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 .
Response to Amendments
Claims 1-9 and 12 are presented for examination. Assig: NEC; Priority 7 November 2023
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, and 12 are rejected under 35 USC 103 as being unpatentable over Englund U.S. 2020/0191613 in view of Showen et al., U.S. 2008/0084788.
On claim 1, Englund cites except as underlined (the italicized portion of the claims indicates the latest amendments):
A system for substation security comprising:
a distributed fiber optic sensing (DFOS) / distributed acoustic sensing (DAS) system including an optical fiber having a plurality of sensing points;
figure 1 and [0062] The disclosed system and method make use of fibre optic distributed acoustic sensing to provide spatial and temporal surveillance and monitoring data within a geographical area, such as a city, utilising one or more optical fibres distributed across the geographical area. Such a sensing technique relies on the occurrence of a nearby acoustic event causing a corresponding local perturbation of refractive index along an optical fibre. The required proximity of the acoustic event depends on noise floor of the sensing equipment, the background noise, and the acoustic properties of the medium or media between the acoustic event and the optical fibre. Due to the perturbed refractive index, an optical interrogation signal transmitted along an optical fibre and then back-scattered in a distributed manner (e.g. via Rayleigh scattering or other similar scattering phenomena) along the length of the fibre will manifest in fluctuations (e.g. in intensity and/or phase) over time in the reflected light. The magnitude of the fluctuations relates to the severity or proximity of the acoustic disturbance. The timing of the fluctuations along the distributed back-scattering time scale relates to the location of the acoustic event.
[0066] In one example, a system 100 for use in distributed acoustic sensing (DAS) is illustrated in FIG. 1. The DAS system 100 includes a coherent optical time-domain reflectometer (C-OTDR) 102. The C-OTDR 102 includes a light source 104 to emit an optical interrogation field 106 in the form of a short optical pulse to be sent into each of optical fibres 105A, 105B and 105C. The optical fibres 105A, 105B and 105C are distributed across a geographical area 107. The C-OTDR 102 includes a photodetector 108 configured to detect the reflected light 110 scattered in a distributed manner and produce a corresponding electrical signal 112 with an amplitude proportional to the reflected optical intensity resolved over time. The time scale may be translated to a distance scale relative to the photodetector 108. An inset in FIG. 1 illustrates a schematic plot of such signal amplitude over distance at one particular instant. The DAS system 100 also includes a processing unit 114, within or separate from the C-OTDR 102, configured to process the acoustic fluctuations 116 in the electrical signal 112.
[0069] FIGS. 2A, 2B, 2C, 2D and 3A illustrate various examples of the disclosed method 200. The disclosed method 200 includes the step 202 of transmitting, at multiple instants 252A, 252B and 252C, interrogating optical signals or fields 106 into each of one or more optical fibres (e.g. one or more of 105A, 105B and 105C) distributed across a geographical area (e.g. 107), which is typically an urban environment. The optical fibres typically form part of a public optical fibre telecommunications network which provides a high degree of coverage (practically ubiquitous) in an urban and particularly inner city environment. The disclosed method 200 also includes the step 204 of receiving, during an observation period (254A, 254B and 254C) following each of the multiple instants 252A, 252B and 252C, returning optical signals (e.g. 110) scattered in a distributed manner over distance along the one or more of optical fibres (e.g. one or more of 105A, 105B and 105C).
(DAS or distributed acoustic sensing using “optical fibres” is disclosed above. The claimed “sensing points” includes any reflected light 110 sensing the cited perturbations and being sent back to photodetector 108).
the substation security system including circuitry comprising at least one memory storing instructions and at least one processor configured to execute the instructions
[0030] The disclosure extends to a computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a processor, enable the spatial and temporal classification of a range of different types of sound producing targets in a geographical area, by executing one or more of the methods summarised above.
