata; and routing the updated improved sensor data to the database (Paragraph [0025], [0027] when calibration data for a sensor is found to be inaccurate later on and new calibration data is generated (i.e., identifying that the sensor metadata has changed), the centralized backend system may regenerate the calibrated sensor data by retrieving the raw sensor data for that sensor and calibrating the raw sensor data again using updated calibration data. In this manner, historic sensor data can be corrected if the calibration data used was found to be inaccurate (i.e., generating updated improved sensor data/ corrected sensor data based on the updated metadata and sending the new calibrated data to the sensor data database) (second database is taught by LEE (Paragraph [0037].
Sayfan et al fails to explicitly teach, first database and second database; wherein the second sensor data processing unit performs ontology processing on the sensor data and the second sensor metadata to identify changes in the second sensor metadata; to overwrite at least a portion of the improved sensor data with the updated improved sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata; and generating one or more commands to control one or more operations of one or more assets associated with the sensor; and transmitting one or more control commands to a control system of the one or more assets to adjust the one or more operations of the one or more assets in real time.
LEE; Kwang-hyeon (US 20110071365 A1) teaches, routing the raw data to a first database and the processed data to a second database (Paragraph [0037] the first database 131 stores raw data of the pieces of blood glucose information and raw data of blood glucose management information corresponding to the pieces of blood glucose information, and the second database 132 stores data obtained by processing, e.g., by referring to the raw data stored in the first database 131. The processed data stored in the second database 132 is prepared by processing data to include the content of the blood glucose data stored in the first database 131);
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al by routing the sensor data to a first database and the improved sensor data to a second database; and routing the updated improved sensor data to the second database, as taught by LEE et al (Paragraph [0037]).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, when calibration data for a sensor is found to be inaccurate later on and new calibration data is generated, the centralized backend system may regenerate the calibrated sensor data by retrieving the raw sensor data for that sensor and calibrating the raw sensor data again using updated calibration data. In this manner, historic sensor data can be corrected if the calibration data used was found to be inaccurate, as taught by LEE et al (Paragraph [0027]).
Sayfan et al and LEE et al fails to explicitly teach, wherein the second sensor data processing unit performs ontology processing on the sensor data and the second sensor metadata to identify changes in the second sensor metadata; overwrite at least a portion of the improved sensor data with the updated improved sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata; and generating one or more commands to control one or more operations of one or more assets associated with the sensor; and transmitting one or more control commands to a control system of the one or more assets to adjust the one or more operations of the one or more assets in real time
Paulson; Erik S (US 20220137569 A1) teaches, receiving, via a user interface, second sensor metadata during a second time period (Paragraph [0081] discloses user input/ feedback for sensor metadata during second period of time. Also see Paragraphs [0093], [0114]);
overwrite at least a portion of the improved sensor data with the updated improved sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata (Paragraph [0117] discloses, overwriting/ filling the gap in the existing graph with the updated sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata. Also see Paragraph [0087], [0093]);
and generating one or more commands to control one or more operations of one or more assets associated with the sensor (Paragraph [0088] discloses generating commands to control the operations of the assets associated with the sensor. Also see Paragraphs [0015], [0047], [0053]).
and transmitting one or more control commands to a control system of the one or more assets to adjust the one or more operations of the one or more assets in real time (Paragraph [0022], [0024] associating the sensor data with the one or more asset nodes includes dynamically controlling an environmental variable of the building, monitoring sensor measurements, and associating the sensor data based on the monitoring (i.e., based on changed reading the adjusting/ controlling operations). Also see [0053]).
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al and LEE et al by overwrite at least a portion of the improved sensor data with the updated improved sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata; and generating one or more commands to control one or more operations of one or more assets associated with the sensor; and transmitting one or more control commands to a control system of the one or more assets to adjust the one or more operations of the one or more assets in real time, as taught by LEE et al (Paragraph [0037]).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, would determine improved and/or optimal control actions for building subsystems 120 based on the inputs, generate control signals based on the improved and/or optimal control actions, and provide the generated control signals to building subsystems 120 as taught by Paulson et al (Paragraph [0059], [0070]).
