DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 1-10 are rejected under 35 USC 103 as being unpatentable over Xia et al; (US 2022/0136891) in view of Wellbrock et al; (Explore Benefits of Distributed Fiber Optic Sensing for Optical Network Service Providers – June 2023 attached).
Regarding claim 1, Xia discloses distributed fiber optic sensing system ;( distributed acoustic sensor, a distributed vibration sensor in fiber optical system, see figure 1A) comprising: the distributed fiber optic sensing (DFOS) system including generative Artificial Intelligence and Large Language Models (AI/LLM),( the fiber optic sensing analysis platform 102 may utilize a machine learning model 148 to process the sensing data to determine a threat level to the fiber optic cable 106, see paragraph 31 and figure 1E) the DFOS system configured to monitor, capture, and analyze one or more of temperature, acoustic, strain, and vibration data of a fiber optic network;( in order to minimize a potential of the activity damaging the fiber optic cable 106, the service provider may utilize the fiber optic sensing analysis platform 102, the fiber sensor device 104, and the fiber optic cable 106 to identify the activity based on vibrations from the environment, see paragraph 13 and figure 1a) and wherein in response to user input and based on captured and analyzed data of the fiber optic network, ;( By analyzing sensing data to identify, in real-time or near real-time, activities that may pose a threat of damage to the fiber optic cable 106, the fiber optic sensing analysis platform 102 may minimize a potential of damage to the fiber optic cable 106, see paragraph 47 and the input component 350 includes a component that permits device 300 to receive information, such as via user input, see paragraph 57 and figure 3 )
However, Xia does not explicitly disclose an interactive, the DFOS system is configured to provide live construction query and response (Live CQ) information, live anomaly query and response (Live AQ) information, and live inquiry query and response (Live IQ) information.
In a related field of endeavor, Wellbrock discloses an interactive, (maintenance team, see figure 10) the DFOS system is configured to provide live construction query and response (Live CQ) information and live inquiry query and response (Live IQ) information;(with fiber sensing equipment installed in central offices, construction and other activities can be monitored and alarms can be sent to network maintenance teams in charge and prompt actions can be taken to avoid cable damages, see page 5, section V and figure 10) live anomaly query and response (Live AQ) information ;( the Fiber-CSAD module detects the anomaly events, the system sends warning messages to field teams, see page 5, section V and figure 11).
Thus, it would be obvious for one of the ordinary skilled in the art before the effective filling date of the invention to combine the interactive DFOS of Wellbrock with Xia to provide real-time processing of the sensing data from the DFOS system and the motivation is to provide immediate detection, classification and location of anomaly events.
Regarding claim 2, Xia does not explicitly disclose the system of claim 1 wherein the Live CQ information includes information about construction activities near the fiber optic network monitored by the DFOS system.
In a related field of endeavor, Wellbrock discloses the system of claim 1 wherein the Live CQ information includes information about construction activities near the fiber optic network monitored by the DFOS system ;(with fiber sensing equipment installed in central offices, construction and other activities can be monitored and alarms can be sent to network maintenance teams in charge and prompt actions can be taken to avoid cable damages, see page 5, section V and figure 10). Motivation is same as claim 1.
Regarding claim 3, Xia does not explicitly disclose the system of claim 2 wherein the Live AQ information includes information about anomaly events along the fiber optic network monitored by the DFOS and the DFOS system is configured to continuously update the large language models (LLM) with Live AQ information.
In a related field of endeavor, Wellbrock discloses the system of claim 2 wherein the Live AQ information includes information about anomaly events along the fiber optic network monitored by the DFOS and the DFOS system ;( the Fiber-CSAD module detects the anomaly events, the system sends warning messages to field teams, see page 5, section V and figure 11) is configured to continuously update the large language models (LLM) with Live AQ information (edge AI infrastructures that process data locally stands out as a more appropriate choice for fiber sensing applications and is adaptive to changing deployment environments. The results are provided in real-time that allows actions to be taken time, see page 2, section III). Motivation is same as claim 1.
Regarding claim 4, Xia does not explicitly disclose the system of claim 3 wherein the Live IQ information includes information about current route conditions along the fiber optic network monitored by the DFOS and the DFOS system is configured to continuously update the LLM with the Live IQ information.
In a related field of endeavor, Wellbrock discloses the system of claim 3 wherein the Live IQ information includes information about current route conditions along the fiber optic network monitored by the DFOS and the DFOS ;(with fiber sensing equipment installed in central offices, construction and other activities can be monitored and alarms can be sent to network maintenance teams in charge and prompt actions can be taken to avoid cable damages, see page 5, section V and figure 10). system is configured to continuously update the LLM with the Live IQ information (edge AI infrastructures that process data locally stands out as a more appropriate choice for fiber sensing applications and is adaptive to changing deployment environments. The results are provided in real-time (current) that allows actions to be taken time, see page 2, section III). Motivation is same as claim 1.
