DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Claims 24-32, 34-37, 39 are pending.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 39 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 39 recites the limitation “an unmanned vehicle” in line 2. However, claim 37, which claim 39 depends from and includes all the limitations of, claims “an unmanned vehicle” in line 2. It is not clear if the “an unmanned vehicle” of claim 39 is a separate vehicle from the one claimed from claim 37 or the same vehicle. The scope of the claim could not be determined and is considered indefinite.
Claim 39 recites the limitation “a GNSS receiver” in line 3. However, claim 37, which claim 39 depends from and includes all the limitations of, claims “a GNSS receiver” in line 23. It is not clear if the receiver of claim 39 is a separate receiver from the one claimed from claim 37 or the same receiver. The scope of the claim could not be determined and is considered indefinite.
Claim 39 recites the limitation “a repellence sub-system” in line 4. However, claim 37, which claim 39 depends from and includes all the limitations of, claims “a repellence sub-system” in line 3. It is not clear if the “a repellence sub-system” of claim 39 is a separate repellence sub-system from the one claimed from claim 37 or the same repellence sub-system. The scope of the claim could not be determined and is considered indefinite.
Claim Rejections - 35 USC § 103
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 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.
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) 24-32, 34, 35, 37, 39 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chung et al. [KR 20170054808A] in view of Gordon et al. [US 20170238505].
As to claim 24. Chung discloses A repellence system for repelling animals, wherein the repellence system comprises:
an unmanned vehicle, [fig. 1, 0028] drone 100, comprising an imaging device arranged to generate image data, [0034] camera 130, and one or more deterrence devices arranged to carry out deterrence actions for repelling animals, [0035] retracting unit 140; and
a repellence sub-system, [0039] control unit 200 having one or more processors and memory storing instructions for execution by the one or more processors, [0048-0051] analyzing image data and issuing commands based on the result requires a processor to execute instructions stored in a memory, the repellence sub-system being configured to
a) control movement of the unmanned vehicle in a predetermined geographical surveillance area having a surveillance area border defining the predetermined geographical surveillance area, [fig. 3, 0048, 0050], the unmanned vehicle configured to patrol in the predetermined geographical surveillance area in autonomous manner, [0042-0049] the control unit 200 autonomously controls the operation of the drone 100 to deter animals from the area s;
b) receive image data of the predetermined geographical surveillance area from the imaging device during movement of the unmanned vehicle in the predetermined geographical surveillance area, [0050];
c) detect an animal in the image data with the repellence sub-system, [0051];
d) identify animal type of the detected animal in the image data with the repellence sub-system, [0051] identify the type of animal from the image;
e) control the unmanned vehicle towards the detected and identified animal in the predetermined geographical surveillance area, [0049, 0050]; and
f) provide type specific deterrence instructions to the one or more deterrence devices based on the identified animal type for carrying out type specific deterrence actions with the deterrence device, [0051], the type specific deterrence instructions being specific to the identified animal type, [0051];
wherein:
the surveillance area border is predetermined, [fig. 5, 0041] surveillance area predefined and sensors already installed around the area,
the repellence sub-system is configured to:
determine vehicle location information of the unmanned vehicle, [0047-0050] the control unit maneuvers the drone to required position, which requires the drone to recognize its own position;
control the movement of the unmanned vehicle in the predetermined geographical surveillance area based on the geographical location information of the predetermined geographical surveillance area and the vehicle location information, [0050] the control unit 200 controls the drone 100 based on the boundary location of the monitoring area s, and its own location which is required to calculate the moving direction of the drone with respect to the surveillance area, the unmanned vehicle configured to patrol in an autonomous manner in the predetermined geographical surveillance area based on the geographical location information of the predetermined geographical surveillance area, and the vehicle location information of the unmanned vehicle, [0047-0050]; and
determine location of the detected and identified animal in the predetermined geographical surveillance area in relation to the surveillance area border, [0050] and control movement of the unmanned vehicle towards the detected and identified animal in the predetermined geographical surveillance area in an approach direction in which the detected and identified animal is located between the unmanned vehicle and the surveillance area border for repelling the animal out of the predetermined geographical surveillance area, [0048-0050] since animals move in opposite direction of a detected threat, the drone moves to a position between the border of the monitored area s and the animals h as indicated in the path movement shown from fig. 3b to fig. 3c to move the animal out of the area s.