Sayfan et al, LEE et al and Paulson et al fails to explicitly teach, wherein the second sensor data processing unit performs ontology processing on the sensor data and the second sensor metadata to identify changes in the second sensor metadata.
DEY; Sounak (US 20150261863 A1) teaches, wherein the second sensor data processing unit performs ontology processing on the sensor data and the second sensor metadata to identify changes in the second sensor metadata (Fig. 4, Paragraph [0055] sensor ontology defining a relationship between the sensor data, the metadata, and the sensor information may be created…. Further, the sensor ontology created may be stored in the data store 220 in form of a knowledge repository (i.e., identifying the changes in sensor metadata by performing the sensor ontology which is stored in knowledge repository). Also see [0042]).
Sayfan et al, LEE et al and Paulson et al and DEY et al fails to explicitly teach, wherein the routing comprises applying an ingestion specification stored in a memory to the updated improved sensor data for determining routing destinations, and wherein the ingestion specification defines routing rules based on the first sensor metadata and the second sensor metadata.
Estrada; Adam (US 11961172 B1) teaches, wherein the routing comprises applying an ingestion specification stored in a memory to the updated improved sensor data for determining routing destinations, and wherein the ingestion specification defines routing rules based on the first sensor metadata and the second sensor metadata (Col 6, Lines 39- 54 sensor data needs to be routed to different destination systems or databases based on specific criteria. Data ingestor 120 may make decisions on where to route data based on predefined rules or conditions)
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al, LEE et al and Paulson et al and DEY et al by providing wherein the routing comprises applying an ingestion specification stored in a memory to the updated improved sensor data for determining routing destinations, and wherein the ingestion specification defines routing rules based on the first sensor metadata and the second sensor metadata, as taught by Estrada et al (Col 6, Lines 39- 54]).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, data ingestor can be designed to scale and handle large data loads efficiently without impacting platform 100 performance as taught by Estrada et al (Col 6, Lines 61-63).
Regarding dependent claim 18, Sayfan et al, LEE et al, Paulson et al, DEY et al and Estrada et al teach, the apparatus of claim 11.
Sayfan et al further teaches, wherein the second database is a time series database (Paragraph [0045], [0046] the sensor data aggregator 112 performs sensor data aggregation at one or more low aggregation levels. For example, raw sensor data may be received from the sensors in the field on a 1-second interval and processed by the sensor data converter 154 at the 1-second interval. The sensor data aggregator 156 may aggregate the calibrated sensor data for each sensor over one or more low-level time intervals, such as a 1-minute interval and/or a 5-minute interval. In the present description, aggregation of sensor data of a sensor over a given time interval refers to averaging all of the sensor data of a sensor belonging to that time interval. In one example, when sensor data from a sensor is received on a 1-second interval, 1-minute sensor data may be generated by aggregating or averaging all the 1-second sensor data during each 1 minute interval. With aggregated sensor data thus generated at one or more low aggregation levels, the sensor data aggregator 112 can perform high-level sensor data aggregation using the low-level aggregated sensor data stored in the sensor data database 108. For example, 10-minute sensor data may be generated by aggregating or averaging the 1-minute sensor data during each 10 minute interval. In another example, 1-hour aggregated sensor data can be generated from the aggregated 10-minute data for the previous hour) (second database is taught by Lee et al Paragraph [0037]).
Regarding dependent claim 19, Sayfan et al, LEE et al, Paulson et al, DEY et al and Estrada et al teach, the apparatus of claim 11.
Sayfan et al further teaches, wherein the at least one processor is configured to: receive second sensor data from the sensor during the second time period; and generate second improved sensor data, wherein generating the second improved sensor data comprises processing the second sensor data in the first sensor data processing unit based at least in part on the second sensor metadata (Paragraph [0044] the sensor data processing system 102 includes a database (dB) factory 110 which queries the sensor metadata database 106 periodically for changes in any of the metadata tables. When a change in a metadata table is detected, the dB factory 110 sends instructions to the sensor data database 108 to create new data tables or to reconfigure the data tables in accordance with the detected changes in the metadata table. As thus constructed, any additive changes to the sensor data database 108 can be realized by merely making the change to the sensor metadata database 106. The sensor data database 108 can thus be readily reconfigured to accommodate changes in the distributed sensor system, such as to add a new sensor, new sensor type, a new geographic location or a new floor plan of an indoor structure (Examiner interprets receiving second sensor metadata as identifying a change in the sensor metadata periodically/ at a second time period). In embodiments of the present invention, the database factory 110 is a software process being executed on a processor).
