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 Objections
Claim 10 is objected to because of the following informalities:
Claim 10 currently recites:
The system of claim 1, comprising:
a gateway device including a first communication circuit configured to communicate with each insect trap of the insect traps; and the insect traps communicatively coupled to the gateway device, the insect traps each including:
the board including the sticky surface configured to trap insects;
a light source configured to emit a light for attracting insect to the sticky surface;
a monitoring device including the camera; and
a second communication circuit configured to communicate with the first communication circuit.
Where there is currently no semicolon present between the light source limitation and monitoring device limitation. The Examiner recommends that the Applicant reviews the claim language to determine if a semicolon between the two limitations is appropriate (as underlined above).
Appropriate correction is required.
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 1-25 are rejected under 35 U.S.C. 101 because the claimed invention is
directed to an abstract idea without reciting elements that amount to significant more than
the abstract idea. The rationale for this rejection, under MPEP § 2106, for this finding is
explained below.
Step 1: Under step 1, the claims are analyzed to determine if the claim is directed to a
process, machine, article of manufacture, or composition of matter. For the claims in question,
claims 1-13 are directed towards a system (i.e., a machine), and claims 14-25 are directed towards a method (i.e., a process).
Step 2A, Prong 1: Under step 2A, prong 1, the claims are evaluated to determine if the
claim recites a judicial exception, which includes the laws of nature, physical phenomena, or an
abstract idea. For independent claim 1 (and corresponding independent claim 14), the limitations regarding analyzing a grayscale image to determine a status information (i.e., a measure of concentration of insects) of an adhesive board are directed towards a mental process. For a given grayscale image, an individual can reasonably determine a concentration of insects in the image by visually counting the number of insects present, and furthermore determine a concentration by using a physical aid to calculate the area of the surface present in the image.
Step 2A, Prong 2: Under step 2A, prong 2, the claims are evaluated to determine
whether the claim as a whole integrates the recited judicial exception into a practical application
of the exception (see MPEP 2106.04(d)). The examiner notes that MPEP 2106.05(a) -(c) and (e)
generally concern limitations that are indicative of integration, whereas 2106.05(f)-(h) generally
concern limitations that are not indicative of integration.
In regards to claims 1 and 14, the additional limitations of utilizing a camera and image processor to generate a grayscale image are recited at a high level of generality and are generic computing components and/or extra-solution activity, and do not constitute integration in to a practical application or significantly more (see MPEP 2106.05 (f), (g), (h)).
In regards to dependent claims 2-13 and 15-25, the additional limitations are broadly recited and further disclose steps used to perform the judicial exception without any clear indication or detail which would indicate integration into a practical application as noted in MPEP 2106.05(a) or MPEP 2106.05(e). Therefore, the additional limitations of claims 2-13 and 15-25 do not constitute integration ion into a practical application.
The examiner emphasizes MPEP 2106.05(a), which states that a limitation is indicative of integration into a practical application if the limitation identifies a manner in which an improvement is explicitly and specifically achieved and recited in the claims. The current claim language all are recited at a high level of generality which do not serve to integrate the limitations in view of MPEP 2106.05(f), and furthermore nothing precludes the current limitations from being interpreted under the mental processes grouping.
Step 2B: Under step 2B, the claims are evaluated as a whole to determine if it amounts to
significantly more than the recited exception (i.e., whether any additional element, or
combination of additional elements, adds an inventive concept to the claim). The considerations
of step 2A, prong 2 and step 2B overlap, but differ in that 2B also requires considering the claim
as a whole/combination of limitations, and with reference to MPEP 2106.05(d) whether the
claims feature any “specific limitation(s) other than what is well - understood, routine,
conventional activity in the field” (WURC). The examiner asserts that, even when considered in
combination, the additional elements of claims 1-25 represent mere instruction to apply a mental
process (determining a measure of concentration of insects in an image) at a high level of generality that is generally linked to the field of applying image analysis techniques for object detection, and therefore does not provide a specifically recited inventive concept.
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.
Claims 1, 7-8, 10-11, 13-19, and 21 are rejected as being unpatentable over Hou (CN 112471103; hereinafter “Hou”) in view of Khir and Pan (US 2023/0129551; hereinafter “Khir”).
