DETAILED ACTION
The following NON-FINAL Office Action is in response to application 18/946329 filed on 11/13/2024.
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 . 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.
Status of Claims
Claims 1-20 are currently pending and have been rejected as follows.
Priority
Examiner has noted that the Applicant has claimed priority from the foreign application KR10-2023-0157461 filed on 11/14/2023.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/13/2024 comply with the provisions of 37 CFR 1.97, 1.98, and MPEP 609 and were considered by the Examiner.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 9-10 and 19-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding Claims 9 and 19
Claims 9 and 19 recite the limitation of “storing on-site processing information for the new incident information and the reported new incident that is processed in the database by preprocessing the on-site processing information for the new incident information and the reported new incident that is processed when the new incident information is determined to be true; and storing the new incident information in the database by preprocessing the new incident information when the new incident information is determined to be not true”.
It is unclear what information is being stored. For example, “on-site processing information for the new incident information” is stored, but it is unclear if on-site processing information for the reported new incident is stored as well.
Additionally, it is unclear what information is being stored when the new incident information is determined to be true or not true. For example, it appears that new incident information is stored in the database regardless of whether it is true or not.
Further, it is unclear what information is being preprocessed and what information is being processed. For example, the reported new incident is “processed in the database” and is “processed when the new incident information is determined to be true”.
Examiner recommends Applicant separate the limitation to clarify which pieces of information are stored in the database and which pieces of information are processed and processed under what conditions.
For purposes of applying art, Examiner interprets the limitation as 4 distinct limitations:
“storing on-site processing information for the new incident information”
“the reported new incident that is processed in the database by preprocessing the on-site processing information for the new incident information”
“the reported new incident that is processed when the new incident information is determined to be true” and
“storing the new incident information in the database by preprocessing the new incident information when the new incident information is determined to be not true”.
Regarding Claims 10 and 20
Claims 10 and 20 recite the limitation of “wherein the new incident information comprises text information and unusual-thing information associated with a reporting situation of the reported new incident”.
The term “unusual-thing” is a relative term which renders the claim indefinite. The term “unusual-thing” or rather “unusual” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
For purposes of applying art, Examiner interprets “unusual-thing information” as a deviation event.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-10 are directed to a method (i.e., a process) and Claims 11-20 are directed to an electronic device (i.e., a machine). Therefore, the claims all fall within one of the four statutory categories of invention.
Step 2A Prong 1
Independent Claim 1 and Claim 11 recite the limitations of:
receiving new incident information and reporter information about a reported new incident;
determining whether the new incident information is obtained by a false or mistaken report, based on the new incident information and the reporter information;
determining, when the new incident information is determined to be true, a similarity with one or more pieces of related incident information associated with the reported new incident…; and
outputting, among the one or more pieces of related incident information, similar incident information to respond to the reported new incident, based on the similarity
Certain Methods of Organizing Human Activity
The limitations stated above are processes that under broadest reasonable interpretation covers “certain methods of organizing human activity” (commercial interactions or managing personal behavior or relationships or interactions between people). Specifically, business relations or social activities in light of Applicant’s specification paragraph 4 “A report of an incident (e.g., a 112 report, etc.) may depend on the subjective perspective and judgment of a reporter, which may differ from information about an actual incident. In addition, when a reported incident is obtained by a false or mistaken report, significant manpower or property loss may occur to handle the reported incident. An on-site manager may not be able to handle an incident in a timely manner due to a time delay in finding an on-site response measure, based on the report content of a new incident, and may inappropriately handle the incident due to failure to find an appropriate on-site response measure”. Accordingly, the claims recite an abstract idea.
Step 2A Prong 2
The judicial exception is not integrated into a practical application. Claim 1 recites the additional elements of an electronic device and a database that stores past incident information. Claim 11 recites the additional elements of an electronic device comprising a processor and a database that stores past incident information.
The additional elements of an electronic device, a processor, and a database that stores past incident information are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f).
Accordingly, the additional elements do not integrate the abstract idea into a practical application, whether individually or viewed in an ordered combination, because mere instructions to apply the exception using a generic computer component does not impose meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
Step 2B
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 additional elements of an electronic device, a processor, and a database that stores past incident information amount to no more than mere instructions to apply the exception using a generic computer component.