[0068] The digitised electrical signal 112, any measured fluctuations 116 and/or processed data associated therewith may be stored in a storage unit 115. The storage unit 115 may include volatile memory, such as random access memory (RAM) for the processing unit 114 to execute instructions, calculate, compute or otherwise process data. The storage unit 115 may include non-volatile memory, such as one or more hard disk drives for the processing unit 114 to store data before or after signal-processing and/or for later retrieval. The processing unit 114 and storage unit 115 and may be distributed across numerous physical units and may include remote storage and potentially remote processing, such as cloud storage, and cloud processing, in which case the processing unit 114 and storage unit 115 may be more generally defined as a cloud computing service.
to:
detect a gunshot acoustic event from DAS data generated by the plurality of sensing points;
[0061] The surveillance data can relate to real-time acoustic data for monitoring targets. Alternatively or additionally, the surveillance data relates to historic acoustic data for later retrieval and searching. In general, such as vehicles (generating tyre/engine noise), pedestrians (generating footsteps), trains (generating rail track noise), building operations (generating operating noise), and road, track or infrastructure works (generating operating noise). They also include events caused by targets, such as car crashes, gunshots caused by a handgun or an explosion caused by explosives (generating high-pressure sound waves and reverberation).
determine, for the gunshot acoustic event, arrival time differences among acoustic signals detected at the plurality of sensing points;
[0031] The disclosure extends to an acoustic system for providing spatial and temporal classification of a range of different types of sound producing targets in a geographical area, the system including: an optical signal transmitter arrangement for repeatedly transmitting, at multiple instants, interrogating optical signals into each of one or more optical fibres distributed across the geographical area and forming at least part of an installed fibre-optic communications network; an optical signal detector arrangement for receiving, during an observation period following each of the multiple instants, returning optical signals scattered in a distributed manner over distance along the one or more of optical fibres, the scattering influenced by acoustic disturbances caused by the multiple targets within the observation period; a processing unit for demodulating acoustic data from the optical signals, processing the acoustic data and classifying it in accordance with the target classes or types to generate a plurality of datasets including classification, temporal and location-related data, and a storage unit for storing the datasets in parallel with raw acoustic data which is time and location stamped so that it can be retrieved for further processing and matched with the corresponding datasets to provide both real time and historic data.
[0066] In one example, a system 100 for use in distributed acoustic sensing (DAS) is illustrated in FIG. 1. The DAS system 100 includes a coherent optical time-domain reflectometer (C-OTDR) 102. The C-OTDR 102 includes a light source 104 to emit an optical interrogation field 106 in the form of a short optical pulse to be sent into each of optical fibres 105A, 105B and 105C.
(The above limitations are met with the “raw acoustic data which is time and location stamped,” the acoustic data being detected at optical fibers 105 A-C at different areas 107 A-C.
determine angle-of-arrival (AOA) directional vectors for the gunshot acoustic event based on the DAS data; and
localize a three-dimensional position of the gunshot acoustic event by combining time-difference-of-arrival (TDOA) hyperbolic equations based on the arrival time differences with the AOA directional vectors.
Regarding the excepted claim limitations, as discussed above, Englund includes an embodiment in figure 1, wherein different optical fiber-detectors 105 A-C provide a return signal 110 responsive to detected sound. Englund doesn’t disclose determining the location of an gunshot event based on AOA and TDOA measurements,
In the same art of gunshot detection systems, Showen discloses:
[0002] Gunshot location systems have been used in various municipalities to assist law enforcement agencies in quickly detecting and responding to incidents of urban gunfire. The details of two such gunshot location systems are described in U.S. Pat. No. 5,973,998 to Showen et al. and U.S. Pat. No. 6,847,587 to Patterson et al., both of which are incorporated herein by reference. Showen's system locates gunshot events using a network of acoustic sensors with an average neighboring sensor separation of approximately 2000 feet. A computer receives acoustic signals from the sensors and triangulates a location, e.g., using relative time-of-arrival (TOA) information and/or angle-of-arrival (AOA) information of signals received from at least three sensors.
Figures 3A and 3B, and [0030] FIG. 3A illustrates two sensors 300, 302 providing AOA and TOA information which define two AOA beams 304, 308 and a TOA hyperbola 312. The gunshot event 314 is located within the intersection of the two AOA beams and the TOA hyperbola. The angular uncertainty of beam 304 defines a beam width 306. Similarly, the angular uncertainty of beam 308 defines a beam width 310. FIG. 3B shows in more detail the region 322 where AOA beams 304 and 308 intersect with each other. Also shown is a portion of TOA hyperbola 312 which intersects the AOA region 322 in a smaller region 324 containing gunshot event 314. Without AOA information, candidate gunshot locations could be anywhere on TOA hyperbola 312. For example, candidate location 320 is on hyperbola 312 but not within either AOA beam. With AOA information from one beam, the candidate location may be further restricted. For example, if AOA information from beam 304 is known, then candidate location 320 may be excluded from consideration. Candidate location 318, however, is in the intersection of beam 304 and hyperbola 312. With AOA information from both beams, even more accuracy is provided. For example, the two-dimensional region 322 which represents the intersection of both beams 304 and 308 with hyperbola 312, eliminates from consideration both candidate locations 320 and 318. Thus, the use of AOA information permits more accuracy and allows the elimination of some candidate locations. Once a small region is determined from intersections, a candidate location may be selected, for example, by computing a centroid of the region.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to include into Englund the gunshot detection features disclosed in Showen such that the claimed invention is realized.
