Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Oath/Declaration
Oath/Declaration as file 07/29/2024 is noted by the Examiner.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
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Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b).
Claims 1-12 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims (1+5), 2-4, 1, 1, (6+10), 7-9, 6 and 6 of U.S. Patent No. 12,050,299 (Application No. 17/596211) respectively. Although the conflicting claims are not identical, they are not patentably distinct from each other because both sets of claims cover the same subject matter.
Both independent claims’ features of the instant application and the co-pending application can be compared as:
Instant Application 18/786668: Claim 1
US Patent 12,050,299: Claims 1 and 5
A passive magnetic detection and discrimination system to detect a magnetized object, comprising:
A passive magnetic detection and discrimination system to detect a magnetized object, comprising:
at least one sensing structure having a plurality of magnetic inductive sensors arranged on a rigid framework;
at least one sensing structure having a plurality of magnetic inductive sensors arranged on a rigid framework;
at least one screening area defined by the at least one sensing structure, whereby the plurality of magnetic inductive sensors are configured to respond to the magnetized object passing thereby;
at least one screening area defined by the at least one sensing structure, whereby the plurality of magnetic inductive sensors are configured to respond to the magnetized object passing thereby; and
a processor and a memory operatively connected to the plurality of sensors and configured to receive data corresponding to amplitude waveforms created in each of the plurality of sensors by the magnetized object;
a processor and a memory operatively connected to the plurality of sensors and configured to receive data corresponding to amplitude waveforms created in each of the plurality of sensors by the magnetized object;
a video camera for capturing an image or video of a subject with the magnetized object passing through the screening area to assist the system with discriminating whether the magnetized object is a threat; and
a video camera for capturing an image or video of a subject with the magnetized object passing through the screening area to assist the passive magnetic detection and discrimination system with discriminating whether the magnetized object is a threat. (Claim 5)
wherein based on characteristic waveforms created by the magnetized object passing by the plurality of sensors, the system detects and discriminates the magnetized object;
wherein based on characteristic waveforms created by the magnetized object passing by the plurality of sensors, the passive magnetic detection and discrimination system detects and discriminates the magnetized object:
wherein the system further comprises an artificial intelligence or machine learning module to improve identification of the magnetized object based on the characteristic waveforms created by the magnetized object.
wherein the passive magnetic detection and discrimination system further comprises an artificial intelligence or machine learning module to improve identification of the magnetized object based on the characteristic waveforms created by the magnetized object;
Both sets of claims’ features of the instant application (claims 2-6) and the US Patent (claims 2-4, 1 and 1) can be compared by using the table shown above.
Instant Application 18/786668: Claim 7
US Patent 12,050,299: Claims 6 and 10
A passive magnetic detection and discrimination method for detecting a magnetized object, comprising:
A passive magnetic detection and discrimination method for detecting a magnetized object, comprising:
providing at least one sensing structure having a plurality of magnetic inductive sensors arranged on a rigid framework;
providing at least one sensing structure having a plurality of magnetic inductive sensors arranged on a rigid framework;
providing at least one screening area defined by the at least one sensing structure, whereby the plurality of magnetic inductive sensors are configured to respond to the magnetized object passing thereby;
providing at least one screening area defined by the at least one sensing structure, whereby the plurality of magnetic inductive sensors are configured to respond to the magnetized object passing thereby;
providing a video camera for capturing an image or video of a subject with the magnetized object passing through the screening area to assist the system with discriminating whether the magnetized object is a threat;
providing a video camera for capturing an image or video of a subject with the magnetized object passing through the screening area to assist the system with discriminating whether the magnetized object is a threat. (Claim 10)
operatively connecting and configuring a processor and a memory to the plurality of sensors to receive data corresponding to amplitude waveforms created in each of the plurality of sensors by the magnetized object; and based on characteristic waveforms created by the magnetized object passing by the plurality of sensors, detecting and discriminating the magnetized object; and
operatively connecting and configuring a processor and a memory to the plurality of sensors to receive data corresponding to amplitude waveforms created in each of the plurality of sensors by the magnetized object; and based on characteristic waveforms created by the magnetized object passing by the plurality of sensors, detecting and discriminating the magnetized object;
utilizing an artificial intelligence or machine learning module to improve identification of the magnetized object based on the characteristic waveforms created by the magnetized object.
utilizing an artificial intelligence or machine learning module to improve identification of the magnetized object based on the characteristic waveforms created by the magnetized object;
Both sets of claims’ features of the instant application (claims 8-12) and the US Patent (claims 7-9, 6 and 6) can be compared by using the table shown above.
