Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Drawings
The drawings were received on 4/4/2024. These drawings are accepted.
Claim Objections
Claim 14 is objected to because of the following informalities: Claim 14 is grammatically incorrect. It fails to include a connective term such as “and”. Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea in the form of a mental process without significantly more. The claim(s) recite(s) gathering data such as “receiving data output by data sources …”, generating a summary of condition or predictors associated with performance metrics, receiving query via computer-based interface, transmission of the query and summary, receiving a response for the query and displaying the response. Such can be performed by a human mentally via pen and paper where data can be written on paper, analysis of the data can be performed mentally, summarization of the analysis with performance metrics can be performed mentally, using pen and paper, an interface to receive a query such as writing a question down on paper with a pen, and using the summarization and query, a response can be generated or receive via pen and paper with display of the response via pen and paper. The recited limitations also recite data sources of a manufacturing site. Such is merely recited to monitoring of manufacturing site, which can be performed by a human being via pen and paper to gather the data via observation or mental process of the manufacturing site. Although the claimed language recites “computer-based interface”, such is merely a generic device generated to perform reception of a query. This judicial exception is not integrated into a practical application because the recited claimed language is merely directed towards the judicial exception without positively recited language integrating the judicial exception into practical application. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the recited limitations are merely directed towards the abstract idea without positively recited language indicating significantly more than the judicial exception.
Claim 2 recites sensors monitoring process carried out at the manufacturing site and such sensors gather or collect data. Such limitation is merely directed towards generic device performing the abstract idea of gathering data.
Claim 3 recites language merely adding to the abstract idea including generic device such as machine learning model and does not include positively recited language integrating the abstract idea into practical application and/or indicating significantly more than the judicial exception.
Claim 4 recites language merely adding to the abstract idea with generic device of a chatbot and large language model and does not include positively recited language integrating the abstract idea into practical application and/or indicating significantly more than the judicial exception.
Claims 5-9,11-16 recites language merely adding to the abstract idea and does not include positively recited language integrating the abstract idea into practical application and/or indicating significantly more than the judicial exception.
Claim 10 recites language merely adding to the abstract idea with generic device of a memory and does not include positively recited language integrating the abstract idea into practical application and/or indicating significantly more than the judicial exception.
Claims 17-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea in the form of a mental process without significantly more. The claim(s) recite(s) gathering data such as “receiving data output by data sources …”, generating a summary of condition or predictors associated with performance metrics, receiving query via computer-based interface, transmission of the query and summary, receiving a response for the query and displaying the response. Such can be performed by a human mentally via pen and paper where data can be written on paper, analysis of the data can be performed mentally, summarization of the analysis with performance metrics can be performed mentally, using pen and paper, an interface to receive a query such as writing a question down on paper with a pen, and using the summarization and query, a response can be generated or receive via pen and paper with display of the response via pen and paper. The recited limitations also recite data sources of a manufacturing site. Such is merely recited to monitoring of manufacturing site, which can be performed by a human being via pen and paper to gather the data via observation or mental process of the manufacturing site. The recited limitations also recite memory, one or more processors and one or more programs, which are directed towards a generic device performing the judicial exception. Although the claimed language recites “computer-based interface”, such is merely a generic device generated to perform reception of a query. This judicial exception is not integrated into a practical application because the recited claimed language is merely directed towards the judicial exception without positively recited language integrating the judicial exception into practical application. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the recited limitations are merely directed towards the abstract idea without positively recited language indicating significantly more than the judicial exception.
Claim 18 recites language merely adding to the abstract idea and does not include positively recited language integrating the abstract idea into practical application and/or indicating significantly more than the judicial exception.