Regarding claim 5, Xia does not explicitly disclose the system of claim 4 wherein the DFOS system, based on trouble tickets (811 tickets) received, is configured is configured to establish surveillance zones at one or more locations along the fiber optic network.
In a related field of endeavor, Wellbrock discloses the system of claim 4 wherein the DFOS system, based on trouble tickets (811 tickets) received, is configured is configured to establish surveillance zones at one or more locations along the fiber optic network; (three events (surveillance zones) are pointed out with field inspection. Event– 1 showed an incident where a pole directly falling on the monitoring cable, which was caused by a construction accident. The AI engine reported the event as high threat which was dangerous to the service cable. Event– 2 was also a high threat event that construction machines were working close to the cable (<3m). For asphalt paving machines, Event– 3, it classified as low risk event since the activities were 8-m away, parallel to the cable, see page 6, section V and figure 11).
Regarding claim 6, Xia does not explicitly disclose the system of claim 5 wherein the LLM is continuously updated with Live AQ information comprises historical event logs and most recently detected anomalies.
In a related field of endeavor, Wellbrock discloses the system of claim 5 wherein the LLM is continuously updated with Live AQ information comprises historical event logs and most recently detected anomalies; (edge AI infrastructures that process data locally stands out as a more appropriate choice for fiber sensing applications and is adaptive to changing deployment environments. The results are provided in real-time (current) that allows actions to be taken time, see page 2, section III and event tracking using event logging with live and historical events, see figure 16). Motivation is same as claim 1.
Regarding claim 7, Xia discloses the system of claim 6 wherein the LLM is continuously updated with the one or more of temperature, acoustic, strain, and vibration data of the fiber optic network ;( distributed acoustic sensor, a distributed vibration sensor in fiber optical system, see figure 1A)
Regarding claim 8, Xia does not explicitly disclose the system of claim 7 wherein the DFOS, based on the 811 tickets received, is configured to extract construction details including type, location, and duration of construction activities and identify and mark the extracted details on a map of the fiber optic network.
In a related field of endeavor, Wellbrock discloses the system of claim 7 wherein the DFOS, based on the 811 tickets received, is configured to extract construction details including type, location, and duration of construction activities and identify and mark the extracted details on a map of the fiber optic network (three events (surveillance zones) are pointed out with field inspection. Event– 1 showed an incident where a pole (type) directly falling on the monitoring cable, which was caused by a construction accident. The AI engine reported the event as high threat which was dangerous to the service cable. Event– 2 was also a high threat event that construction machines were working close to the cable (<3m)(location). For asphalt paving machines, Event– 3, it classified as low risk event since the activities were 8-m away (location) parallel to the cable, see page 6, section V and figure 11). Motivation is same as claim 1.
Regarding claim 9, Xia does not explicitly disclose the system of claim 8, wherein the DFOS is configured to allow a user interaction via smart devices or computers, using natural language.
In a related field of endeavor, Wellbrock discloses the system of claim 8, wherein the DFOS is configured to allow a user interaction via smart devices or computers, using natural language ;(with fiber sensing equipment installed in central offices, construction and other activities can be monitored and alarms can be sent to network maintenance teams (user interaction) in charge and prompt actions can be taken to avoid cable damages, see page 5, section V and figure 10). Motivation is same as claim 1.
Regarding claim 10, Xia does not explicitly disclose the system of claim 9, wherein the Live CQ, Live AQ, and Live IQ information is available to a user through a world wide web interface using a natural language of the user.
In a related field of endeavor, Wellbrock discloses the system of claim 9, wherein the Live CQ, Live AQ, and Live IQ information is available to a user through a world wide web interface using a natural language of the user ;(with fiber sensing equipment installed in central offices, construction and other activities can be monitored and alarms can be sent to network maintenance teams (user interaction) in charge and prompt actions can be taken to avoid cable damages, see page 5, section V and figure 10). Motivation is same as claim 1.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure as reproduced below.
a. Carter et al; (US 2026/0118161) discloses a sensory network for monitoring a physical condition within a confinement having edges. The network includes a fiber optic cable, a sensory load, a distributed sensing modulator, a database, a process module, a comparator module and a monitoring receiver, see figure 2.
b. Gunnai et al; (US 2024/0278423) discloses system for an anomaly detected in an authentication request by a classifier, including. obtaining the anomaly detection model, with the anomaly detection model having been trained to detect anomalous authentication requests. Also disclosed is obtaining a multi-layer perceptron (MLP) model trained to provide MLP results similar to anomaly detection results when the same features are provided to both the anomaly detection model and the MLP model, see figure 2.
c. Bergkvist et al; (US 2021/0304077) discloses a method for using machine learning techniques to analyze sensor data from an electronic device and to determine whether the data is associated with an out-of-warranty event, see figure 2.
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/AMRITBIR K SANDHU/ Primary Examiner, Art Unit 2634
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