This is a double patenting rejection since the conflicting claims have been patented.
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.
Claim(s) 1-3, 5-9, 11 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Hibbs US 2008/0117044 (Hereinafter Hibbs) in view of Dreessen US 2018/0357472 (Hereinafter Dreessen).
Regarding claim 1, Hibbs teaches a passive magnetic detection and discrimination system to detect a magnetized object ([0010, 0015, 0045]; a passive magnetic detection system to detect ferrous (magnetized) objects and discriminate different kinds of objects), comprising:
at least one sensing structure having a plurality of magnetic inductive sensors arranged on a rigid framework (Fig. 1; [0026]; a rigid structure/gateway 4 (framework) with the induction sensors 10-19 contained (arranged) on a frame 38);
at least one screening area defined by the at least one sensing structure (Fig. 1; [0026] the structure is a security screening structure through which people must pass through (screening area)), whereby the plurality of magnetic inductive sensors are configured to respond to the magnetized object passing thereby ([0029]; the magnetic induction sensors distinguish (configured to respond) a magnetic object as it passes through the gateway);
a processor (Fig. 3; [0029, 0033, 0042]; a CPU 96) and a memory (Fig. 3; [0029, 0033, 0042]; memory 9) operatively connected to the plurality of sensors and configured to receive data corresponding to amplitude waveforms created in each of the plurality of sensors by the magnetized object (Fig. 3; [0029, 0033, 0042]; a CPU 96 and memory 97 measure the response of each of the sensors comprising an amplitude of a time-varying (waveform) signal of the magnetic object);
a video camera for capturing an image or video of a subject with the magnetized object passing through the screening area to assist the system with discriminating whether the magnetized object is a threat ([0029, 0046]; a video camera capturing video footage of a person (subject) responsible for transporting the magnetized object as it passes through the gateway for the purpose of identifying the person transporting an unauthorized object such as a gun (discriminating a threat)); and
wherein based on characteristic waveforms created by the magnetized object passing by the plurality of sensors, the system detects and discriminates the magnetized object ([0028-0029]; based on the amplitude of time-varying signals produced (created) by the magnetized object passing through the gateway comprising the sensors, the system detects and distinguishes (discriminates) a small object from a physically larger object);
wherein the system further identification of the magnetized object based on the characteristic waveforms created by the magnetized object ([0028-0029]; distinguish a small magnetic object from a physically larger object (identification) based on the amplitude of time-varying signals produced by the magnetized object).
Hibbs does not specifically teach wherein the system comprises an artificial intelligence or machine learning module to improve identification of the object.
However, Dreesen does teach wherein the system comprises an artificial intelligence or machine learning module to improve identification of the object ([0122, 0205]; a machine learning model using the processor is used to identify movement and position of an object (improve identification).
It would have been obvious before the effective filing date of the claimed invention to modify the passive magnetic detection system for security screening of Hibbs by implementing the teachings of Dreesssen regarding wherein the system comprises an artificial intelligence or machine learning module to improve identification of the object; for the benefit of eliminating background and motion isolation to improve object edge detection, thereby improving the accuracy of object identification and prevent false positive identification (See Dreessen; [0102]).
Regarding claim 2, the combination of Hibbs and Dreessen teaches the system of claim 1, wherein Hibbs further teaches wherein the plurality of sensors is positioned and oriented on the rigid framework to discriminate between different types of magnetized objects (Fig. 1; sensors 10-19 are strategically placed (positioned) on the frame 38 with a spacing and orientation to detect unauthorized items and detect and distinguish a small object from a physically larger object).
Regarding claim 3, the combination of Hibbs and Dreessen teaches the system of claim 1, wherein Hibbs further teaches wherein the rigid framework is at least partially non-metallic ([0026]; “gateway 4 includes a frame 38 which can be formed in many ways and of various materials”; which would include non-metallic materials).
Regarding claim 5, the combination of Hibbs and Dreessen teaches the system of claim 1, wherein Hibbs further teaches wherein the system is further adapted to correlated the image or video of the subject with locational data of the magnetized object calculated from data corresponding to amplitude waveforms created by the sensors to flag a location of the magnetized object in the image or video ([0010, 0028, 0046]; capturing video footage of the person and using (correlating) the magnetic signals from the sensors that decrease relative to distance from the object (locational data) to give an indication (flag) of the actual location of a detected ferrous item on the body and relative to the subject possessing the item).