Claims 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea in the form of a mental process without significantly more. The claim(s) recite(s) gathering data such as “receiving data output by data sources …”, generating a summary of condition or predictors associated with performance metrics, receiving query via computer-based interface, transmission of the query and summary, receiving a response for the query and displaying the response. Such can be performed by a human mentally via pen and paper where data can be written on paper, analysis of the data can be performed mentally, summarization of the analysis with performance metrics can be performed mentally, using pen and paper, an interface to receive a query such as writing a question down on paper with a pen, and using the summarization and query, a response can be generated or receive via pen and paper with display of the response via pen and paper. The recited limitations also recite data sources of a manufacturing site. Such is merely recited to monitoring of manufacturing site, which can be performed by a human being via pen and paper to gather the data via observation or mental process of the manufacturing site. The recited limitations also recite “a non-transitory computer readable storage medium storing one or more programs …”, which are directed towards a generic device performing the judicial exception. Although the claimed language recites “computer-based interface”, such is merely a generic device generated to perform reception of a query. This judicial exception is not integrated into a practical application because the recited claimed language is merely directed towards the judicial exception without positively recited language integrating the judicial exception into practical application. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the recited limitations are merely directed towards the abstract idea without positively recited language indicating significantly more than the judicial exception.
Claim 20 recites language merely adding to the abstract idea and does not include positively recited language integrating the abstract idea into practical application and/or indicating significantly more than the judicial exception.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-2,5-9,13,15-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sierhuis et al (US Publication No.: 20160180222) in view of Schuck (US Publication No.: 20230067083).
Claim 1, Sierhuis et al discloses
Receiving data output by data sources (Fig. 1, label sensors 300, paragraph 27 discloses “sensors 300, the person, agent or machine 200 …”. Paragraph 5 discloses “… provide responsive information to such machines, sensors, or other people or request certain actions to be taken by such machines, sensors, or other people.”);
determining, from the received data, one or more predictors having correlations with one or more performance metrics characterizing a process carried out by the machines (Paragraph 88 discloses analytics service predicts the violates the threshold for a user, Hank, wherein such prediction correlates to correlations with performance metrics such as comparison of the heart rate to the threshold resulting to a violation.);
generating one or more textual sentences describing the one or more predictors and the corresponding correlations (Paragraph 88 discloses analytics service predicts the violates the threshold for a user, Hank, wherein such prediction correlates to correlations with performance metrics such as comparison of the heart rate to the threshold resulting to a violation. The system outputs a violation message or summary of the violation. Paragraph 50 discloses analytics can include trend analysis, descriptive statistics, etc. which also indicates summary or textual sentence describing predictors.);
generating a computer-based interface for receiving a query requesting information describing the manufacturing site (Paragraph 54 discloses the user may ask questions to the intelligent personal agents in the agent service via the interaction service. Paragraph 53 discloses “The interaction service communicates with these various components within and external to the platform to pass data necessary between the components.” Such indicates generation of a computer-based interface to receive query requesting information.);
receiving the query (Paragraph 54 discloses user may ask questions to the intelligent personal agents via the interaction service which indicates reception of the query.);
in response to receiving the query, transmitting the query and the generated one or more textual sentences to a conversational agent (Fig. 3, label 120 outputs the analytics such as summary of the sensor data or textual sentences, and user 200,400 sends questions via the user interaction label 160 to label 140, via 120, 140, 130, etc.);
receiving, from the conversational agent, a response to the transmitted query (Fig. 3, label 400,200); and
displaying the response on the computer-based interface (Fig. 3, label 400).
Sierhuis et al fails to disclose the machines are at a manufacturing site.
Schuck et al discloses manufacturing plant with machines monitored by sensors and analysis of the data from the sensors (Fig. 1, label 122, 110 as the sensors at the manufacturing site or plant, label 118 as the analytics processing apparatus or risk processing apparatus. Fig. 2, label 118 is shown with probably assessor and analysis of overall plant risk.).