Regarding independent claim 20, Sayfan et al teaches, a non-transitory computer-readable storage medium comprising computer program code for execution by one or more processors of a device, the computer program code configured to, when executed by the one or more processors (Paragraph [0011]), cause the device to: receive sensor data from a sensor connected to one or more assets during a first time period (Paragraph [0033] a Period timestamp may be used to indicate the time period in which the sensor readings are generated. Also see Paragraph [0035]);
generate improved sensor data, wherein generating the improved sensor data comprises processing the sensor data in a first sensor data processing unit based at least in part on first sensor metadata (Paragraphs [0040], [0041] The sensor data processing system 102 processes the sensor data messages using the sensor metadata information stored in the sensor metadata database 106. More specifically, the sensor metadata information includes identifying information for each sensor, such as the sensor identifier and the associated sensor type. The metadata information further includes calibration data associated with each sensor. The data processor 104 processes the raw sensor data in the generically defined data fields in the sensor data message using the metadata information to apply the correct conversion for the sensor data type and to apply the corresponding calibration data for that particular sensor to the sensor data (Examiner interprets processing of raw sensor data/ correct conversion as improved sensor data));
routing the sensor data to a database and the improved sensor data to a database (Paragraph [0037] Returning to FIG. 2, the sensor data processing system 102 includes the message queue 103 for receiving and storing incoming sensor messages, the data processor 104 for processing the sensor messages, the sensor data database 108 for storing raw and processed sensor data. Also see Paragraph [0025] The calibrated sensor data may also be stored in the sensor data database 108 (Examiner interprets calibrated sensor data as improved sensor data (LEE et al teaches first and second database (Paragraph [0037]));
receiving, via a user interface, receive second sensor metadata during a second time period (Paragraph [0044] the sensor data processing system 102 includes a database (dB) factory 110 which queries the sensor metadata database 106 periodically for changes in any of the metadata tables. When a change in a metadata table is detected, the dB factory 110 sends instructions to the sensor data database 108 to create new data tables or to reconfigure the data tables in accordance with the detected changes in the metadata table. As thus constructed, any additive changes to the sensor data database 108 can be realized by merely making the change to the sensor metadata database 106. The sensor data database 108 can thus be readily reconfigured to accommodate changes in the distributed sensor system, such as to add a new sensor, new sensor type, a new geographic location or a new floor plan of an indoor structure (Examiner interprets receiving second sensor metadata as identifying a change in the sensor metadata periodically/ as a second time period). In embodiments of the present invention, the database factory 110 is a software process being executed on a processor);
retrieve the sensor data from the first database; generate updated improved sensor data, wherein generating the updated improved sensor data comprises processing the sensor data in a second sensor data processing unit based at least in part on the second sensor metadata; and routing the updated improved sensor data to the database (Paragraph [0025], [0027] when calibration data for a sensor is found to be inaccurate later on and new calibration data is generated (i.e., identifying that the sensor metadata has changed), the centralized backend system may regenerate the calibrated sensor data by retrieving the raw sensor data for that sensor and calibrating the raw sensor data again using updated calibration data. In this manner, historic sensor data can be corrected if the calibration data used was found to be inaccurate (i.e., generating updated improved sensor data/ corrected sensor data based on the updated metadata and sending the new calibrated data to the sensor data database) (second database is taught by LEE (Paragraph [0037].