Hibbs does not specifically teach 3D locational data calculated from data.
However, Dreessen does teach 3D locational data calculated from sensor data ([0059, 0121, 0122]; automatically selecting points where a location of an identified object in the target video of a 3D body model of the subject matches a location of a corresponding object the subject video captured by cameras (sensor)).
It would have been obvious before the effective filing date of the claimed invention to modify the passive magnetic detection system for security screening of Hibbs by implementing the teachings of Dreesssen regarding 3D locational data calculated from sensor data; for the benefit of providing a more accurate picture to security personnel of where an object representing a potential threat is located on a person’s body.
Regarding claim 6, the combination of Hibbs and Dreessen teaches the system of claim 1, wherein Dreessen further teachs wherein the system is further adapted to provide a captured image or video of a subject as an additional input to the artificial intelligence or machine learning module to improve system identification and discrimination of the magnetized object ([0115, 0119, 0122]; the machine learning model is used on a captured target video (additional input) with an image of a person (subject) to identify movement and position of the object).
Regarding claim 7, Hibbs teaches a passive magnetic detection and discrimination method for detecting a magnetized object ([0010, 0015, 0045]; a passive magnetic detection system to detect ferrous (magnetized) objects and discriminate different kinds of objects), comprising:
providing at least one sensing structure having a plurality of magnetic inductive sensors arranged on a rigid framework (Fig. 1; [0026]; a rigid structure/gateway 4 (framework) with the induction sensors 10-19 contained (arranged) on a frame 38);
providing at least one screening area defined by the at least one sensing structure (Fig. 1; [0026] the structure is a security screening structure through which people must pass through (screening area)), whereby the plurality of magnetic inductive sensors are configured to respond to the magnetized object passing thereby ([0029]; the magnetic induction sensors distinguish (configured to respond) a magnetic object as it passes through the gateway);
providing a video camera for capturing an image or video of a subject with the magnetized object passing through the screening area to assist the system with discriminating whether the magnetized object is a threat ([0029, 0046]; a video camera capturing video footage of a person (subject) responsible for transporting the magnetized object as it passes through the gateway for the purpose of identifying the person transporting an unauthorized object such as a gun (discriminating a threat));
operatively connecting and configuring a processor (Fig. 3; [0029, 0033, 0042]; a CPU 96) and a memory (Fig. 3; [0029, 0033, 0042]; memory 97) to the plurality of sensors to receive data corresponding to amplitude waveforms created in each of the plurality of sensors by the magnetized object (Fig. 3; [0029, 0033, 0042]; a CPU 96 and memory 97 measure the response of each of the sensors comprising an amplitude of a time-varying (waveform) signal of the magnetic object); and
based on characteristic waveforms created by the magnetized object passing by the plurality of sensors, detecting and discriminating the magnetized object ([0028-0029]; based on the amplitude of time-varying signals produced (created) by the magnetized object passing through the gateway comprising the sensors, the system detects and distinguishes (discriminates) a small object from a physically larger object); and
identification of the magnetized object based on the characteristic waveforms created by the magnetized object ([0028-0029]; distinguish a small magnetic object from a physically larger object (identification) based on the amplitude of time-varying signals produced by the magnetized object).
Hibbs does not specifically teach utilizing an artificial intelligence or machine learning module to improve identification of the object.
However, Dreesen does teach utilizing an artificial intelligence or machine learning module to improve identification of the object ([0122, 0205]; a machine learning model using the processor is used to identify movement and position of an object (improve identification).
It would have been obvious before the effective filing date of the claimed invention to modify the passive magnetic detection system for security screening of Hibbs by implementing the teachings of Dreesssen regarding utilizing an artificial intelligence or machine learning module to improve identification of the object; for the benefit of eliminating background and motion isolation to improve object edge detection, thereby improving the accuracy of object identification and prevent false positive identification (See Dreessen; [0102]).
Regarding claim 8, the combination of Hibbs and Dreessen teaches the method of claim 7, wherein Hibbs further teaches further comprising positioning and orienting the plurality of sensors on the rigid framework to discriminate between different types of magnetized objects (Fig. 1; [0029-0032]; sensors 10-19 are strategically placed (positioned) on the frame 38 with a spacing and orientation to detect unauthorized items and detect and distinguish a small object from a physically larger object).