None of the steps/functions of Claim 1 and Claim 11 when evaluated individually or as an ordered combination amount to significantly more than the abstract idea. The additional elements are merely used to perform the limitations directed to organizing human activity and mere instructions to apply the judicial exception, thus, the analysis does not change when considered as an ordered combination.
The additional elements of Claim 1 and Claim 11 amount to no more than mere instructions to implement the abstract idea on a computer. Even when considered in combination, these additional elements represent mere instructions to apply an exception using a generic computer component which cannot provide an inventive concept. Thus, the additional elements do not meaningfully limit the claim. Accordingly, Claim 1 and Claim 11 are ineligible.
Dependent Claims 2 and 12, Claims 6 and 16, Claims 7 and 17, and Claims 10 and 20 merely add additional limitations that narrow down the abstract idea identified above.
Dependent Claims 3 and 13 merely add additional limitations (“select” and “determine the similarity”) that narrow down the abstract idea identified above. The claims also recite an additional element of a text similarity algorithm. Such a feature merely limits the claims to the text similarity field i.e., to execution by a text similarity algorithm which is simply an attempt to limit the use of the abstract idea to a particular technological environment. See MPEP 2106.05(h).
Dependent Claims 4 and 14 and Claims 5 and 15 merely add additional limitations (determining, determining, and determining) that narrow down the abstract idea identified above. Claims 5 and 15 also recite an additional element of a binary classification deep learning model that trains the past incident information. Such a feature merely limits the claims to the deep learning/machine learning field i.e., to execution by a binary classification deep learning model that trains the past incident information which is simply an attempt to limit the use of the abstract idea to a particular technological environment.
Dependent Claims 8 and 18 and Claims 9 and 19 merely add additional limitations (storing, storing, and storing) that narrow down the abstract idea identified above. Examiner noting that the limitations of “storing” may also be interpreted as an additional element. Specifically, insignificant extra-solution activity of data storage which is a computer function that is well-understood, routine, and conventional – “storing and retrieving information in memory” in MPEP 2106.05(d)(II)(iv).
Thus, taken alone and when viewed as an ordered combination, nothing in dependent claims 2-10 and 12-20 amount to significantly more than the judicial exception. Claims 1-20 are ineligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 8, 11, and 18 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Gratton et al. (US2021/0081559).
As per independent Claim 1 and Claim 11,
Gratton teaches an operating method of an electronic device, the operating method comprising:/ An electronic device comprising: a processor, wherein the processor is configured to: (para. 109-117)
receiving new incident information and reporter information about a reported new incident (figure 1A and para. 141 (and para. 129) raw signals such as social posts, 911 calls, crowd sourced information where the content of raw signals can include images, video, audio, text, etc.; para. 142-151 where in para. 151 the raw signal is processed and the normalized signal (time, location, context, content (“new incident information”), type, and source (“reporter information”)) is sent to event detection infrastructure)
determining whether the new incident information is obtained by a false or mistaken report, based on the new incident information and the reporter information (para. 196-197 event detection infrastructure can determine event truthfulness (how likely an event is actually an event versus a hoax, fake, misinterpreted, etc.); para. 206 determine truthfulness based on source (“reporter information”), type, age, and content (“new incident information”) of normalized signals; see also para. 215-230 for entire truthfulness module description)
determining, when the new incident information is determined to be true, a similarity with one or more pieces of related incident information associated with the reported new incident in a database that stores past incident information (para. 224 based on the truth score exceeding a threshold, event detection infrastructure can trigger an event detection for the event (“determined to be true” – see para. 217-218); Figure 17 and para. 384-391 where in para. 385 receiving an event feed of events detected from one or more normalized signals and specifically para. 386-388 where characteristics of the event are compared to characteristics of prior events; see also Figure 16 and para. 380-383; para. 375-379 “The impact prediction module can maintain an event history database of prior events and corresponding impacts. As new events are detected, the impact prediction module can refer to the event history database and compare the new events to prior events”)
outputting, among the one or more pieces of related incident information, similar incident information to respond to the reported new incident, based on the similarity (Para. 398 timely notification of predicted impacts allow entities to better prepare or take measures to address the predicted impacts; Para. 377-379 impact prediction module can formulate predicted impacts of new events based on impacts of prior similar events and send the predicted impacts (types and areas) to a notification module which notifies entities; see also para. 389-397)
As per dependent Claim 8 and Claim 18,
Gratton teaches the operating method of claim 1 and the electronic device of claim 11.