Regarding Claim 1, Hou discloses a system for insect control using insect traps each including a board having a sticky surface, the system comprising (see Fig. 1, Fig. 3):
a camera configured to take a photograph showing the sticky surface of the board of each insect trap of the insect traps and to generate an image file representing the photograph (Page 2, Hou discloses a camera which can obtain a picture of an insect catching plate, wherein the insect catching plate consists of an adhesive surface.); and
an image processor communicatively coupled to the camera and configured to (see Fig. 3, Page 2):
analyze the sticky surface (Page 2, Hou discloses analyzing the gray value of the image information, and checking if the gray value exceeds a threshold to determine the concentration of winged insects present on the trap.).
Hou does not explicitly disclose generate a grayscale image of the sticky surface by processing the image file; and analyze the grayscale image.
Khir discloses generate a grayscale image of the sticky surface by processing the image file; and analyze the grayscale image ([0051], Khir discloses converting an image into greyscale in order to determine an insect count).
Hou and Khir are considered to be analogous to the claimed invention as they are in the same field of using image processing techniques to measure and analyze insect counts. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hou such that the gray value used to determine a concentration of winged insects is obtained based on the grayscale image produced by Khir. The motivation for this combination being the explicit generation of a grayscale image, which can aid in improving computational efficiency and accuracy.
Claim 14 is the method claim corresponding to claim 1, and is similarly rejected (see Page 2).
Regarding Claim 7, the current combination of Hou in view of Khir teaches the system of claim 1.
The current combination of Hou in view of Khir does not explicitly teach wherein the image processor is configured to perform, by analyzing the image file, at least one of classifying the insects on the sticky surface or counting the insects on the sticky surface.
Khir further discloses wherein the image processor is configured to perform, by analyzing the image file, at least one of classifying the insects on the sticky surface or counting the insects on the sticky surface ([0052], Khir discloses determining a count of insects in an image.).
It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to further modify the invention of Hou in view of Khir such that it incorporated the explicit counting disclosure provided by Khir. The motivation for this combination being the ability to generate and output a quantifiable measure of the number of insects present on a trap, which can be useful for further downstream processing and calculations.
Regarding Claim 8, Hou in view of Khir teaches the system of claim 1, comprising a monitoring device in the each insect trap, the monitoring device including the camera and the image processor (Page 2, Hou discloses an insect trapping device including a microcomputer and camera.).
Regarding Claim 10, Hou in view of Khir teaches the system of claim 1, comprising:
a gateway device including a first communication circuit configured to communicate with each insect trap of the insect traps; and the insect traps communicatively coupled to the gateway device (Fig. 1, Page 2, Hou discloses a gateway alarm apparatus connected to an insect trapping device), the insect traps each including:
the board including the sticky surface configured to trap insects (Page 2, Hou discloses an insect trapping device including an insect trapping plate made with an adhesive.);
a light source configured to emit a light for attracting insect to the sticky surface (Page 2, Hou discloses an insect trapping device which includes a light ray attracting device.)
a monitoring device including the camera; and a second communication circuit configured to communicate with the first communication circuit (Page 2, Hou discloses an insect trapping device including a camera, microcomputer, and carrier transmitter.).
Regarding Claim 11, Hou in view of Khir teaches the system of claim 10, wherein the gateway device comprises the image processor, and the second communication circuit is configured to transmit the image file to the image processor through the first communication circuit (Pages 2-3, Fig. 5, Hou discloses a gateway device including a microprocessor, which can receive a high frequency signal from the insect trapping device.).
Regarding Claim 13, Hou in view of Khir teaches the system of claim 10, further comprising a control center communicatively coupled to the gateway device via a telecommunication network, and wherein the first communication circuit is further configured to transmit results of the analysis of the grayscale image to the control center (Page 3, Hou discloses sending data from a gateway device to a server.).
Regarding Claim 15, Hou in view of Khir teaches the method of claim 14, further comprising:
placing the insect traps in various locations ([0030-0031], Khir discloses placing several smart traps in different locations.);
positioning a camera in each insect trap of the insect traps; and orienting the camera to take the photograph covering the entire board of the each insect trap (Page 2, Hou discloses an insect trap consisting of a camera which obtains images of an insect trapping plate.).
Regarding Claim 16, Hou in view of Khir teaches the method of claim 15, further comprising communicating with the cameras using a gateway device configured to wirelessly communicate with each insect trap of the insect traps (Fig. 1, Page 2, Hou discloses a gateway alarm apparatus connected to an insect trapping device).
Regarding Claim 17, Hou in view of Khir teaches the method of claim 16, further comprising including the image processor in the gateway device (Fig. 5, Hou discloses a gateway device including a microprocessor.).