Showen discloses a known embodiment in which a confluence of angle-of-arrival detection data and time-difference-of-arrival measurements are used to determine the location of a gunshot event.
While Englund discloses a basic embodiment for using a plurality of acoustic detectors to determine the location of a gunshot, Englund’s embodiment is modifiable to use the gunshot detection features disclosed in Showen such that the modified embodiment meets the claimed invention. One of ordinary skill would have used together these two methods of gunshot detection to accurately locate the gunshot event.
Furthermore, although Showen doesn’t disclose localize a three-dimensional position of the gunshot acoustic event by combining time-difference-of-arrival (TDOA) hyperbolic equations based on the arrival time differences with the AOA directional vectors, Showen’s invention, as embodied in figures 3A and 3B clearly shows the principles of using the combination of TDOA and AOA measurements to determine the location of a gunshot, the use of TDOA and AOA measurements as shown in the figures that the claimed time-difference-of-arrival (TDOA) hyperbolic equations based on the arrival time differences with the AOA directional vectors are used. Thus, one of ordinary skill, apprised of these known principles, would have arrived at the same conclusion as the claimed invention.
On claim 2, Englund and Showen cites:
The system of claim 1, wherein the at least one processor is configured to process the instructions to triangulate the gunshot acoustic event's origin by determining differences in arrival times and angles of the gunshot acoustic event detected by the DAS system at the plurality of sensing points.
See the rejection of claim 1 citing Showen:
[0002] A computer receives acoustic signals from the sensors and triangulates a location, e.g., using relative time-of-arrival (TOA) information and/or angle-of-arrival (AOA) information of signals received from at least three sensors.
On claim 5, Englund cites:
The system of claim 1 further comprising one or more convolutional neural networks (CNN), wherein the at least one processor is configured to process the instructions to distinguish gunshot acoustic events from other, non-gunshot acoustic events.
As disclosed previously, in the rejection of claim 1, Englund discloses:
[0061] The surveillance data can relate to real-time acoustic data for monitoring targets.
Alternatively or additionally, the surveillance data relates to historic acoustic data for later retrieval and searching. In general, such as vehicles (generating tyre/engine noise), pedestrians (generating footsteps), trains (generating rail track noise), building operations (generating operating noise), and road, track or infrastructure works (generating operating noise). They also include events caused by targets, such as car crashes, gunshots caused by a handgun or an explosion caused by explosives.
On claim 12, Englund and Showden cites:
A method for substation security using a distributed fiber optic sensing (DFOS) / distributed acoustic sensing (DAS) system including an optical fiber having a plurality of sensing points, the method comprising:
generating DAS data using the plurality of sensing points;
detecting a gunshot acoustic event from the DAS data generated by the plurality of sensing points;
determining, for the gunshot acoustic event, arrival time differences among acoustic signals detected at the plurality of sensing points;
determining angle-of-arrival (AOA) directional vectors for the gunshot acoustic event based on the DAS data; and
localizing a three-dimensional position of the gunshot acoustic event by combining time-difference-of-arrival (TDOA) hyperbolic equations based on the arrival time differences with the AOA directional vectors.
See the rejection of claim 1 which discloses the same subject matter as claim 12 and is rejected for the same reasons.
Claims 3 are rejected under 35 USC 103 as being unpatentable over Englund U.S. 2020/0191613 in view of Showen et al., U.S. 2008/0084788 and Azimi-Sajadi et al., U.S. 20120300587 (hereinafter 587).
On claim 3, Englund and Showen cites except as underlined:
The system of claim 2, wherein the at least one processor is configured to process the instructions to determine a real-time bullet trajectory of the gunshot acoustic event detected.