Gratton teaches:
storing the new incident information in the database by preprocessing the new incident information (figures 3A-C and para. 160-162 storage for signals in different stages of normalization; figure 4 and para. 168-169 storing the normalized signal; para. 380-397 where in para. 397 events can be stored as a prior event in event history database along with predicted impacts)
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 2-3 and 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Gratton et al. (US2021/0081559) as applied to claims 1 and 11, further in view of Takacs (US2019/0164245).
As per dependent Claim 2 and Claim 12,
Gratton teaches the operating method of claim 1 and the electronic device of claim 11.
Gratton teaches:
selecting the one or more pieces of related incident information, based on the new incident information; and determining the similarity (Para. 386 comparing characteristics of the event to characteristics of a plurality of prior events specifically comparing event category, event time, event location, etc.; para. 391 comparing day of week, holidays, etc.; see also Figure 17 and para. 384-398)
Gratton does not teach, but Takacs teaches:
by comparing text of the new incident information with text of the one or more pieces of related incident information (para. 29 incident reports have location indicator, time indicator, raw text writeup of the incident; para. 39 time distance represented by absolute values of the date difference, time of day difference, geographic distance, and cosine similarity between two incident writeups; para. 40 cosine similarity between text of incident reports – may be replaced with neural networks to link incidents; para. 69 Latent Semantic Analysis clusters using weight assigned to raw text similarity, geographic similarity, and date similarity)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the Gratton invention with Takac with the motivation of improving efficiency. See para. 3 “scraping data from criminal activity reports, categorizing the data, and then using machine-learning to predictively and automatically link related events” and para. 6 “there is a need for a system that allows companies and law enforcement to link related crimes based on information contained in the respective incident reports, such that knowledge of the linked incidents may prevent future related incidents. Further, such a system would be able to determine the presence of a repeat criminal offender or offenders, in addition to being able to uncover large groups of people coordinating efforts to perpetrate crimes. Moreover, such a system would make it easy to assemble evidence to turn over to law enforcement, or to be used by prosecutors to help supplement a case.”
As per dependent Claim 3 and Claim 13,
Gratton teaches the operating method of claim 1 and the electronic device of claim 11.
Gratton teaches:
selecting the one or more pieces of related incident information using incident classification, report date and time, and a report location of the new incident information; and determining the similarity (Para. 386 comparing characteristics of the event to characteristics of a plurality of prior events specifically comparing event category, event time, event location, etc.; para. 391 comparing day of week, holidays, etc.; see also Figure 17 and para. 384-398)
Gratton does not teach, but Takac teaches:
using a text similarity algorithm (para. 29 incident reports have location indicator, time indicator, raw text writeup of the incident; para. 39 time distance represented by absolute values of the date difference, time of day difference, geographic distance, and cosine similarity between two incident writeups; para. 40 cosine similarity between text of incident reports – may be replaced with neural networks to link incidents; para. 69 Latent Semantic Analysis clusters using weight assigned to raw text similarity, geographic similarity, and date similarity)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the Gratton invention with Takac with the motivation of improving efficiency. See para. 3 “scraping data from criminal activity reports, categorizing the data, and then using machine-learning to predictively and automatically link related events” and para. 6 “there is a need for a system that allows companies and law enforcement to link related crimes based on information contained in the respective incident reports, such that knowledge of the linked incidents may prevent future related incidents. Further, such a system would be able to determine the presence of a repeat criminal offender or offenders, in addition to being able to uncover large groups of people coordinating efforts to perpetrate crimes. Moreover, such a system would make it easy to assemble evidence to turn over to law enforcement, or to be used by prosecutors to help supplement a case.”
Claims 4 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Gratton et al. (US2021/0081559) as applied to claims 1 and 11, further in view of Embree et al. (US2005/0160330).
As per dependent Claim 4 and Claim 14,
Gratton teaches the operating method of claim 1 and the electronic device of claim 11.
Gratton teaches:
determining whether the new incident information is obtained by the false or mistaken report (para. 196-197 event detection infrastructure can determine event truthfulness (how likely an event is actually an event versus a hoax, fake, misinterpreted, etc.); para. 206 determine truthfulness based on source, type, age, and content of normalized signals; see also para. 215-230 for entire truthfulness module description)
Gratton suggests the limitation in para. 623 where the power utility is deemed a reliable source of information and a social media source is not. Similarly, para. 206 teaches the reliability of sources.