Regarding Claim 18, Hou in view of Khir teaches the method of claim 16, further comprising including the camera and the image processor in each insect trap of the insect traps (Page 2, Hou discloses an insect trapping device including a microcomputer and camera.).
Regarding Claim 19, Hou in view of Khir teaches the method of claim 16, further comprising transmitting the status information from the gateway device to a remote control center via a telecommunication network (Page 3, Hou discloses sending data from a gateway device to a server.).
Regarding Claim 21, Hou in view of Khir teaches the method of claim 14, wherein generating the grayscale image comprises:
cropping the photograph into an image showing only the sticky surface ([0049-0050], Khir discloses cropping an image to remove extraneous details.); and
converting the image into the grayscale image by extracting the black and white components of the image showing only the sticky surface ([0051], Khir discloses converting an image into greyscale in order to determine an insect count).
Claims 2-3 and 22 are rejected as being unpatentable over Hou in view of Khir in view of Bisberg et al. (US 2019/0034736; hereinafter “Bisberg”)
Regarding Claim 2, Hou in view of Khir teaches the system of claim 1
Hou in view of Khir does not explicitly teach wherein the image processor is configured to identify the insects on the sticky surface by analyzing each pixel of the grayscale image to determine a numeric value representing a shade of gray for that pixel and indicating presence of an insect for each pixel when the numeric value exceeds a threshold.
Bisberg teaches wherein the image processor is configured to identify the insects on the sticky surface by analyzing each pixel of the grayscale image to determine a numeric value representing a shade of gray for that pixel and indicating presence of an insect for each pixel when the numeric value exceeds a threshold ([0073-0075], Bisberg discloses converting an image to grayscale and performing a thresholding process based on a minThreshold and maxThreshold in order to identify an insect of interest.).
Hou, Khir, and Bisberg are considered to be analogous to the claimed invention as they are in the same field of using image processing techniques to measure and analyze insects. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hou in view of Khir such that it incorporates the thresholding logic disclosed by Bisberg. The motivation for this combination being the ability to tune the threshold used to identify insects, therefore improving the accuracy of insect detection.
Regarding Claim 3, Hou in view of Khir in view of Bisberg teaches the system of claim 2, wherein the image processor is configured to determine a percentage of the pixels for which the numeric values exceed the threshold (Page 2, Hou discloses when a gray value exceeds a threshold B, the insect trapping plate is completely filled (i.e., 100%).).
Regarding Claim 22, Hou in view of Khir teaches the method of claim 14, wherein analyzing the grayscale image comprises: (Page 2, Hou discloses when a gray value exceeds a threshold B, the insect trapping plate is completely filled (i.e., 100%).).
Hou in view of Khir does not explicitly teach analyzing each pixel of the grayscale image to determine a numeric value representing a shade of gray for that pixel.
Bisberg teaches analyzing each pixel of the grayscale image to determine a numeric value representing a shade of gray for that pixel. ([0073-0075], Bisberg discloses converting an image to grayscale and performing a thresholding process based on a minThreshold and maxThreshold in order to identify an insect of interest.).
Hou, Khir, and Bisberg are considered to be analogous to the claimed invention as they are in the same field of using image processing techniques to measure and analyze insects. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hou in view of Khir such that it incorporates the thresholding logic disclosed by Bisberg. The motivation for this combination being the ability to tune the threshold used to identify insects, therefore improving the accuracy of insect detection.
Claim 4 is rejected as being unpatentable over Hou in view of Khir in view of Selvig and O’Donnell (US 2019/0327951; hereinafter “Selvig”).
Regarding Claim 4, Hou in view of Khir teaches the system of claim 1.
Hou in view of Khir does not explicitly teach wherein the image processor is configured to generate a saturation alarm in response to the measure of the concentration of insects on the sticky surface exceeding a saturation threshold, and the saturation threshold indicates a need for replacing the board.
Selvig discloses wherein the image processor is configured to generate a saturation alarm in response to the measure of the concentration of insects on the sticky surface exceeding a saturation threshold, and the saturation threshold indicates a need for replacing the board ([0055], Selvig discloses triggering an alarm when a threshold insect count is exceeded such that a technician can come service the insect trap.).
Hou, Khir, and Selvig are considered to be analogous to the claimed invention as they are in the same field of using image processing techniques to measure and analyze insect counts. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hou in view of Khir such that it incorporates the alarm system provided by Selvig. The motivation for this combination being the ability to alert relevant individuals when a trap is no longer effective.