As disclosed previously, Englund disclosed an embodiment locating the source of a gunshot. Furthermore, Englund states:
[0061] The surveillance data can relate to real-time acoustic data for monitoring targets.
However, Englund doesn’t disclose the excepted claim limitations.
In the same art of gunshot detection systems, 587 cites:
[0001] The present invention relates to systems and methods for locating the origin of weapon fire and more particularly to a system and method for determining the origin and trajectory of a gunshot projectile with a distributed wireless acoustic sensor network.
[0002] Shooting incidents in the U.S. and in the rest of the world are on the rise. The number one problem most police personnel and U.S. forces operating in hostile urban areas face is not being able to detect where the shooter is actually located at any given time during the pursuit. It is difficult for humans to rely strictly on their hearing to locate where the sound of gunfire is coming from. Police and military personnel also have trouble relying on witness accounts during these events because people often give inaccurate information when they are in a state of panic, shock and confusion. Additionally, decisions must be made very quickly and accurately before additional causalities are inflicted. A solution that would greatly benefit military, police and law enforcement agencies should offer not only real-time detection of transient sounds such as gunshots or explosives, but also the ability to determine the location of sources of the transient sounds.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to include into Englund and Showen the features disclosed in 587 such that the claimed invention is realized. 587 discloses a known desired feature of determining the origin of a gunshot, in particular, knowing when the gun was fired and also the trajectory of the bullet that was fired in real time. One of ordinary skill, apprised of these known features, would have wanted to determine this information in real time so the data can be acted upon immediately instead of data that is stale and not immediate.
Claim 4 is rejected under 35 USC 103 as being unpatentable over Englund U.S. 2020/0191613 in view of Showen et al., U.S. 2008/0084788 and Azimi-Sadjadi et al., U.S. 2012/0300587 (hereinafter 587) and Frimpong et al., U.S. 2017/0274419 (hereinafter 419) and Gould et al., WO 2011/121338A1.
On claim 4, Englund, Showen, and 587 cites except as underlined:
The system of claim 3 , wherein the at least one processor is configured to process the instructions to determine the real-time bullet trajectory including bullet direction and speed from a frequency change of the gunshot acoustic event.
As disclosed previously, Englund, Showen, and 587 disclosed an embodiment in which real time tracking of a gunshot and bullet trajectory was disclosed. However, none of the references disclosed the excepted limitations.
In the similar art of transformer protection, 419 cites:
[0256] The second category solution uses multiple sensors and more complex algorithms to provide actionable information, such as the shooter direction and location, as well as bullet trajectory, speed, caliber, and number of shots. When an impact is detected in real-time, an alarm signal may be transmitted to the control station and a substation's camera may be then directed to the location of interest.
Furthermore, Gould cites:
Page 14, lines 16-22: In this embodiment the processor 3 compares the frequency of the microwave signal sent by the transmission antennas of the radar antenna array 4 to that reflected from the bullet 10 and received by the radar antenna array 4, allowing for the direct and highly accurate measurement of target velocity component in the direction of the beam. In this way, the processor 3 uses the Doppler Effect of the returned microwave signals from the bullet to determine its radial velocity.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention. One of ordinary skill, apprised of the known measuring techniques disclosed in Gould and 419 would have provided an embodiment meeting the claimed invention.
Claim 6 is rejected under 35 USC 103 as being unpatentable over Englund U.S. 2020/0191613 in view of Showen et al., U.S. 2008/0084788 and Frimpong et al., U.S. 2017/0274419 (hereinafter 419).
On claim 6, Englund cites except as underlined:
The system of claim 5 wherein the at least one processor is configured to process the instructions configured to distinguish a type and extent of damage to the substation resulting from bullet impacts.