Sayfan et al fails to explicitly teach, first database and second database; wherein the second sensor data processing unit performs ontology processing on the sensor data and the second sensor metadata to identify changes in the second sensor metadata; to overwrite at least a portion of the improved sensor data with the updated improved sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata; and generating one or more commands to control one or more operations of one or more assets associated with the sensor; transmit one or more control commands to a control system of the one or more assets to adjust the one or more operations of the one or more assets in real time
LEE; Kwang-hyeon (US 20110071365 A1) teaches, routing the raw data to a first database and the processed data to a second database (Paragraph [0037] the first database 131 stores raw data of the pieces of blood glucose information and raw data of blood glucose management information corresponding to the pieces of blood glucose information, and the second database 132 stores data obtained by processing, e.g., by referring to the raw data stored in the first database 131. The processed data stored in the second database 132 is prepared by processing data to include the content of the blood glucose data stored in the first database 131);
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al by routing the sensor data to a first database and the improved sensor data to a second database; and routing the updated improved sensor data to the second database, as taught by LEE et al (Paragraph [0037]).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, when calibration data for a sensor is found to be inaccurate later on and new calibration data is generated, the centralized backend system may regenerate the calibrated sensor data by retrieving the raw sensor data for that sensor and calibrating the raw sensor data again using updated calibration data. In this manner, historic sensor data can be corrected if the calibration data used was found to be inaccurate, as taught by LEE et al (Paragraph [0027]).
Sayfan et al and LEE et al fails to explicitly teach, wherein the second sensor data processing unit performs ontology processing on the sensor data and the second sensor metadata to identify changes in the second sensor metadata; overwrite at least a portion of the improved sensor data with the updated improved sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata; and generating one or more commands to control one or more operations of one or more assets associated with the sensor; transmit one or more control commands to a control system of the one or more assets to adjust the one or more operations of the one or more assets in real time
Paulson; Erik S (US 20220137569 A1) teaches, receiving, via a user interface, second sensor metadata during a second time period (Paragraph [0081] discloses user input/ feedback for sensor metadata during second period of time. Also see Paragraphs [0093], [0114]);
overwrite at least a portion of the improved sensor data with the updated improved sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata (Paragraph [0117] discloses, overwriting/ filling the gap in the existing graph with the updated sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata. Also see Paragraph [0087], [0093]);
and generating one or more commands to control one or more operations of one or more assets associated with the sensor (Paragraph [0088] discloses generating commands to control the operations of the assets associated with the sensor. Also see Paragraphs [0015], [0047], [0053]). and transmitting one or more control commands to a control system of the one or more assets to adjust the one or more operations of the one or more assets in real time (Paragraph [0022], [0024] associating the sensor data with the one or more asset nodes includes dynamically controlling an environmental variable of the building, monitoring sensor measurements, and associating the sensor data based on the monitoring (i.e., based on changed reading the adjusting/ controlling operations). Also see [0053]).
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al and LEE et al by overwrite at least a portion of the improved sensor data with the updated improved sensor data in response to determining that at least a first configuration of the sensor indicated in the first sensor metadata is different from a second configuration of the sensor indicated in the second sensor metadata; and generating one or more commands to control one or more operations of one or more assets associated with the sensor; and transmitting one or more control commands to a control system of the one or more assets to adjust the one or more operations of the one or more assets in real time, as taught by LEE et al (Paragraph [0037]).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, would determine improved and/or optimal control actions for building subsystems 120 based on the inputs, generate control signals based on the improved and/or optimal control actions, and provide the generated control signals to building subsystems 120 as taught by Paulson et al (Paragraph [0059], [0070]).
Sayfan et al, LEE et al and Paulson et al fails to explicitly teach, wherein the second sensor data processing unit performs ontology processing on the sensor data and the second sensor metadata to identify changes in the second sensor metadata.
DEY; Sounak (US 20150261863 A1) teaches, wherein the second sensor data processing unit performs ontology processing on the sensor data and the second sensor metadata to identify changes in the second sensor metadata (Fig. 4, Paragraph [0055] sensor ontology defining a relationship between the sensor data, the metadata, and the sensor information may be created…. Further, the sensor ontology created may be stored in the data store 220 in form of a knowledge repository (i.e., identifying the changes in sensor metadata by performing the sensor ontology which is stored in knowledge repository). Also see [0042]).
Sayfan et al, LEE et al and Paulson et al and DEY et al fails to explicitly teach, wherein the routing comprises applying an ingestion specification stored in a memory to the updated improved sensor data for determining routing destinations, and wherein the ingestion specification defines routing rules based on the first sensor metadata and the second sensor metadata.