Claim 5 is rejected as being unpatentable over Hou in view of Khir in view of Bjerge et al. (“Accurate detection and identification of insects from camera trap images with deep learning”, DOI: https://doi.org/10.1371/journal.pstr.0000051, Publication Year: 2023; hereinafter “Bjerge”).
Regarding Claim 5, Hou in view of Khir teaches the system of claim 1.
Hou in view of Khir does not explicitly teach wherein the image processor is configured to determine a rate of change of the concentration of insects on the sticky surface over time.
Bjerge discloses wherein the image processor is configured to determine a rate of change of the concentration of insects on the sticky surface over time (Fig. 8, Bjerge discloses measuring the number of detections within one square meter (i.e., a concentration) over time. The Examiner notes that the slope of each curve shown in Fig. 8 represents the claimed “rate of change”.).
Hou, Khir, and Bjerge are considered to be analogous to the claimed invention as they are in the same field of using image processing techniques to measure and analyze insect counts. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hou in view of Khir such that it incorporates rate of concentration change provided by Bjerge. The motivation for this combination being the ability to note changes that occur over time as opposed to just at a singular moment.
Claim 6 is rejected as being unpatentable over Hou in view of Khir in view of Bjerge in view of Gilbert and Metcalfe (US 2015/0351336; hereinafter “Gilbert”).
Regarding Claim 6, Hou in view of Khir in view of Bjerge teaches the system of claim 5.
Hou in view of Khir in view of Bjerge does not explicitly teach wherein the image processor is configured to generate an infestation alarm in response to the rate of change of the insect concentration exceeding an infestation threshold, and the infestation threshold indicates a sign of insect infestation.
Gilbert teaches wherein the image processor is configured to generate an infestation alarm in response to the rate of change of the insect concentration exceeding an infestation threshold, and the infestation threshold indicates a sign of insect infestation ([0074], [0127-0130], Gilbert discloses deriving infestation tracking data based on trap information collected over time, and consequently delivering an alert when the infestation parameter meets a threshold.).
Hou, Khir, Bjerge, and Gilbert are considered to be analogous to the claimed invention as they are in the same field of utilizing insect traps for analyzing insects. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hou in view of Khir in view of Bjerge such that it incorporates the infestation alarm logic disclosed by Gilbert. The motivation for this combination being the ability to notify a user when an infestation is occurring.
Claims 9 and 20 are rejected as being unpatentable over Hou in view of Khir in view of Marka et al. (US 2019/0000059; hereinafter “Marka”).
Regarding Claim 9, Hou in view of Khir teaches the system of claim 8.
Hou in view of Khir does not explicitly teach wherein the monitoring device further comprises an ambient light sensor configured to sense a measure of an ambient light, and the image processor is configured to analyze the image file using the sensed measure of the ambient light.
Marka discloses wherein the monitoring device further comprises an ambient light sensor configured to sense a measure of an ambient light, and the image processor is configured to analyze the image file using the sensed measure of the ambient light ([0082], Marka discloses an environment sensor which can detect ambient light, and consequently adjust the lighting from a light source (which is used to set the light conditions of an image).).
Hou, Khir, and Marka are considered to be analogous to the claimed invention as they are in the same field of using image processing techniques to measure and analyze insect counts. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hou in view of Khir such that it incorporates the ambient light sensor disclosed by Marka. The motivation for this combination being the ability to account for changes in environmental lighting which may affect image processing.
Regarding Claim 20, Hou in view of Khir teaches the method of claim 14.
Hou in view of Khir does not explicitly teach further comprising sensing a measure of an ambient light in the each insect trap, and wherein at least one of the generating the grayscale image or the analyzing the grayscale image comprises using the measure of an ambient light to compensate an effect of the ambient light on the photograph.
Marka discloses further comprising sensing a measure of an ambient light in the each insect trap, and wherein at least one of the generating the grayscale image or the analyzing the grayscale image comprises using the measure of an ambient light to compensate an effect of the ambient light on the photograph ([0082], Marka discloses an environment sensor which can detect ambient light, and consequently adjust the lighting from a light source (which is used to set the light conditions of an image).).
Hou, Khir, and Marka are considered to be analogous to the claimed invention as they are in the same field of using image processing techniques to measure and analyze insect counts. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hou in view of Khir such that it incorporates the ambient light sensor disclosed by Marka. The motivation for this combination being the ability to account for changes in environmental lighting which may affect image processing.
Claim 12 is rejected as being unpatentable over Hou in view of Khir in view of Gilbert.