As disclosed previously, in the rejection of claim 1, Englund and Showen disclosed an embodiment in which tracking of a gunshot was disclosed. However, none of the references disclosed the excepted limitations
In the related art of transformer protection, 419 cites:
[0250] An option that can address some of the shortcomings of using only the accelerometer sensors or only the acoustic sensors would be to include one of each. While an accelerometer may not always differentiate between a firearm and a different type of impact, the combination of an accelerometer and an acoustic sensor may be used to pick up also the pressure levels and identify a bullet impact. While an acoustic sensor might capture events that are not associated with the inductive device but are nearby, cross-referencing with the accelerometer can reveal a simultaneous vibration signal received from the inductive device.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to modify Englund’s gunshot tracking system with 419’s bullet damage assessment feature to realize an embodiment meeting the claimed limitations. 419 discloses a combination of an acoustic sensor with pressure level measurement to assess bullet impact. The cited pressure levels is taken to mean the amount of bullet pressure one can experience in the environment. For example a 22 Long Rifle bullet will likely produce less pressure than a 357 Magnum bullet due to their respective energy levels. Accordingly, one of ordinary skill, apprised of the types of bullet impacts being experiences, would assess the damage from one identified bullet to be different from another.
Claim 7 is rejected under 35 USC 103 as being unpatentable over Englund U.S. 2020/0191613 in view of Showen et al., U.S. 2008/0084788 and Frimpong et al., U.S. 2017/0274419 (hereinafter 419) and Fisher et al., U.S. 2008/0219100 and Hermann et al., U.S. 2015/0177363.
On claim 7, Englund cites except as underlined:
The system of claim 6 wherein the at least one processor is configured to process the instructions to distinguish the type and extend of damage to the substation resulting from bullet impacts includes analyzing post-gunshot acoustic signals comprising reflections, vibrations, and resonance patterns.
Englund discloses:
[0065] Reference to acoustic data also needs to be read in context with optical data. The raw optical data in the preferred embodiment is stream of repeating reflection sets from a series of optical pulses directed down the sensing fibre. These reflection sets are sampled at very high rates (in the order of gigabits per second) and are demodulated into a series of time windows that correspond to a physical location along the optical fibre. The data in these time windows is used to demodulate the integrated strain along the local length of the fibre at that time. The integrated strain contains signals such as acoustics, seismic, vibration and other signals that induce strain on the fibre.
(Englunds cited “repeated reflections” are return signals 110 to the previously cited COTDR 102 carrying any acoustic information, to include detected gunshot sounds, being sent back to the photodetector 108 disclosed in figure 1).
Englund doesn’t cite the excepted claim limitations. In the related art of transformer protection, 419 cites:
[0177] The inductive device 10 is equipped with vibration sensors for sensing impact and an alarm for notifying personnel when the transformer 10 receives a shock or vibration, such as from a ballistic projectile. If the shock, vibration or noise level is above the threshold for shocks or vibrations experienced during normal operation of the inductive device 10, a safety mode is activated.
And
[0054] FIG. 40 is a plot of acceleration versus time for the bullet impact of trial 12 as measured by the raw vibration and RMS sensors
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to include into Englund the ability to measure vibrations issuing from a gunshot’s impact on a target. One of ordinary skill would have included this feature as another way to determine the amount of damage upon an impacted target.
Regarding the excepted “resonance,” Englund, while disclosing
Englund doesn’t cite the excepted claim limitations. In the related art of gunshot location, Fisher cites:
[0060] With still further reference to FIG. 13, the spectral content of gunshot 200 can be found by performing a transformation from the time domain, as represented by graph 200 to the frequency domain, as represented by graph 500, typically through a Fourier transform. As can be seen in FIG. 13, the spectral content of gunshot 200 shows a noise floor 504 extending from the lower end of the audible spectrum and tapering off somewhere above 1 kilohertz. Of particular significance is the single predominant spike 502 at approximately 240 Hertz. Typically, significant periodic information would be indicative of a resonance, likely from the frame of the gun, the resonance of the barrel cavity, or other like feature of the gun.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to include into Englund the ability to measure resonance issuing from a detected gunshot. One of ordinary skill would have included this feature as another way to determine the type of weapon involved.
Regarding the excepted “reflections,” Englund, while disclosing
[0065] Reference to acoustic data also needs to be read in context with optical data. The raw optical data in the preferred embodiment is stream of repeating reflection sets from a series of optical pulses directed down the sensing fibre. These reflection sets are sampled at very high rates (in the order of gigabits per second) and are demodulated into a series of time windows that correspond to a physical location along the optical fibre.
Englund doesn’t disclose embodiments involving “reflections” regarding bullet impacts.
