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 .
DETAILED ACTION
Claims 1-20 are presented for examination. The earliest priority date for this application is 19 July 2024. The applicant is BiaTech Corporation.
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 and 17 are rejected under 35 USC 101.Claims 2-16, and 18-20 are also rejected for depending on the above rejected claims.
The claimed inventions are directed to non-statutory subject matter. The claims are ineligible under 101 because each respective claim is directed to an Abstract idea, to include organizing human activity via mental process/evaluative selection, and data reception. The additional elements do not provide something “significantly more.”
The invention is directed to monitoring airport runways, the embodiment involving collecting aircraft, runway, and environmental data, and using an artificial-intelligence computing device, analyzing the above data. The artificial intelligence computing device, having analyzed the collected data, derives a quantitative runway condition report to determine the conditions of the runway and how the conditions would affect the aircraft traversing the runway. However, the observed “organizing human activity via mental process/evaluative selection” boils down to a person making observations of the weather, the conditions of the runway (for example, if there is ice, rain, winds, and the like), determining the aircraft’s approach, knowledge of the airspeed and aircraft specifications, and having this data, deriving a landing or takeoff pattern based on the observed and known data. Note that basic observation of the weather, the runway, and aircraft characteristics does not necessarily require sensors or a computer in order to derive an aircraft’s reasoned approach or takeoff pattern. Accordingly, this places the invention in a judicial exception to the statutory classes of inventions found in 35 USC 101. For the same reasons, claims 2-16, and 18-20 are also rejected for depending on the above rejected claims. See the “Remarks” section for further clarification as well as MPEP 2106.04(a)(3)
Claim Rejections - 35 USC § 112(b)
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.
Claim 10 recites the limitation "wherein the computing device optimizes data delivery by tuning input data to the output modality or modalities best suited to the data range and intended use.” There is insufficient antecedent basis for this limitation in the claim.
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 may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 2, 5, 14, 17, and 20 are rejected over 35 USC 103 as being unpatentable over Raby et al, U.S. 2022/0122469 in view of Williams et al., U.S. 2025/0174131.
On claim 1, Raby cites except as underlined:
A system for monitoring runways, comprising:
a plurality of sensors configured to collect environmental, runway, and aircraft input data disposed about a runway,
[0030] The runway condition monitoring unit 100 is connected to the aircraft's data system with both a receiver 160 and transmitter 162 along the ARINC 429 data bus. Various discrete inputs such as weight on wheels, landing gear handles, ground spoiler, reverse thrust, etc. are received via a dedicated data port 164, and in situ dedicated sensors that evaluate GPS location, acceleration, or other parameters are connected at the data input port 166.
an artificial intelligence-enabled computing device configured to analyze input data and generate an output through anthropomorphic computing;
[0029] FIG. 3 is a schematic of interrelationship between the braking system and runway condition monitoring unit, and the potential recipients of the runway condition report. The sensors 120 in the aircraft, such as wheel speed sensor, braking pressure transducer, etc., are received in the BCU 210 as described with respect to FIG. 2. The BCU 210 communicates directly with the runway condition monitoring unit 100, which utilizes the input from the BCU (and possibly other sensors that report directly to the runway condition monitoring unit), and the software within the runway condition monitoring unit 100 analyzes the input and generates a quantitative runway condition report. The runway condition monitoring unit 100 is equipped with a communications system that allows the runway condition monitor unit to transmit the report via the aircraft communication bus 101 to the flight deck 102. Additionally, the report can be sent from the runway condition monitor unit 100 (via other onboard aircraft system) to the air traffic control, or airlines, or airport operations 103. When the pilots receive the report within the flight deck 102, they can add a subjective evaluation of the conditions on the runway, and these subjective evaluations are forwarded orally to the air traffic control 103 along with the generated report.
and
a user interface configured to present the output to at least one user.
See [0029] above.
Regarding the excepted an artificial intelligence-enabled computing device, Raby, while disclosing a runway condition monitoring unit), and the software within the runway condition monitoring unit 100 analyzes the input and generates a quantitative runway condition report, Raby doesn’t disclose using artificial intelligence to do the runway condition report.