Regarding Claim 12, Hou in view of Khir teaches the system of claim 10.
Hou in view of Khir does not explicitly teach comprising a private edge network connecting the gateway device and the insect traps and configured to allow the second communication circuit of each insect trap of the insect traps to communicate with the first communication circuit.
Gilbert discloses comprising a private edge network connecting the gateway device and the insect traps and configured to allow the second communication circuit of each insect trap of the insect traps to communicate with the first communication circuit ([0040], Gilbert discloses a mesh network to propagate data between an insect detection module and a gateway device.).
Hou, Khir, and Gilbert are considered to be analogous to the claimed invention as they are in the same field of utilizing insect traps and a gateway device. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hou in view of Khir such that it incorporates the explicit network communication structure disclosed by Gilbert. The motivation for this combination being the ability to have a plurality of devices be able to communicate with each other to share information.
Claim 23 is rejected as being unpatentable over Hou in view of Khir in view of Bisberg in view of Selvig.
Regarding Claim 23, Hou in view of Khir in view of Bisberg teaches the method of claim 22.
Hou in view of Khir in view of Bisberg does not explicitly teach generating a saturation alarm in response to the measure of the concentration of insects on the sticky surface exceeding a saturation threshold, the saturation threshold indicating a need for replacing the board.
Selvig discloses generating a saturation alarm in response to the measure of the concentration of insects on the sticky surface exceeding a saturation threshold, the saturation threshold indicating a need for replacing the board. ([0055], Selvig discloses triggering an alarm when a threshold insect count is exceeded such that a technician can come service the insect trap.).
Hou, Khir, Bisberg, and Selvig are considered to be analogous to the claimed invention as they are in the same field of using image processing techniques to measure and analyze insect counts. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hou in view of Khir in view of Bisberg such that it incorporates the alarm system provided by Selvig. The motivation for this combination being the ability to alert relevant individuals when a trap is no longer effective.
Claim 24 is rejected as being unpatentable over Hou in view of Khir in view of Bisberg in view of Bjerge.
Regarding Claim 24, Hou in view of Khir in view of Bisberg teaches the method of claim 22.
Hou in view of Khir in view of Bisberg does not explicitly teach determining a rate of change of the concentration of insects on the sticky surface over time.
Bjerge discloses determining a rate of change of the concentration of insects on the sticky surface over time. (Fig. 8, Bjerge discloses measuring the number of detections within one square meter (i.e., a concentration) over time. The Examiner notes that the slope of each curve shown in Fig. 8 represents the claimed “rate of change”.).
Hou, Khir, Bisberg, and Bjerge are considered to be analogous to the claimed invention as they are in the same field of using image processing techniques to measure and analyze insect counts. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hou in view of Khir in view of Bisberg such that it incorporates rate of concentration change provided by Bjerge. The motivation for this combination being the ability to note changes that occur over time as opposed to just at a singular moment.
Claim 25 is rejected as being unpatentable over Hou in view of Khir in view of Bisberg in view of Bjerge in view of Gilbert.
Regarding Claim 25, Hou in view of Khir in view of Bisberg in view of Bjerge teaches the method of claim 24.
Hou in view of Khir in view of Bisberg in view of Bjerge does not explicitly teach generating an infestation alarm in response to the rate of change exceeding an infestation threshold, the infestation threshold indicating a sign of insect infestation.
Gilbert teaches generating an infestation alarm in response to the rate of change exceeding an infestation threshold, the infestation threshold indicating a sign of insect infestation ([0074], [0127-0130], Gilbert discloses deriving infestation tracking data based on trap information collected over time, and consequently delivering an alert when the infestation parameter meets a threshold.).
Hou, Khir, Bisberg, Bjerge, and Gilbert are considered to be analogous to the claimed invention as they are in the same field of utilizing insect traps for analyzing insects. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hou in view of Khir in view of Bisberg in view of Bjerge such that it incorporates the infestation alarm logic disclosed by Gilbert. The motivation for this combination being the ability to notify a user when an infestation is occurring.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Janét et al. (US 2020/0107533)
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PROMOTTO TAJRIAN ISLAM whose telephone number is (703)756-5584. The examiner can normally be reached Monday - Friday 8:30 am - 5:00 pm EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chan Park can be reached at (571) 272-7409. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/PROMOTTO TAJRIAN ISLAM/Examiner, Art Unit 2669 /CHAN S PARK/Supervisory Patent Examiner, Art Unit 2669
Prosecution Insights