Gratton does not teach, but Embree teaches:
using a judgment weight based on the past incident information in the database (para. 54 user issue reporting performance table with records of past performance of a user in reporting issues – false positive rate, historical accuracy or correctness in reporting uses; para. 59 issue table with record for each issue including identity of the reporting entity and reported entity; para. 67-68, 74 update performance data of reporting entities; figure 9 and para. 72 if reporting entity has been highly reliable and accurate in reporting issues, the module will assign a higher performance priority to the issue; para. 73 “the user performance module 138 may factor in both the past performance of a reporting entity, and a reported entity when calculating the performance priority 172. The module 138 can also attribute different weights to information concerning the reporting entity and the reported entity. For example, a higher weighting may be attributed to the past performance of the reporting entity”; see also para. 75-78)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the Gratton invention with Embree with the motivation of increasing the accuracy of the determination by accounting for the reliability of the source.
See para. 2-4 “The above issues pertaining to the processing of issue reports are amplified by a number of factors, such as an increase in the complexity or rules pertaining to the operation of a system (e.g., an online resource of forum), and an increase in the number of sources from which issue reports may originate” and para. 97 “This has the effect of allowing the historical accuracy (or other performance metrics) associated with a reporting entity (e.g., a human reporting user) to be factored into the prioritization of response activities to an issue.”
Claims 5 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Gratton et al. (US2021/0081559) in view of Embree et al. (US2005/0160330) as applied to claims 4 and 14, further in view of non-patent literature Quijano-Sanchez et al. (“Applying automatic text-based detection of deceptive language to police reports: Extracting behavioral patterns from a multi-step classification model to understand how we lie to the police” published in 2018; https://doi.org/10.1016/j.knosys.2018.03.010).
As per dependent Claim 5 and Claim 15,
Gratton teaches the operating method of claim 4 and the electronic device of claim 14.
Gratton teaches:
determining a probability of whether the new incident information is obtained by the false or mistaken report, based on text of the new incident information (figure 1A and para. 141 (and para. 129) raw signals such as social posts, 911 calls, crowd sourced information where the content of raw signals can include images, video, audio, text, etc.; para. 196-197 event detection infrastructure can determine event truthfulness (how likely an event is actually an event versus a hoax, fake, misinterpreted, etc.); para. 206 determine truthfulness based on source, type, age, and content of normalized signals; see also para. 215-230 for entire truthfulness module description)
determining whether the new incident information is obtained by the false or mistaken report, based on the probability of whether the new incident information is obtained by the false or mistaken report (para. 215-230 where in para. 218 truth score or truthfulness is represented by a percentage indicating a probability that an associated event is actually true; para. 224 based on the truth score exceeding a threshold, event detection infrastructure can trigger an event detection for the event)
Gratton does not teach, but Embree teaches:
based on the judgment weight (para. 54 user issue reporting performance table with records of past performance of a user in reporting issues – false positive rate, historical accuracy or correctness in reporting uses; para. 59 issue table with record for each issue including identity of the reporting entity and reported entity; para. 67-68, 74 update performance data of reporting entities; figure 9 and para. 72 if reporting entity has been highly reliable and accurate in reporting issues, the module will assign a higher performance priority to the issue; para. 73 “the user performance module 138 may factor in both the past performance of a reporting entity, and a reported entity when calculating the performance priority 172. The module 138 can also attribute different weights to information concerning the reporting entity and the reported entity. For example, a higher weighting may be attributed to the past performance of the reporting entity”; see also para. 75-78)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the Gratton invention with Embree with the motivation of increasing the accuracy of the determination by accounting for the reliability of the source. See para. 2-4 and para. 97.
Gratton/Embree does not teach, but Quijano-Sanchez teaches:
using a binary classification deep learning model that trains the past incident information (Abstract a model for detection of false robbery reports based solely on their text, combining NLP and machine learning to provide police officers the probability that a given report is false; page 158-159 Methodology where the model is trained using 1122 robbery reports (“trains past incident information”); page 159 regression methodologies such as RLR, SVM, Random Forest, Naïve bayes (all of which are models used for binary classification) and the classification into false or true (“binary classification deep learning model”))
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the Gratton invention with Quijano-Sanchez with the motivation of improving the accuracy of the probability. See Abstract “Empirical results show that it is extremely effective in discriminating between false and true reports with a success rate of more than 91%, improving by more than 15% the accuracy of expert police officers on the same dataset. The underlying classification model can be analysed to extract patterns and insights showing how people lie to the police (as well as how to get away with false reporting).” See also page 156 “this system would help the police to better focus their resources and, when properly publicized, its mere existence would discourage citizens from filing a false report, thus preventing the commission of crimes”.