In the same art of runway information processing, Williams cites:
[0037] As described herein, the artificial intelligence control unit 102 is configured to provide an intelligent, contextual, summarized digest of relevant airport and runway information for pilots relative to their operation, fleet, runway configuration, and current environmental conditions using trajectory-related pattern recognition algorithms and natural language processing of dynamic data (for example, NOTAMs, weather data, and the like), spatial data, static airport data (for example, airport charted notes, fleet specific restriction data), airline-specific data, and crowd-sourced usage patterns. In at least one example, the artificial intelligence control unit 102 uses machine learning and natural language processing to reduce a total quantity of unnecessary information presented to a pilot, and provide relevant data into a single, simple view (that is, the information presentation on the display 116) that can be used in conjunction with dynamic airport maps. In contrast to known methods, examples of the present disclosure provide a strategic, push-oriented process, which highlights important information for a pilot.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to modify Raby’s embodiment using the artificial intelligence (or AI) control unit disclosed in Williams such that the claimed invention is realized.
One of ordinary skill would have included William’s AI feature into Raby “to reduce a total quantity of unnecessary information presented to a pilot, and provide relevant data into a single, simple view (that is, the information presentation on the display 116).”
On claim 2, Raby cites:
The system of claim 1, wherein the sensors are configured to detect one or more of light, sound, temperature, pressure, motion, chemical composition, and force.
[0030] Various discrete inputs such as weight on wheels, landing gear handles, ground spoiler, reverse thrust, etc. are received via a dedicated data port 164, and in situ dedicated sensors that evaluate GPS location, acceleration, or other parameters are connected at the data input port 166.
On claim 5, Raby cites:
The system of claim 1, wherein input data further comprises data from external sources.
[0029] FIG. 3 is a schematic of interrelationship between the braking system and runway condition monitoring unit, and the potential recipients of the runway condition report. The sensors 120 in the aircraft, such as wheel speed sensor, braking pressure transducer, etc., are received in the BCU 210 as described with respect to FIG. 2. The BCU 210 communicates directly with the runway condition monitoring unit 100, which utilizes the input from the BCU (and possibly other sensors that report directly to the runway condition monitoring unit), and the software within the runway condition monitoring unit 100 analyzes the input and generates a quantitative runway condition report. The runway condition monitoring unit 100 is equipped with a communications system that allows the runway condition monitor unit to transmit the report via the aircraft communication bus 101 to the flight deck 102. Additionally, the report can be sent from the runway condition monitor unit 100 (via other onboard aircraft system) to the air traffic control, or airlines, or airport operations 103. When the pilots receive the report within the flight deck 102, they can add a subjective evaluation of the conditions on the runway, and these subjective evaluations are forwarded orally to the air traffic control 103 along with the generated report.
On claim 14, Raby cites:
The system of claim 1, wherein the user interface is further configured to collect user input data.
[0029] FIG. 3 is a schematic of interrelationship between the braking system and runway condition monitoring unit, and the potential recipients of the runway condition report. The sensors 120 in the aircraft, such as wheel speed sensor, braking pressure transducer, etc., are received in the BCU 210 as described with respect to FIG. 2. The BCU 210 communicates directly with the runway condition monitoring unit 100, which utilizes the input from the BCU (and possibly other sensors that report directly to the runway condition monitoring unit), and the software within the runway condition monitoring unit 100 analyzes the input and generates a quantitative runway condition report. The runway condition monitoring unit 100 is equipped with a communications system that allows the runway condition monitor unit to transmit the report via the aircraft communication bus 101 to the flight deck 102. Additionally, the report can be sent from the runway condition monitor unit 100 (via other onboard aircraft system) to the air traffic control, or airlines, or airport operations 103. When the pilots receive the report within the flight deck 102, they can add a subjective evaluation of the conditions on the runway, and these subjective evaluations are forwarded orally to the air traffic control 103 along with the generated report.
On claim 17, Raby and Williams cites:
A method for monitoring aircraft and runways, comprising:
collecting environmental, aircraft, and runway data from a plurality of sensors disposed about a runway and external sources;
analyzing data using an artificial intelligence-enabled program;
generating an integrated output using an artificial intelligence-enabled program;
delivering the output to a user through a user interface; and
collecting user input data through the user interface.
See the rejection of claim 1 which discloses the same subject matter as claim 17 and is rejected for the same reasons.
On claim 20, Raby and Williams cites:
The method of claim 17, further comprising transmitting user input data to the artificial intelligence-enabled program for evaluation and integration into the multimodal presentation. See the rejection of claim 1 citing Williams, [0037], artificial intelligence.