In the same art of bullet tracking, Hermann cites:
[0015] Moreover, as mentioned above, and as is required when using data 115 from Type A vehicles 101, the computer 105 and/or the server 125 may utilize a time of day at which a gunshot event was recognized to further improve accuracy of the location 195 approximation. For example, a time signature stamp may be obtained from a shared clock such as that received from GPS satellites to ensure each vehicle 101 stamps the time to a common reference. Further, the accuracy of the time stamp should have a resolution (e., 10 milliseconds) sufficient to map out audio reflections from the multiple locations from which a gunshot is captured to allow triangulation.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to include into Englund the ability to measure reflections issuing from a detected gunshot. One of ordinary skill would have included this feature as another way to locate the source of the gunshot.
Claim 8 is rejected under 35 USC 103 as being unpatentable over Englund U.S. 2020/0191613 in view of Showen et al., U.S. 2008/0084788 and Frimpong et al., U.S. 2017/0274419 (hereinafter 419) and Fisher et al., U.S. 2008/0219100 and Hermann et al., U.S. 2015/0177363 and Onofrio et al., U.S. 12,566,238.
On claim 8, Englund cites except as underlined:
The system of claim 7 configured to provide gunshot event correlation to acoustic events occurring before and after the gunshot event.
As disclosed previously, in the rejection of claim 1, Englund discloses:
[0061] The surveillance data can relate to real-time acoustic data for monitoring targets. Alternatively or additionally, the surveillance data relates to historic acoustic data for later retrieval and searching. In general, such as vehicles (generating tyre/engine noise), pedestrians (generating footsteps), trains (generating rail track noise), building operations (generating operating noise), and road, track or infrastructure works (generating operating noise). They also include events caused by targets, such as car crashes, gunshots caused by a handgun or an explosion caused by explosives.
Englund doesn’t disclose embodiments involving event correlation with gunshots.
In the same art of gunshot detection and locating, Onofrio cites:
Col. 3, lines 12-21 cites: The acoustic information can be used to identify a high-intensity gunshot sound, and to correlate, using the gunshot sensor device, the high-intensity gunshot sound to the infrared information that was collected. The collected IR information can be buffered. The correlating can include establishing a temporal correspondence between the gunshot sound and an infrared event that occurred in time before the gunshot sound. The temporal correspondence can identify the number of milliseconds (time) between the events.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to include into Englund the gunshot correlation feature of Onofrio such that the claimed invention is realized. Onofrio discloses a known embodiment for matching an IR event with a gunshot and one of ordinary skill would have used such a feature to match audio to visual occurrences.
Claim 9 is rejected under 35 USC 103 as being unpatentable over Englund U.S. 2020/0191613 in view of Showen et al., U.S. 2008/0084788 and Frimpong et al., U.S. 2017/0274419 (hereinafter 419), and Fisher et al., U.S. 2008/0219100 and Hermann et al., U.S. 2015/0177363 and Onofrio et al., U.S. 12,566,238 and Jung et al., U.S. 2009/0319551.
On claim 9, Englund cites except:
The system of claim 8 wherein the acoustic events occurring before and after the gunshot event include vehicle noises and voices.
As disclosed previously, in the rejection of claim 1, Englund discloses:
[0061] The surveillance data can relate to real-time acoustic data for monitoring targets. Alternatively or additionally, the surveillance data relates to historic acoustic data for later retrieval and searching. In general, such as vehicles (generating tyre/engine noise), pedestrians (generating footsteps), trains (generating rail track noise), building operations (generating operating noise), and road, track or infrastructure works (generating operating noise). They also include events caused by targets, such as car crashes, gunshots caused by a handgun or an explosion caused by explosives.
Englund doesn’t disclose embodiments involving event correlation with gunshots
In the same art of event detection, Jung discloses:
[0097] The event-data storage program automatically searches each sensor data set for sensor data having representative features correlating to a gunshot, siren, tire screech, or loud voices using the selected pattern recognition criteria. If sensor data correlating to a representative feature of a gunshot, siren, tire screech, and loud voices is found, the program stores the correlated sensor data in a retained data storage.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to include into Englund acoustic identification embodiment the event-data correlation feature disclosed in Jung such that the claimed invention is realized. One of ordinary skill would have included such a feature to assemble a change of events leading up to and determining an aftermath of a shooting.