Chung fails to explicitly disclose wherein the border is predefined based on GNSS coordinates; the unmanned vehicle is provided with a GNSS receiver configured to receive GNSS signals from GNSS satellites; wherein determining the vehicle location information of the unmanned vehicle is based on the GNSS signals received in the GNSS receiver of the unmanned vehicle; wherein the predetermined geographical surveillance area is predetermined by the GNSS coordinates; wherein the location of the vehicle is determined by GNSS signals received in the GNSS receiver of the unmanned vehicle; wherein the patrol of the vehicle is based on the location information predetermined by the GNSS coordinates and the vehicle location information of the unmanned vehicle determined by GNSS signals received in the GNSS receiver of the unmanned vehicle wherein the identified type is the species of the animal.
Gordon teaches an unmanned aerial vehicle (UAV) 102 for generating geolocation exclusion zones of animals, [fig. 1, 0031], in a monitored area 504, [fig. 5, 0097], defined using map coordinates, [0040]; wherein the UAV tracks animals in the monitored location and provides map coordinates by using a GPS, [0040]; wherein the UAV’s path is determined based on the received coordinate information, [0067], and determines the type of animal based on the animal’s species, [0072]; wherein the system determines a specific deterrent for an identified animal based on the species of the animal, [0084].
It would have been obvious for one of ordinary skill in the art at the time of the filing of the claimed invention to combine the teachings of Chung with that of Gordon so that the system can use known characteristics of the animal species to determine the type of deterrent to use without harming the animal.
As to claim 25. Chung discloses The repellence system according to claim 24, wherein the repellence sub-system is configured to:
control movement of the unmanned vehicle in the predetermined geographical surveillance area in an autonomous manner, [0039]; or
control movement of the unmanned vehicle in the predetermined geographical surveillance area along a predetermined surveillance path, [0049, 0050]; or
maintain geographical location information of the predetermined geographical surveillance area and control movement of the unmanned vehicle in the predetermined geographical surveillance area; or
maintain geographical location information of the predetermined geographical surveillance area and control movement of the unmanned vehicle in the predetermined geographical surveillance area in an autonomous manner or along a predetermined surveillance path.
As to claim 26. Chung discloses The repellence system according to claim 24, wherein the repellence sub-system is configured to:
detect the animal in the image data with a computer vision algorithm, [0051]; or
input the image data as first input image data to a computer vision algorithm, and detect the animal in the first input image data with the computer vision algorithm, the computer vision algorithm being trained to detect animals in the first input image data; or
input the video image data as first input image data to a computer vision algorithm, and detect the animal in the first input image data with the computer vision algorithm by processing each frame of the video image data with the computer vision algorithm to detect the animal, the computer vision algorithm being trained to detect animals in the first input image data.
Chung fails to disclose wherein the computer vision algorithm being trained to detect animal in the image data.
Gordon teaches a camera system and method for monitoring animal activity that uses a computer vision algorithm, [0040] and a machine learning algorithm to classify and identify animal type in image data received from cameras, [0040]; wherein the type is determined by identifying the animal’s species, [0072].
It would have been obvious for one of ordinary skill in the art at the time of the filing of the claimed invention to combine the teachings of Chung with that of Gordon so that the system can use known algorithms to identify the animal species to reduce implementation cost of the system.
As to claim 27. Chung discloses The repellence system according to claim 24, wherein the repellence sub-system is configured to:
identify the animal species of the detected animal in the image data with an image identification algorithm, [0051]; or
input the image data as second input image data to an image identification algorithm, and identify animal species of the detected animal in the second input image data with the image identification algorithm, the image identification algorithm being trained to identify different animal species from the second input image data; or
input the video image data as second input image data to an image identification algorithm, and identify animal species of the animal in the second input image data with the image identification algorithm by processing one or more frames of the video image data with the image identification algorithm to identify animal species of the animal, the image identification algorithm being trained to identify different animal species from the second input image data.
Chung fails to disclose wherein the image identification algorithm being trained to identify different animal species from the image data.
Gordon teaches a camera system and method for monitoring animal activity that uses a computer vision algorithm, [0040] and a machine learning algorithm to classify and identify animal species in image data received from cameras, [0040].
It would have been obvious for one of ordinary skill in the art at the time of the filing of the claimed invention to combine the teachings of Chung with that of Gordon so that the system can use known algorithms to identify the animal species to reduce implementation cost of the system.