Claims 3 and 4 are rejected over 35 USC 103 as being unpatentable over Raby et al, U.S. 2022/0122469 in view of Williams et al., U.S. 2025/0174131 and Rasmussen et al., U.S. 2005/0268710.
On claim 3, Raby cites except as underlined:
The system of claim 1, wherein the sensors are positioned and oriented to optimize distributed data collection.
Raby cites:
[0030] The runway condition monitoring unit 100 is connected to the aircraft's data system with both a receiver 160 and transmitter 162 along the ARINC 429 data bus. Various discrete inputs such as weight on wheels, landing gear handles, ground spoiler, reverse thrust, etc. are received via a dedicated data port 164, and in situ dedicated sensors that evaluate GPS location, acceleration, or other parameters are connected at the data input port 166.
Raby doesn’t cite the excepted claim limitations. In the same art of aircraft monitoring, Rasmussen cites:
[0049] If desired, interface 304 could be configured to allow ground personnel to adjust the orientation of sensors 301-303 before a flight to optimize sensor performance based on the aerodynamic characteristics of the airplane.
Rasmussen further includes:
[0072] Sensor system 300 may be used with a camera and computer where the camera and computer characterize ice and water particles by phase, shape, and density. This data can be used to validate the outputs of circuitry 900.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to include into Raby the sensor positioning feature disclosed in Rasmussen such that the claimed invention is realized. Rasmussen discloses a known practice of adjusting sensor orientation to optimize sensor performance concurrent to aircraft aerodynamics.
On claim 4, Raby and Rasmussen cites:
The system of claim 1, wherein the sensors comprise one or more of fiber optic sensors, cameras, microphones, thermal sensors, and gas sensors.
See the rejection of claim 3 regarding cameras.
Claims 6 is rejected over 35 USC 103 as being unpatentable over Raby et al, U.S. 2022/0122469 in view of Williams et al., U.S. 2025/0174131 and Saxena et al., U.S. 2019/0035291.
On claim 6, Raby cites except as underlined:
The system of claim 1, wherein the computing device is further configured to use computer vision, 3D imaging, and multi-sensor fusion to monitor environmental, runway, and aircraft conditions.
Raby cites:
[0029] FIG. 3 is a schematic of interrelationship between the braking system and runway condition monitoring unit, and the potential recipients of the runway condition report. The sensors 120 in the aircraft, such as wheel speed sensor, braking pressure transducer, etc., are received in the BCU 210 as described with respect to FIG. 2. The BCU 210 communicates directly with the runway condition monitoring unit 100, which utilizes the input from the BCU (and possibly other sensors that report directly to the runway condition monitoring unit), and the software within the runway condition monitoring unit 100 analyzes the input and generates a quantitative runway condition report.
[0030] The runway condition monitoring unit 100 is connected to the aircraft's data system with both a receiver 160 and transmitter 162 along the ARINC 429 data bus. Various discrete inputs such as weight on wheels, landing gear handles, ground spoiler, reverse thrust, etc. are received via a dedicated data port 164, and in situ dedicated sensors that evaluate GPS location, acceleration, or other parameters are connected at the data input port 166.
Raby doesn’t cite the excepted claim limitations.
In the related art of aircraft collision prevention, Saxena cites:
[0045] The display is coupled to receive image rendering display commands and is configured, upon receipt thereof, to render one or more images. The receiver is configured to wirelessly receive the object data transmitted from each transmitter. The display processor is coupled to the receiver to receive the object data therefrom, and is configured to fuse the object data and supply the image rendering display commands to the display. Each transmitter is configured to wirelessly transmit the received object data. The receiver is configured to wirelessly receive the object data transmitted from each transmitter. The display processor is configured to: transform the object data transmitted from each transmitter into a common reference frame; fuse the object data by combining objects detected by more than one 3D LIDAR sensor that correspond to a same object into a single object; track the objects over time; and determine when each object poses a potential obstacle.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to modify the multiple sensor data processing system disclosed in Raby using the data processing and imaging features disclosed in Saxena such that the claimed invention is realized. Saxena discloses a known embodiment for combining aircraft-related sensor data into a 3D format. One of ordinary skill would have provided this modification to have a convenient way to view multiple issues in a single display.
Claims 8 is rejected over 35 USC 103 as being unpatentable over Raby et al, U.S. 2022/0122469 in view of Williams et al., U.S. 2025/0174131 and Malladi et al., U.S. 2021/0326128.