Estrada; Adam (US 11961172 B1) teaches, wherein the routing comprises applying an ingestion specification stored in a memory to the updated improved sensor data for determining routing destinations, and wherein the ingestion specification defines routing rules based on the first sensor metadata and the second sensor metadata (Col 6, Lines 39- 54 sensor data needs to be routed to different destination systems or databases based on specific criteria. Data ingestor 120 may make decisions on where to route data based on predefined rules or conditions)
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al, LEE et al and Paulson et al and DEY et al by providing wherein the routing comprises applying an ingestion specification stored in a memory to the updated improved sensor data for determining routing destinations, and wherein the ingestion specification defines routing rules based on the first sensor metadata and the second sensor metadata, as taught by Estrada et al (Col 6, Lines 39- 54]).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, data ingestor can be designed to scale and handle large data loads efficiently without impacting platform 100 performance as taught by Estrada et al (Col 6, Lines 61-63).
8. Claims 2, 3 12 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Sayfan; Gigi (US 20160370338 A1) in view of LEE; Kwang-hyeon (US 20110071365 A1), Paulson; Erik S (US 20220137569 A1), DEY; Sounak (US 20150261863 A1), Estrada; Adam (US 11961172 B1) and in further view of and in further view of Conradi; Christian (US 20230401191 A1).
Regarding dependent claim 2, Sayfan et al, LEE et al, Paulson et al, DEY et al and Estrada et al teach, the computer-implemented method of claim 1.
Sayfan et al further teaches, wherein the improved sensor data is routed to a second database (Paragraph [0028]);
Sayfan et al, LEE et al, Paulson et al and DEY et al fails to explicitly teach, first container.
Conradi; Christian (US 20230401191 A1) discloses wherein the improved sensor data is routed to a first container (Paragraphs [0057]-[0060] sensor data is routed/stored to/in first container based on the data type).
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al, LEE et al, Paulson et al and DEY et al wherein the improved sensor data is routed to a first container, as taught by Conradi et al (Paragraphs [0057]-[0060]).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, retrieval of sensor data from the sensor data table can be targeted such that only requested sensor data is returned. Such feature represents an improvement in both operating efficiency (e.g., data transmission) and memory usage compared to the conventional BLOB approach which can incur additional overhead or waste by returning unneeded/unrequested sensor data as taught by Conradi et al (Paragraph [0133], [0150]).
Regarding dependent claim 3, Sayfan et al, LEE et al, Paulson et al, DEY et al, Estrada et al and Conradi et al teach, the computer-implemented method of claim 2.
Sayfan et al teaches, wherein the updated improved sensor data is routed to a second database (Paragraph [0028]).
Conradi further discloses wherein the improved sensor data is routed to a second container (Paragraphs [0057]-[0060] sensor data is routed/stored to/in second container based on the data type).
Regarding dependent claim 12, Sayfan et al, LEE et al, Paulson et al, DEY et al and Estrada et al teach, the apparatus of claim 11.
Sayfan et al further teaches, wherein the improved sensor data is routed to a second database (Paragraph [0028]);
Sayfan et al, LEE et al and Paulson et al fails to explicitly teach, first container.
Conradi; Christian (US 20230401191 A1) discloses wherein the improved sensor data is routed to a first container (Paragraphs [0057]-[0060] sensor data is routed/stored to/in first container based on the data type).
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al, LEE et al, Paulson et al and DEY et al wherein the improved sensor data is routed to a first container, as taught by Conradi et al (Paragraphs [0057]-[0060]).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, retrieval of sensor data from the sensor data table can be targeted such that only requested sensor data is returned. Such feature represents an improvement in both operating efficiency (e.g., data transmission) and memory usage compared to the conventional BLOB approach which can incur additional overhead or waste by returning unneeded/unrequested sensor data as taught by Conradi et al (Paragraph [0133], [0150]).
Regarding dependent claim 13, Sayfan et al, LEE et al, Paulson et al, DEY et al, Estrada et al and Conradi et al teach, the apparatus of claim 12.
Sayfan et al teaches, wherein the updated improved sensor data is routed to a second database (Paragraph [0028]).
Conradi further discloses wherein the improved sensor data is routed to a second container (Paragraphs [0057]-[0060] sensor data is routed/stored to/in second container based on the data type).