Regarding claim 9, the combination of Hibbs and Dreessen teaches the method of claim 7, wherein Hibbs further teaches wherein the rigid framework is at least partially non-metallic ([0026]; “gateway 4 includes a frame 38 which can be formed in many ways and of various materials”; which would include non-metallic materials).
Regarding claim 11, the combination of Hibbs and Dreessen teaches the method of claim 7, wherein Hibbs further teaches further comprising correlating the image or video of the subject with locational data of the magnetized object calculated from data corresponding to amplitude waveforms created by the sensors to flag a location of the magnetized object in the image or video ([0010, 0028, 0046]; capturing video footage of the person and using (correlating) the magnetic signals from the sensors that decrease relative to distance from the object (locational data) to give an indication (flag) of the actual location of a detected ferrous item on the body and relative to the subject possessing the item).
Hibbs does not specifically teach 3D locational data calculated from sensor data.
However, Dreessen does teach 3D locational data calculated from sensor data ([0059, 0121, 0122]; automatically selecting points where a location of an identified object in the target video of a 3D body model of the subject matches a location of a corresponding object the subject video captured by cameras (sensor)).
It would have been obvious before the effective filing date of the claimed invention to modify the passive magnetic detection system for security screening of Hibbs by implementing the teachings of Dreesssen regarding 3D locational data calculated from sensor data; for the benefit of providing a more accurate picture to security personnel of where an object representing a potential threat is located on a person’s body.
Regarding claim 12, the combination of Hibbs and Dreessen teaches the method of claim 7, wherein Dressen further teaches further comprising providing a captured image or video of a subject as an additional input to an artificial intelligence or machine learning module to improve system identification and discrimination of a magnetized object ([0115, 0119, 0122]; the machine learning model is used on a captured target video (additional input) with an image of a person (subject) to identify movement and position of the object).
Claim(s) 4 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Hibbs in view of Dreessen in further view of Frankhauser et al. WO 2016/120379 (Hereinafter Frankhauser; Copy Provided by Examiner).
Regarding claim 4, the combination of Hibbs and Dreessen teaches the system of claim 1, but not specifically wherein the rigid framework of the sensing structure hides the number, location, and orientation of the magnetic sensors such that the screening area for detection of subjects with magnetized objects passing by is covert.
However, Frankhauser does teach wherein the rigid framework of the sensing structure hides the number, location, and orientation of the magnetic sensors such that the screening area for detection of subjects with magnetized objects passing by is covert (Fig. 3; [0164, 0165]; a security checkpoint housing 302 (structure) comprising hidden equipment including sensors is concealed (hides the number, location and orientation) by a one-way mirror 306).
It would have been obvious before the effective filing date of the claimed invention to modify the combination of Hibbs and Dreessen by implementing the teachings of Frankhauser regarding wherein the rigid framework of the sensing structure hides the number, location, and orientation of the magnetic sensors such that the screening area for detection of subjects with magnetized objects passing by is covert; for the benefit of automatically detecting an object when a person is not aware of passing through a security structure.
Regarding claim 10, the combination of Hibbs and Dreessen teaches the method of claim 7, but not specifically further comprising hiding the number, location, and orientation of the magnetic sensors in the rigid framework of the sensing structure, such that the screening area for detection of subjects with magnetized objects passing by is covert.
However, Frankhauser does teach further comprising hiding the number, location, and orientation of the magnetic sensors in the rigid framework of the sensing structure, such that the screening area for detection of subjects with magnetized objects passing by is covert (Fig. 3; [0164, 0165]; a security checkpoint housing 302 (structure) comprising hidden equipment including sensors is concealed (hides the number, location and orientation) by a one-way mirror 306).
It would have been obvious before the effective filing date of the claimed invention to modify the combination of Hibbs and Dreessen by implementing the teachings of Frankhauser regarding further comprising hiding the number, location, and orientation of the magnetic sensors in the rigid framework of the sensing structure, such that the screening area for detection of subjects with magnetized objects passing by is covert; for the benefit of automatically detecting an object when a person is not aware of passing through a security structure.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Lanter US 2019/0003908 - A sensor device includes a base element extending in an axial direction and a first magneto elastic active region representing a first longitudinal section of a surface of the base element.
DeGois US 2021/0278245 - A magnetic sensor system includes a magnet and a sensor device.
Brooks et al. US 2016/0245072 - Methods for determining a distance from a drilling well to a magnetized target well include acquiring magnetic field measurements from the drilling well.
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/RAUL J RIOS RUSSO/Examiner, Art Unit 2858