On claim 8, Raby cites except as underlined:
The system of claim 1, wherein the computing device utilizes edge computing.
Raby cites:
[0022] The brake control unit determines a runway/aircraft interface status and sends the data to the runway condition monitoring unit 100. The runway condition monitoring unit 100 can then incorporate additional inputs, such as a stand-alone accelerometer module and/or a Global Positioning System (GPS) module as additional data source for processing, calculating and displaying the runway condition. The runway condition monitoring unit 100 includes a processor that collects, processes, and stores data using a computer program, where input from each wheel 230 in the landing gear 205 is fed to the program. The program performs numerous calculations according to specific algorithms, and outputs a unique and objective runway condition report that may be stored, broadcasted, and otherwise made available through various means to subsequently landing aircraft at the same runway.
Raby doesn’t disclose edge computing.
In the related art of computer processing, Malladi cites:
[0011] Edge intelligence platform is a software-based solution based on fog computing concepts which extends data processing and analytics closer to the edge where the IIoT devices reside. Maintaining close proximity to the edge devices rather than sending all data to a distant centralized cloud, minimizes latency allowing for maximum performance, faster response times, and more effective maintenance and operational strategies. It also significantly reduces overall bandwidth requirements and the cost of managing widely distributed networks.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to include into Raby the edge computing feature disclosed in Malladi such that the claimed invention is provided. Edge computing minimizes latency allowing for maximum performance, faster response times, and more effective maintenance and operational strategies. It also significantly reduces overall bandwidth requirements and the cost of managing widely distributed networks.
Claims 9 is rejected over 35 USC 103 as being unpatentable over Raby et al, U.S. 2022/0122469 in view of Williams et al., U.S. 2025/0174131 and Malladi et al., U.S. 2021/0326128 and Lo et al., U.S. 2024/0257648.
On claim 9, Raby cites except as underlined:
The system of claim 8, wherein edge computing is supported with federated machine learning.
In the rejection of claim 8, Raby in view of Malladi disclosed an embodiment involving edge computing. However, neither involved “federated machine learning.
In the related art of drone monitoring, Lo discloses:
[0031] In contrast to traditional drone monitoring systems, aspects of this disclosure provide cloud services using edge computing to monitor both authorized and unauthorized drone activities, and mitigate unauthorized drone activities without requiring direct control over those drones, authorized or unauthorized. In certain embodiments, the system can implement monitoring and mitigation of drone activities using edge computing based on federated learning techniques for the data analytics of drone activities.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to include into Malladi’s edge computing the federated machine learning processes disclosed in Lo. One of ordinary skill would have implemented federated learning to: allow for real-time updates of the model as training occurs locally and for raining on local data to reduce the computational load and power consumption.
Claims 7 is rejected over 35 USC 103 as being unpatentable over Raby et al, U.S. 2022/0122469 in view of Williams et al., U.S. 2025/0174131 and McKean et al., U.S. 2017/0097887.
On claim 7, Raby cites except as underlined:
The system of claim 1, wherein the computing device comprises:
a memory storing input data and artificial intelligence programming, a processing unit communicatively coupled to the memory and a communications interface,
figure 3 and [0022] discloses:
[0022] The brake control unit determines a runway/aircraft interface status and sends the data to the runway condition monitoring unit 100. The runway condition monitoring unit 100 can then incorporate additional inputs, such as a stand-alone accelerometer module and/or a Global Positioning System (GPS) module as additional data source for processing, calculating and displaying the runway condition. The runway condition monitoring unit 100 includes a processor that collects, processes, and stores data using a computer program, where input from each wheel 230 in the landing gear 205 is fed to the program. The program performs numerous calculations according to specific algorithms, and outputs a unique and objective runway condition report that may be stored, broadcasted, and otherwise made available through various means to subsequently landing aircraft at the same runway.
and wherein:
the processing unit is configured to process input data,
(see above).
optimize data storage, processing, and delivery, and generate an output using the artificial intelligence programming, and the communications interface is configured to facilitate communication with other systems or devices.
See figure 3 and [0022] above.
Regarding the excepted optimized data storage, as disclosed above, Raby includes the processing and storage of data. Raby doesn’t disclose the excepted claim limitations.