9. Claims 4 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Sayfan; Gigi (US 20160370338 A1) in view of LEE; Kwang-hyeon (US 20110071365 A1), Paulson; Erik S (US 20220137569 A1), DEY; Sounak (US 20150261863 A1), Estrada; Adam (US 11961172 B1), Conradi; Christian (US 20230401191 A1) and in further view of Deligia; Agostino (US 20180253344 A1).
Regarding dependent claim 4, Sayfan et al, LEE et al, Paulson et al, DEY et al, Estrada et al and Conradi et al teach, the computer-implemented method of claim 3.
Sayfan et al, LEE et al, Paulson et al, DEY et al, Estrada et al and Conradi et al fails to explicitly teach, further comprising: generating ingestion specification, wherein the ingestion specification is configured to instruct the second database to overwrite at least a portion of the improved sensor data in the first container with at least a portion of the updated improved sensor data in the second container; and transmitting the ingestion specification to the second database.
Deligia; Agostino (US 20180253344 A1) teaches, further comprising: generating an ingestion specification, wherein the ingestion specification is configured to instruct the second database to overwrite at least a portion of the improved sensor data in the first container with at least a portion of the updated improved sensor data in the second container; and transmitting the ingestion specification to the second database (Paragraph [0048] discloses generating ingestion specification based on updated metadata and overwriting portion of the previous data with the updated data. Containers are taught by Conradi et al and databases are taught by Sayfan et al. Therefore combined together Sayfan et al, Conradi et al and Deligia et al teach the entire claim).
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al, LEE et al, Paulson et al, DEY et al and Conradi et al generating an ingestion specification, wherein the ingestion specification is configured to instruct the second database to overwrite at least a portion of the improved sensor data in the first container with at least a portion of the updated improved sensor data in the second container; and transmitting the ingestion specification to the second database, as taught by Deligia et al (Paragraph [0048]).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, the asynchronous and synchronous processes can be used independently or in conjunction—provided by ingestion pipeline 420 is not available or possible in data processing systems that employ only asynchronous ingestion pipelines. The ability of ingestion pipeline 420 to ingest and process data in a synchronous manner (in addition to asynchronously) advantageously allows for a more flexible workflow, allowing clients to customize data processing based on their individual needs and get results back.as taught by Deligia et al (Paragraph [0116]).
Regarding dependent claim 14, Sayfan et al, LEE et al, Paulson et al, DEY et al, Estrada et al and Conradi et al teach, the apparatus of claim 13.
Sayfan et al, LEE et al, Paulson et al, DEY et al and Conradi et al fails to explicitly teach, wherein the at least one processor is configured to: generate ingestion specification, wherein the ingestion specification is configured to instruct the second database to overwrite at least a portion of the improved sensor data in the first container with at least a portion of the updated improved sensor data in the second container; and transmit the ingestion specification to the second database.
Deligia; Agostino (US 20180253344 A1) teaches, further comprising: generating an ingestion specification, wherein the ingestion specification is configured to instruct the second database to overwrite at least a portion of the improved sensor data in the first container with at least a portion of the updated improved sensor data in the second container; and transmitting the ingestion specification to the second database (Paragraph [0048] discloses generating ingestion specification based on updated metadata and overwriting portion of the previous data with the updated data. Containers are taught by Conradi et al and databases are taught by Sayfan et al. Therefore combined together Sayfan et al, Conradi et al and Deligia et al teach the entire claim).
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al, LEE et al, Paulson et al, DEY et al and Conradi et al generating an ingestion specification, wherein the ingestion specification is configured to instruct the second database to overwrite at least a portion of the improved sensor data in the first container with at least a portion of the updated improved sensor data in the second container; and transmitting the ingestion specification to the second database, as taught by Deligia et al (Paragraph [0048]).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, the asynchronous and synchronous processes can be used independently or in conjunction—provided by ingestion pipeline 420 is not available or possible in data processing systems that employ only asynchronous ingestion pipelines. The ability of ingestion pipeline 420 to ingest and process data in a synchronous manner (in addition to asynchronously) advantageously allows for a more flexible workflow, allowing clients to customize data processing based on their individual needs and get results back.as taught by Deligia et al (Paragraph [0116]).