Claims 6-7, 10, 16-17, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Gratton et al. (US2021/0081559) as applied to claims 1 and 11, further in view of Shaffer et al. (US2008/0280637).
As per dependent Claim 6 and Claim 16,
Gratton teaches the operating method of claim 1 and the electronic device of claim 11.
Gratton does not teach, but Shaffer teaches:
wherein the outputting of the similar incident information further comprises, based on regulation information associated with laws, systems, or guidelines to respond to the reported new incident, outputting on-site response information changed according to the regulation information (para. 17 standard operating procedures (SOP) followed in the event of an incident and SOPs may be adapted to deviations that arise and the system may log the events and actions that occur so that “the basis of a database which may then be used to suggest actions to take should a similar deviation arise during a different incident”; para. 36 policy engine; para. 49-56 where in para. 54 the SOPs may be updated/revised based on how the deviations were handled in response to other incidents and para. 55 the system may be able to modify prior deviations to adapt them to a current incident; figure 4 and para. 57-69 where in para. 61 determining if the deviation event is similar to a previous event and para. 62 modifies the first policy based on deviation event)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the Gratton invention with Shaffer with the motivation of improving a user’s ability to respond to incidents.
See Para. 9 “Technical advantages of particular embodiments include methods and systems for handling dynamic incidents. Accordingly, an interoperability system may be able to adjust the actions of a policy or log the actions performed by a user in case an incident does not unfold exactly as the events of a standard operating procedure predicted it would unfold. Another technical advantage of particular embodiments is to allow deviations from a policy to be monitored and logged. Accordingly, the deviations may later be analyzed to determine if the policy needs to be updated or revised. The log of the deviations may also be stored in a database that may be used in creating or revising policies for different incidents.”
As per dependent Claim 7 and Claim 17,
Gratton teaches the operating method of claim 1 and the electronic device of claim 11.
Gratton does not teach, but Shaffer teaches:
wherein the outputting of the similar incident information further comprises outputting textual on-site response information to respond to the reported new incident, based on the new incident information and the similar incident information (para. 17 standard operating procedures (SOP) followed in the event of an incident and SOPs may be adapted to deviations that arise and the system may log the events and actions that occur so that “the basis of a database which may then be used to suggest actions to take should a similar deviation arise during a different incident”; para. 36 policy engine; para. 49-56 where in para. 54 the SOPs may be updated/revised based on how the deviations were handled in response to other incidents and para. 55 the system may be able to modify prior deviations to adapt them to a current incident; figure 4 and para. 57-69 where in in para. 60 bank robbery is occurring during middle of day and lasted longer than traditional bank robbery, system suggests a hostage negotiator be called in, para. 61 determining if the deviation event is similar to a previous event and para. 62 modifies the first policy based on deviation event or generating a suggested modification that is then presented to a user such as a dispatcher who may confirm/approve the modification; para. 23-24, 50 system communicates with various users through endpoints)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the Gratton invention with Shaffer with the motivation of improving a user’s ability to respond to incidents.
See Para. 9 “Technical advantages of particular embodiments include methods and systems for handling dynamic incidents. Accordingly, an interoperability system may be able to adjust the actions of a policy or log the actions performed by a user in case an incident does not unfold exactly as the events of a standard operating procedure predicted it would unfold. Another technical advantage of particular embodiments is to allow deviations from a policy to be monitored and logged. Accordingly, the deviations may later be analyzed to determine if the policy needs to be updated or revised. The log of the deviations may also be stored in a database that may be used in creating or revising policies for different incidents.”
As per dependent Claim 10 and Claim 20,
Gratton teaches the operating method of claim 1 and the electronic device of claim 11.