Sierhuis et al discloses sensors or machines (paragraph 5), and Schuck et al discloses monitoring manufacturing plants (Fig. 1, label 110). Both Sierhuis et al and Schuck et al discloses such monitoring fur the purpose of monitoring machines or sensors in areas such as healthcare, military, emergency response, planning, automotive, etc., where monitoring of machines in a manufacturing plant of Schuck et al is a similar area as disclosed by Seirhauis et al (paragraph 13). Hence, it would be obvious to one skilled in the art before the effective filing date of the application to modify Sierhuis et al’s monitoring system with chatbot to monitor machines in a manufacturing site as disclosed by Schuck et al in order to solve the same problem of monitoring the condition of machines for the purpose of determining the conditions of the machines, whether it be machines or sensors for healthcare as disclosed by Sierhuis et al or machines in a manufacturing plant as disclosed by Schuck et al so to improve provide services necessary for those using the monitored machines such as preventing health failure as disclosed by Sierhuis et al to provide emergency services when needed or failure of machines at a manufacturing plant as disclosed by Schuck et al to provide emergency services when needed.
Claim 2, Schuck et al the data sources include one or more sensors monitoring the process carried out at the manufacturing site (Fig. 1, label 110, 116,122,140), and wherein the data includes output of the one or more sensors (Fig. 1, label 122, 144,142a-142b).
Claim 5, Sierhuis et al wherein the query is a natural language query (paragraph 54 discloses “the user may ask questions to the intelligent personal agents…”. This indicates the query is a natural language query.), and wherein the response is a natural language response (Paragraph 82 discloses the intelligent personal agent generates answers such as trend and likelihood of meeting a predefined goal or plan to meet a defined goal. This indicates a natural language response.).
Claim 6, Schuck et al discloses wherein the predictors include one or more of a physical state associated with the process, or an environmental state of the manufacturing site (Paragraph 41 discloses sensors are located through the plan constantly or periodically record data. Paragraph 43 discloses examples of the different sensors and data received from the respective sensors. For example, a power sensor may be assigned to all devices of the plan measures the overall power draw by the plant’s devices. This indicates environmental state (power consumption) of the manufacturing site.).
Claim 7, Schuck et al discloses wherein the correlations include positive correlations between the one or more predictors and the one or more performance metrics, and negative correlations between the one or more predictors and the one or more performance metrics (Paragraph 88 discloses a correlation between the predictors such as heart rate compared to a threshold, and performance metrics such as over a threshold indicates violation. The heart rate indicates sensor data. Depending on whether the heart rate or sensor data compared to a threshold indicates violation or no violation, the correlations includes positive (no violation) and negative (violation).).
Claim 8, Sierhuis et al discloses wherein the predictors comprise one or more of the output of the data sources or a quantity determined from the output of the data sources (Paragraphs 50 discloses analytics generating predictors from sensor data. Paragraph 29 discloses sensors collect data such as physical sensors, virtual sensors and human services or computation services wherein a variety of devices or data sources have sensors to collect data. This indicates the predictors comprise one or more of the output of the data sources.).
Claim 9, Sierhuis et al discloses wherein the performance metrics comprise one or more of the output of the data sources or a quantity determined from the output of the data sources (Paragraph 50 discloses analytics and paragraph 42 discloses sensors may include software in which several measurements are processed together or where measurements or process parameters from one metric are used to calculate another metric …”. This indicates the performance metrics or analytics generated from the sensor data compare one or more output of the data sources or quantity determined from the output data sources such as device with sensors discussed in paragraph 29.).
Claim 13, Sierhuis et al discloses wherein the determining further comprises: determining the one or more predictors from the received data (Paragraph 88 discloses one or more predictors is determined from the sensor data such as heart rate.);
determining the one or more performance metrics at least in part from the received data (paragraph 88 discloses performance metrics or condition of the user via heart rate based on the sensor data or received data.); and
determining the correlations, the correlations being relationships between the determined one or more predictors and the determined one or more performance metrics (paragraph 88 discloses relationship (comparison result to violation/no violation) between the determined one or more predictors (comparison between heart rate and threshold) and the determined one or more performance metrics (violation/no violation).).
Claim 15, Sierhuis et al discloses wherein the transmitting the query (Fig. 3, label 120 outputs the analytics such as summary of the sensor data or textual sentences, and user 200,400 sends questions via the user interaction label 160 to label 140, via 120, 140, 130, etc.) further comprises, in response to receiving the query, transmitting the query, the generated one or more textual sentences, and at least a portion of the received data to the conversational agent (Fig. 3, label 400 as query receives via 160, 120 (analytics or generated one or more textual sentences),300,350 (sensor data or received data) is transmitted to agent service, interaction service in order to generate an answer to the query.).