Response to Arguments
Claim 1 claims, in part: “detect a gunshot acoustic event from DAS data generated by the plurality of sensing points; determine, for the gunshot acoustic event, arrival time differences among acoustic signals detected at the plurality of sensing points; determine angle-of-arrival (AOA) directional vectors for the gunshot acoustic event based on the DAS data; and localize a three-dimensional position of the gunshot acoustic event by combining time- difference-of-arrival (TDOA) hyperbolic equations based on the arrival time differences with the AOA directional vectors…”
The applicant’s arguments regarding the rejection of claim 1 were carefully considered, wherein the applicant alleges (on page 5, last paragraph):
“The Examiner's 103 rejection of Claim 1 relies fundamentally on combining the distributed fiber optic network of Englund with the angle of arrival techniques of Azimi-Sadjadi. The Examiner concedes that Englund "did not disclose the use of angles in determining the location of a disturbance." To bridge this gap, the Examiner cites Azimi-Sadjadi. However, Azimi-Sadjadi fails to cure the deficiencies of Englund because Azimi-Sadjadi relies on an entirely different structural foundation. Azimi-Sadjadi explicitly teaches a system comprising "a plurality of spaced sensor nodes" where "[e]ach sensor node 15 has a microphone or acoustic sensor 20." Thus, Azimi-Sadjadi is directed to processing data derived from conventional, discrete microphone arrays. A Person Having Ordinary Skill In The Art (PHOSITA) would not have been motivated, nor had a reasonable expectation of success, to extract mathematical logic (AOA methodologies) designed for discrete microphone nodes and apply them to the continuous optical fiber backscatter data (DAS data) disclosed in Englund. The physics and signal processing requirements of discrete point-sensors are functionally incompatible with the continuous acoustic profile generated by a DAS system.”
However, as shown in the quoted portion of claim 1, the applicant included an amendment involving detecting a system for substation security in which “a distributed fiber optic sensing (DFOS)/distributed acoustic sensing (DAS) system included an optical fiber having a plurality of sensing points.” Due to this amendment, the operation of claim 1 also changed in scope as the amended DFOS/DAS optical sensing device now requires a plurality of sensing devices. As a result, the rejection of claim 1 has been correspondingly amended to meet the new excepted claim limitations wherein added aspects of Englund included describing the claimed “plurality of sensing points” as described in the rejection at [0062, 66, 69] and figures 1, 2A, 2B, 2D, and 3A.
The applicant’s argument has also pointed out (second paragraph, page 6):
“Piecing together discrete components from up to eight different references-
relying on a fiber optic system from one, a discrete microphone system from another, and hyperbolic tracking algorithms from yet another-constitutes impermissible hindsight reconstruction (MPEP 2145). The prior art lacks any teaching, suggestion, or motivation to extract AOA directional vectors and TDOA hyperbolic equations specifically from DAS fiber data to localize a 3D position.”
In response to applicant's argument that the examiner has combined an excessive number of references, reliance on a large number of references in a rejection does not, without more, weigh against the obviousness of the claimed invention. See In re Gorman, 933 F.2d 982, 18 USPQ2d 1885 (Fed. Cir. 1991). As clearly indicated in the prior examination, it is claim 8, and not claim 1, which required eight references. Unless the applicant’s rebuttal includes evidence or argumentation impeaching the credibility of the combination, the applicant’s arguments criticizing the number of references used to reject the claim is without merit.
In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971).
It is clear that the rejection of claim 1 relied on art pertinent to different elements of Englund and 587 to meet the claimed limitations. Since these references preceded the invention and does not obtain any knowledge from the applicant’s disclosure (as the citations from these references were mapped to their respective claim limitations, hindsight reasoning is not seen here. For this reason, the applicant’s arguments are also unpersuasive.
In an additional issue, the applicant also amended claim 1 to include “localize a three-dimensional position of the gunshot acoustic event by combining time- difference-of-arrival (TDOA) hyperbolic equations based on the arrival time differences with the AOA directional vectors…” This amendment wasn’t previously considered as the previous claim limitations required obtaining TDOA and AOA equations to triangulate the location the gunshot event. The TDOA and AOA measurements do not now require triangulation but instead, are combined to find the location of the gunshot event. In order to meet the amendments, the rejection of claim 1 includes a reference to Showen wherein a gunshot event based on a combination of angle-of-arrival (AOA) and time-difference-of-arrival (TDOA) techniques were used to determine the location of the detected gunshot even. Because of this, the applicant’s arguments are unpersuasive.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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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