Gratton teaches:
wherein the new incident information comprises text information associated with a reporting situation of the reported new incident wherein the text information comprises incident classification of the reported new incident and content of the reported new incident (figure 1A and para. 141 (and para. 129) raw signals such as social posts, 911 calls, crowd sourced information where the content of raw signals can include images, video, audio, text, etc.; para. 142-151 where in para. 151 the raw signal is processed and the normalized signal (time, location, context, content (“content”), type (“classification”), and source) is sent to event detection infrastructure)
Gratton does not teach, but Shaffer teaches:
unusual-thing information (para. 6 deviation event may comprise an unexpected event; para. 39 detecting events that occur during the course of an incident; figure 4 and para. 57-69 where in in para. 60 system detects a deviation event, para. 61 determining if the deviation event is similar to a previous event and para. 62 modifies the first policy based on deviation event or generating a suggested modification that is then presented to a user such as a dispatcher who may confirm/approve the modification)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the Gratton invention with Shaffer with the motivation of improving a user’s ability to respond to incidents.
See Para. 9 “Technical advantages of particular embodiments include methods and systems for handling dynamic incidents. Accordingly, an interoperability system may be able to adjust the actions of a policy or log the actions performed by a user in case an incident does not unfold exactly as the events of a standard operating procedure predicted it would unfold. Another technical advantage of particular embodiments is to allow deviations from a policy to be monitored and logged. Accordingly, the deviations may later be analyzed to determine if the policy needs to be updated or revised. The log of the deviations may also be stored in a database that may be used in creating or revising policies for different incidents.”
Claims 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Gratton et al. (US2021/0081559) as applied to claims 1 and 11, further in view of Shaffer et al. (US2008/0280637) in view of Embree et al. (US2005/0160330).
As per dependent Claim 9 and Claim 19,
Gratton teaches the operating method of claim 1 and the electronic device of claim 11.
Gratton teaches:
the reported new incident that is processed when the new incident information is determined to be true (para. 224 based on the truth score exceeding a threshold, event detection infrastructure can trigger an event detection for the event (“determined to be true” – see para. 217-218); Figure 17 and para. 384-391 where in para. 385 receiving an event feed of events detected from one or more normalized signals and specifically para. 386-388 where characteristics of the event are compared to characteristics of prior events; see also Figure 16 and para. 380-383; para. 375-379 “The impact prediction module can maintain an event history database of prior events and corresponding impacts. As new events are detected, the impact prediction module can refer to the event history database and compare the new events to prior events”)
Gratton does not teach, but Shaffer teaches
storing on-site processing information for the new incident information (para. 17 standard operating procedures (SOP) followed in the event of an incident and SOPs may be adapted to deviations that arise and the system may log the events and actions that occur so that “the basis of a database which may then be used to suggest actions to take should a similar deviation arise during a different incident”; para. 36 policy engine)
and the reported new incident that is processed in the database by preprocessing the on-site processing information for the new incident information (para. 49-56 where in para. 54 the SOPs may be updated/revised based on how the deviations were handled in response to other incidents and para. 55 the system may be able to modify prior deviations to adapt them to a current incident; figure 4 and para. 57-69 where in para. 61 determining if the deviation event is similar to a previous event and para. 62 modifies the first policy based on deviation event)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the Gratton invention with Shaffer with the motivation of improving a user’s ability to respond to incidents. See Para. 9.
Gratton/Shaffer does not teach, but Embree teaches:
storing the new incident information in the database by preprocessing the new incident information when the new incident information is determined to be not true (para. 54 user issue reporting performance table with records of past performance of a user in reporting issues – false positive rate, historical accuracy or correctness in reporting uses; para. 59 issue table with record for each issue including identity of the reporting entity and reported entity; para. 67-68, 74 update performance data of reporting entities; figure 9 and para. 72-74 where in para. 74 update write process where if a particular issue is a false positive, records are updated to indicate the outcome; see also para. 100-105)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the Gratton invention with Embree with the motivation of increasing efficiency by storing information which is not true as it improves future determinations of whether information is true or not.
See para. 2-4 “The above issues pertaining to the processing of issue reports are amplified by a number of factors, such as an increase in the complexity or rules pertaining to the operation of a system (e.g., an online resource of forum), and an increase in the number of sources from which issue reports may originate” and para. 97 “This has the effect of allowing the historical accuracy (or other performance metrics) associated with a reporting entity (e.g., a human reporting user) to be factored into the prioritization of response activities to an issue.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Formhals et al. (US2016/0203817)
Asano et al. (US2020/0250183)
Mukund et al. (US2023/0077338)
Galitsky (US2021/0165969)
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/L.M./Examiner, Art Unit 3628
/SHANNON S CAMPBELL/Supervisory Patent Examiner, Art Unit 3628