In the related art of storage management, McKean discloses:
Abstract: Systems and techniques for performing a data transaction are disclosed that provide improved cache performance by pinning recovery information in a controller cache. In some embodiments, a data transaction is received by a storage controller of a storage system. The storage controller determines whether the data transaction is directed to a data stripe classified as frequently accessed. Data associated with the data transaction and recovery information associated with the data transaction are cached in a cache of the storage controller. The recovery information is pinned in the cache based on the data transaction being directed to the data stripe that is classified as frequently accessed, and the data is flushed from the cache independently from the pinned recovery information.
[0004] Therefore, in order to provide optimal data storage performance and protection, a need exists for systems and techniques for managing data that make efficient use of caches and processing resources to mitigate the penalties associated with recovery information. In particular, systems and methods that reduce the latency associated with maintaining recovery information while still protecting data integrity would provide a valuable improvement over conventional storage systems. Thus, while existing storage systems have been generally adequate, the techniques described herein provide improved performance and efficiency.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to modify Raby’s embodiment using the optimized data storage as disclosed in McKean such that the claimed invention is realized.
One of ordinary skill would have included McKean’s systems and methods to reduce the latency associated with maintaining recovery information while still protecting data integrity and providing a valuable improvement over conventional storage systems
Claims 10-13, 16, 18, and 19 are rejected over 35 USC 103 as being unpatentable over Raby et al, U.S. 2022/0122469 in view of Williams et al., U.S. 2025/0174131 and Junkin et al., U.S. 2005/0153268.
On claim 10, Raby cites except as underlined:
The system of claim 1, wherein the computing device optimizes data delivery by tuning input data to the output modality or modalities (112(b)) best suited to the data range and intended use.
Raby cites:
[0022] The program performs numerous calculations according to specific algorithms, and outputs a unique and objective runway condition report that may be stored, broadcasted, and otherwise made available through various means to subsequently landing aircraft at the same runway.
Raby doesn’t disclose the excepted claim limitations. However, in the same art presentation systems, Junkin cites:
[0042]A multimodal (visual and/or auditory and/or tactile and/or olfactory and/or gustatory) presentation system used to improve performance of a subject, by means of presentation of stimuli, recording subjects' reactions to the stimuli, altering future stimuli in response to the subjects' reactions, and comparing changes in subject's reactions across trials…
In other words, Junkin’s embodiment, while not only including providing an embodiment in presenting different types of stimuli responsive to an initial input, Junkin’s embodiment is involve in altering future stimuli output based on feedback observed recorded reactions.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to modify Raby’s runway presentation using the features disclosed in Junkin to provide an embodiment accurately reflecting the user’s response to intial stimuli.
On claim 11, Raby cites except as underlined:
The system of claim 1, wherein the output is a multimodal presentation including visual, auditory, tactile, olfactory, and gustatory stimuli.
Raby discloses:
[0022] The program performs numerous calculations according to specific algorithms, and outputs a unique and objective runway condition report that may be stored, broadcasted, and otherwise made available through various means to subsequently landing aircraft at the same runway.
Raby doesn’t disclose the presentation provided in a user interface as disclosed in the excepted limitations above.
In the related art of presentation systems, Junkin cites:
[0042]A multimodal (visual and/or auditory and/or tactile and/or olfactory and/or gustatory) presentation system used to improve performance of a subject, by means of presentation of stimuli, recording subjects' reactions to the stimuli, altering future stimuli in response to the subjects' reactions, and comparing changes in subject's reactions across trials…
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to modify Raby’s presentation system using the features disclosed in Junkin such that the claimed invention is realized.
One of ordinary skill would have included this feature to improve performance of a subject, by means of presentation of stimuli.
On claim 12, Raby and Junkin cites:
The system of claim 11, wherein the multimodal presentation is delivered through one of an augmented reality environment, a virtual reality environment, or conventional monitor, tablet, or personal communication device. See the rejection of claim 11. By definition, the passage disclosed in Junkins, [0022], is an “augmented reality environment”
On claim 13, Raby and Junkin cites:
The system of claim 1, wherein the user interface is configured to deliver visual, auditory, tactile, olfactory and gustatory stimuli. See the rejection of claim 11 which discloses the same subject matter as claim 13 and is rejected for the same reasons.
On claim 16, Raby and Junkin cites:
The system of claim 1, wherein the user interface is a virtual reality appliance having one or more of a visualization screen, audio output, scent projectors, camera, microphones, motion sensors, and haptics. See the rejection of claim 11 citing Junkins. The cited “olfactory presentation system” meets the claimed “scent projectors.