10. Claims 5-7 and 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over Sayfan; Gigi (US 20160370338 A1) in view of LEE; Kwang-hyeon (US 20110071365 A1), Paulson; Erik S (US 20220137569 A1), DEY; Sounak (US 20150261863 A1), Estrada; Adam (US 11961172 B1) and in further view of JAS; Frank (US 20200295879 A1).
Regarding dependent claim 5, Sayfan et al, LEE et al, Paulson et al, DEY et al and Estrada et al teach, the computer-implemented method of claim 1.
Sayfan et al, LEE et al, Paulson et al, DEY et al and Estrada et al fails to explicitly teach, wherein the first sensor data processing unit comprises at least one of first ontology circuitry, first normalization circuitry, or first interpolation circuitry and the second sensor data processing unit comprises at least one of second ontology circuitry, second normalization circuitry, or second interpolation circuitry.
JAS; Frank (US 20200295879 A1) teaches, wherein the first sensor data processing unit comprises at least one of first ontology circuitry, first normalization circuitry, or first interpolation circuitry and the second sensor data processing unit comprises at least one of second ontology circuitry, second normalization circuitry, or second interpolation circuitry (Paragraph [0004], Abstract a device may receive a first telemetry data entry associated with an attribute and store a record associated with the first telemetry data entry, wherein the record identifies a first context value associated with the attribute (Examiner interprets ontology as context). The device may log a first timestamp of the first telemetry data entry in a lookup table, wherein the lookup table includes a mapping of the attribute to the first context value and to the first timestamp. The device may receive a second telemetry data entry associated with the attribute and may determine, from the mapping, that the second telemetry data entry is associated with a second context value that is different from the first context value. The device may determine whether a second timestamp, of the second telemetry data entry, is before the first timestamp. The device may perform an action based on whether the second timestamp is before the first timestamp).
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al, LEE et al, Paulson et al, DEY et al and Estrada et al, wherein the first sensor data processing unit comprises at least one of first ontology circuitry, first normalization circuitry, or first interpolation circuitry and the second sensor data processing unit comprises at least one of second ontology circuitry, second normalization circuitry, or second interpolation circuitry, as taught by JAS et al (Paragraph [0004], Abstract).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, the network device may quickly (e.g., as soon as the context entry is received rather than after detecting the error due to one or more other prolonged processes, such as batch processing, and/or the like) and efficiently detect and/or indicate that one or more event records is erroneous to permit the event records to be addressed (e.g., flagged, erased, corrected, and/or the like). Accordingly, computing resources and/or network resources associated with analyzing and/or relying on inaccurate or erroneous event records may be conserved as taught by JAS et al (Paragraph [0012]).
Regarding dependent claim 6, Sayfan et al, LEE et al, Paulson et al, DEY et al, Estrada et al and JAS et al teach, the computer-implemented method of claim 5.
JAS et al further teaches, wherein the first ontology circuitry is configured to associate the first sensor metadata with the sensor data (Paragraph [0004], Abstract a device may receive a first telemetry data entry associated with an attribute and store a record associated with the first telemetry data entry, wherein the record identifies a first context value associated with the attribute. The device may log a first timestamp of the first telemetry data entry in a lookup table, wherein the lookup table includes a mapping of the attribute to the first context value and to the first timestamp).
Regarding dependent claim 7, Sayfan et al, LEE et al, Paulson et al, DEY et al, Estrada et al and JAS et al teach, the computer-implemented method of claim 5.
JAS et al further teaches, wherein the second ontology circuitry is configured to associate the second sensor metadata with the sensor data (Paragraph [0004], Abstract the device may receive a second telemetry data entry associated with the attribute and may determine, from the mapping, that the second telemetry data entry is associated with a second context value that is different from the first context value).
Regarding dependent claim 15, Sayfan et al, LEE et al, Paulson et al, DEY et al and Estrada et al teach, the apparatus of claim 11.
Sayfan et al, LEE et al, Paulson et al, DEY et al and Estrada et al fails to explicitly teach, wherein the first sensor data processing unit comprises at least one of first ontology circuitry, first normalization circuitry, or first interpolation circuitry and the second sensor data processing unit comprises at least one of second ontology circuitry, second normalization circuitry, or second interpolation circuitry.