Claim 16, Sierhuis et al discloses analytics of the sensor data is generated, wherein analytics includes summary or the textual sentences such as descriptive statistics, trend analysis, etc. (paragraph 50) and Schuck et al shows risk report included in the summary or analytics (Fig. 4) including text (Fig. 4, label 410,5, where textual sentences that are grammatically complete sentences are type of text). Although Fig. 4 does not show sentences in the report, it would be obvious to one skilled in the art before the effective filing date, based on design choice, for the text to include sentences or grammatically complete sentences since text is included in the report and sentences are a type of text.
Claim 17 recites similar limitations as claim 1 and is rejected on the same grounds as claim 1. In addition, Sierhuis et al discloses one or more processors (paragraph 32); a memory (paragraph 32); and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for limitations similarly found in claim 1 (paragraph 32 and see claim 1).
Claim 18 recites similar limitations as claim 16 and is rejected on the same grounds as claim 16.
Claim 19 recites similar limitations as claim 1 and is rejected on the same grounds as claim 1.
Claim 20 recites similar limitations as claim 16 and is rejected on the same grounds as claim 16.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sierhuis et al (US Publication No.: 20160180222) in view of Schuck (US Publication No.: 20230067083), further in view of Gomes et al (US Publication No.: 20210072736).
Claim 3, Sierhuis et al discloses wherein the determining further comprises determining the one or more predictors according to an analytics service having the received data as input (Paragraph 50 discloses software that receives sensor data and generates any number of analyses such as trend analysis, machine learning, descriptive statistics, etc.) and trained to generate the one or more predictors as output (Paragraph 50 discloses any number of analyses may be performed including machine learning which indicates training, wherein the analytics services generates one or more predictors indicating the analytic services is trained to generate predictors.).
Sierhuis et al discloses software that receives the sensor data and generates analyses (paragraph 50), but fails to disclose at least one machine learning model.
Gomes et al discloses analytics generated by a trained machine learning model, trained to generate analytics. (Paragraph 14 discloses “this specification provides real-time (or predictive) and accurate assessments of the operational state of the manufacturing device based on real-time sensor data (e.g. data from sound and/or vibration sensors distributed around the manufacturing plant) and model-based analysis (e.g. models that are trained on historic sensor data and their corresponding operational states) of the sensor data.”) It would be obvious to one skilled in the art before the effective filing date of the application to modify Sierhuis et al by incorporating a trained model to generate analytics or predictions from sensor data as disclosed by Gomes et al so to detect failures in the plant in order determine the health of the operations of the plant, hence preventing failure such as plant operation reduction.
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sierhuis et al (US Publication No.: 20160180222) in view of Schuck (US Publication No.: 20230067083), further in view of Siebel et al (US Publication No.: 20240202225).
Claim 4, Sierhuis et al discloses wherein the conversational agent comprises a chatbot generating the response (Fig. 1 shows a chatbot or a virtual interaction between user and agent.), but fails to disclose the response is generated at least in part according to a large language model.
Siebel et al discloses virtual interaction between user and agent comprising receiving a query and generating a response or answer to the query using large language models (paragraph 42 discloses a user query is received, and utilizing “the various agents, large language models, and other features to generate an accurate and reliable … answer to the user query …”.) Both Sierhuis et al and Siebel et al discloses receiving a user query and generating a response (Paragraph of 54 of Sierhuis et al and Paragraph 42 of Siebel et al), hence it would be obvious to one skilled in the art before the effective filing date of the application to modify Sierhuis et al by incorporating a large language model to generate a response to the user query as disclosed by Siebel et al so to solve the problem of generating a response to a user query and improve accuracy of the response.
Allowable Subject Matter
Claims 10-12,14 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LINDA WONG whose telephone number is (571)272-6044. The examiner can normally be reached 9-5.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew C Flanders can be reached at 571-272-7516. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/LINDA WONG/Primary Examiner, Art Unit 2655