On claim 18, Raby and Junkin cites:
The method of claim 17, wherein generating an integrated output comprises: identifying the desired input data; converting data into ranges that map to human senses; tuning input data to particular human senses; and combining multiple input types onto one or more senses to create a comprehensive, multimodal presentation for delivery to the user. See the rejection of claim 10 citing Junkin:
[0042]A multimodal (visual and/or auditory and/or tactile and/or olfactory and/or gustatory) presentation system used to improve performance of a subject, by means of presentation of stimuli, recording subjects' reactions to the stimuli, altering future stimuli in response to the subjects' reactions, and comparing changes in subject's reactions across trials…
The claimed “tuning input data to particular human senses” is provided in the recorded subjects reactions to the stimuli and altering future stimuli responsive to the recorded subject reactions.
On claim 19, Raby and Junkin cites:
The method of claim 17, wherein the integrated output is a multimodal presentation including visual, auditory, tactile, olfactory, and gustatory stimuli. See the rejection of claim 11 which discloses the same subject matter as claim 19 and is rejected for the same reasons.
Allowable Subject Matter
Claim 15 is objected to for depending on a rejected claim but is otherwise allowable if amended into an independent format (if additional amendments were provided to the claim to overcome the 101 rejection). Claim 15 claims, in part:
“wherein the computing device is further configured to: analyze user input data; modify artificial intelligence computing algorithms according to user input data; alter input data collection based on user input data; generate a predictive model for predicting user responses; and generate tailored outputs to reflect user preferences.”
In short, the claimed invention can be summed up in two parts:
The first part requiring an analysis of user input data, and altering or adjusting AI computer algorithms responsive to input data collection based on user input data.
The second part includes generating a predictive model for predicting user responses of the user input data, and generating tailored outputs to reflect user preferences. Each part, although both disclosed in claim 15, are separate and distinct “sub-embodiments.”
The closest reference of record involves an embodiment to Bugenhagen, U.S. 2018/0322419 (hereinafter “419”). In particular, 419 cites:
“[0054] In various embodiments, refining or tuning of the AI agent 215 and/or AI engine may include the removal of “false positives” resulting from the algorithms utilized by the AI agent 215 and/or AI engine. For example, in some embodiments, the AI agent 215 and/or an AI engine 105 may produce a false positive in response to a user input or obtained data 210, and a user, third-party vendor, service provider, or a software tool may remove the false positive by modifying an algorithm and/or data 210 utilized by the AI agent 215 and/or AI engine. As previously described, to accelerate the learning process, the AI agent 215 and/or AI engine may include a feedback mechanism, such as, without limitation, an API (e.g., a learning API), interface, or trigger (e.g., a physical button, switch, or trigger on a device or a software button). The feedback mechanism may be configured to cause the AI agent 215 and/or AI engine to enter a learning mode. In the learning mode, the AI agent 215 and/or AI engine may be configured to generate a snapshot of state inputs (e.g., the data 210 obtained from the managed object 205).”
419 clearly addresses the first part, as the embodiment includes taking into consideration user input “false positives,” and modifying the AI algorithm to remove the false positives.
However, the second part of the claim involves providing a predictive model for predicting responses to the user input data and generating tailored outputs reflective of user preferences. A search for references analogous to the second part of claim 15 was researched but failed to yield results meeting that part of the claimed invention. Because of this, claim 15 is otherwise deemed allowable subject matter, however, amending claim 15 alone is insufficient to make the amendment allowable. In order to have the amendments “amount to something more,” the applicant is invited to review MPEP 2106.05 “Eligibility Step 2B: Whether a Claim Amounts to Significantly More.” This review should include “A. Relevant Considerations For Evaluating Whether Additional Elements Amount To An Inventive Concept” and “B. Examples Of How Courts Conduct The Search For An Inventive Concept.” During this review, any amendment should include ensuring there is support in the specification to avoid any 35 USC 112 issues.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CAL EUSTAQUIO whose telephone number is (571)270-7229. The examiner can normally be reached on 8am-5pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Brian Zimmerman, can be reached at (571) 272-3059. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application lnformation Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAlR only. For more information about the PAlR system, see http:/lpair-direct.uspto.gov. Should you have questions on access to the Private PAlR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-91 99 (IN USA OR CANADA) or 571-272-1000.
/CAL J EUSTAQUIO/Examiner, Art Unit 2686
/BRIAN A ZIMMERMAN/Supervisory Patent Examiner, Art Unit 2686
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