JAS; Frank (US 20200295879 A1) teaches, wherein the first sensor data processing unit comprises at least one of first ontology circuitry, first normalization circuitry, or first interpolation circuitry and the second sensor data processing unit comprises at least one of second ontology circuitry, second normalization circuitry, or second interpolation circuitry (Paragraph [0004], Abstract a device may receive a first telemetry data entry associated with an attribute and store a record associated with the first telemetry data entry, wherein the record identifies a first context value associated with the attribute (Examiner interprets ontology as context). The device may log a first timestamp of the first telemetry data entry in a lookup table, wherein the lookup table includes a mapping of the attribute to the first context value and to the first timestamp. The device may receive a second telemetry data entry associated with the attribute and may determine, from the mapping, that the second telemetry data entry is associated with a second context value that is different from the first context value. The device may determine whether a second timestamp, of the second telemetry data entry, is before the first timestamp. The device may perform an action based on whether the second timestamp is before the first timestamp).
Therefore it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention, to have modified the teachings of Sayfan et al, LEE et al, Paulson et al, DEY et al and Estrada et al wherein the first sensor data processing unit comprises at least one of first ontology circuitry, first normalization circuitry, or first interpolation circuitry and the second sensor data processing unit comprises at least one of second ontology circuitry, second normalization circuitry, or second interpolation circuitry, as taught by JAS et al (Paragraph [0004], Abstract).
One of the ordinary skill in the art would have been motivated to make this modification, by doing so, the network device may quickly (e.g., as soon as the context entry is received rather than after detecting the error due to one or more other prolonged processes, such as batch processing, and/or the like) and efficiently detect and/or indicate that one or more event records is erroneous to permit the event records to be addressed (e.g., flagged, erased, corrected, and/or the like). Accordingly, computing resources and/or network resources associated with analyzing and/or relying on inaccurate or erroneous event records may be conserved as taught by JAS et al (Paragraph [0012]).
Regarding dependent claim 16, Sayfan et al, LEE et al, Paulson et al, DEY et al, Estrada et al and JAS et al teach, the apparatus of claim 15.
JAS et al further teaches, wherein the first ontology circuitry is configured to associate the first sensor metadata with the sensor data (Paragraph [0004], Abstract a device may receive a first telemetry data entry associated with an attribute and store a record associated with the first telemetry data entry, wherein the record identifies a first context value associated with the attribute. The device may log a first timestamp of the first telemetry data entry in a lookup table, wherein the lookup table includes a mapping of the attribute to the first context value and to the first timestamp).
Regarding dependent claim 17, Sayfan et al, LEE et al, Paulson et al, DEY et al, Estrada et al and JAS et al teach, the apparatus of claim 15.
JAS et al further teaches, wherein the second ontology circuitry is configured to associate the second sensor metadata with the sensor data (Paragraph [0004], Abstract the device may receive a second telemetry data entry associated with the attribute and may determine, from the mapping, that the second telemetry data entry is associated with a second context value that is different from the first context value).
Closest Prior Art
11. The prior art made of record and not relied upon is considered pertinent to the applicant’s disclosure.
Kumar; Venki (US 20220327538 A1) teaches, [0093] The data collection and processing system 10 of the present invention can also employ an optional normalization module or unit 100 for normalizing the data received from either the data sources 12 or from the computing layer 18, as shown for example in FIG. 6).
12. Examiner has pointed out particular references contained in the prior arts of record in the body of this action for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and Figures may apply as well. It is respectfully requested from the applicant, in preparing the response, to consider fully the entire references as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior arts or disclosed by the examiner. It is noted that any citation to specific pages, columns, figures, or lines in the prior art references any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331-33, 216 USPQ 1038-39 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 USPQ 275, 277 (CCPA 1968))).
Conclusion
Applicant’s amendments/Arguments necessitated new grounds of rejection as presented in this office action. THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SUMAN RAJAPUTRA whose telephone number is (571) 272-4669. The examiner can normally be reached between 8:00 AM - 5:00 PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tony Mahmoudi (571) 272-4078 can be reached. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/S. R./
Examiner, Art Unit 2163
/ALEX GOFMAN/Primary Examiner, Art Unit 2163
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