As to claim 28. Chung discloses The repellence system according to claim 24, wherein the repellence sub-system is configured to:
detect the animal and identify animal species of the detected animal in the image data with a computer vision algorithm, [0051]; or
input the image data as first input image data to a computer vision algorithm, and detect the animal and identify animal species of the detected animal in the first input image data with the computer vision algorithm, the computer vision algorithm being trained to detect animals and identify animal species in the first input image data; or
input the video image data as first input image data to a computer vision algorithm, and detect the animal and identify animal species of the detected animal in the first input image data with the computer vision algorithm by processing each frame of the video image data with the computer vision algorithm to detect the animal, the computer vision algorithm being trained to detect animals and identify animal species in the first input image data.
Chung fails to disclose wherein the computer vision algorithm being trained to detect animals and identify animal species in the image data.
Gordon teaches a camera system and method for monitoring animal activity that uses a computer vision algorithm, [0040] and a machine learning algorithm to classify and identify animal species in image data received from cameras, [0040].
It would have been obvious for one of ordinary skill in the art at the time of the filing of the claimed invention to combine the teachings of Chung with that of Gordon so that the system can use known algorithms to identify the animal species to reduce implementation cost of the system.
As to claim 29. Chung discloses The repellence system according to claim 24, wherein the one or more deterrence devices comprise:
a deterrence sound device arranged to generate species-specific deterrence sound action as the deterrence action in response to the species-specific deterrence instructions, [0051]; or
a deterrence ultrasound device arranged to generate species-specific deterrence ultrasound action as the deterrence action in response to the species-specific deterrence instructions; or
a deterrence light device arranged to generate species-specific deterrence light action as the deterrence action in response to the species-specific deterrence instructions; or
a deterrence sound device arranged to generate species-specific deterrence sound action and a deterrence light device arranged to generate species-specific deterrence light action as the deterrence actions in response to the species-specific deterrence instructions; or
a deterrence ultrasound device arranged to generate species-specific deterrence ultrasound action and a deterrence light device arranged to generate species-specific deterrence light action as the deterrence actions in response to the species-specific deterrence instructions; or
a deterrence ultrasound device arranged to generate species-specific deterrence ultrasound action and a deterrence sound device arranged to generate species-specific deterrence sound action as the deterrence actions in response to the species-specific deterrence instructions.
As to claim 30. Chung discloses The repellence system according to claim 29, wherein:
the repellence sub-system is configured to generate species-specific deterrence instructions based on the identification of the animal species of the detected animal, and provide the generated species-specific deterrence instructions to the one or more deterrence devices, [0051]; or
two or more animal species profiles are provided, each animal species profile comprising species-specific deterrence instructions specific to the respective animal species, the species-specific deterrence instructions comprising instructions to carry out species-specific deterrence actions with the one or more deterrence devices specific to the animal species,
the repellence sub-system being configured to
carry out the species-specific deterrence actions based on the species-specific deterrence instructions of the animal species profile corresponding the identified animal species of the detected animal, [0051], or
provide the species-specific deterrence instructions of the animal species profile corresponding the identified animal species of the detected animal to the one or more deterrence devices, and
operate the one or more deterrence devices based on the species-specific deterrence instructions corresponding the animal species profile of the identified animal species o the detected animal to generate species-specific deterrence actions with the one or more deterrence devices, [0051, 0064].
As to claim 31. Chung discloses The repellence system according to claim 24, wherein the one or more deterrence devices comprise the deterrence ultrasound device, [0035], the repellence sub-system being configured to:
carry out the species-specific deterrence actions based on the identified animal species of the detected animal, the species-specific deterrence instructions comprising the species-specific output, [0051]; or
generate species-specific deterrence instructions comprising a species-specific ultrasound frequency value for the deterrence ultrasound device based on the identified animal species of the detected animal, [0051],
provide the generated species-specific deterrence instructions to the deterrence ultrasound device, [0051], and
operate the deterrence ultrasound device with the species-specific output value of the species-specific deterrence instructions, [0051, 0052]; or
two or more animal species profiles are provided, each animal species profile comprising species-specific deterrence instructions specific to the respective animal species, the species-specific deterrence instructions comprising species-specific ultrasound frequency value to be utilized by the deterrence ultrasound device, and
the repellence sub-system being configured to
carry out the species-specific deterrence actions by utilizing the species-specific ultrasound frequency value in the deterrence ultrasound device based on the species-specific deterrence instructions of the animal species profile corresponding the identified animal species of the detected animal, or
provide the species-specific deterrence instructions of the animal species profile corresponding the identified animal species of the detected animal to the deterrence ultrasound devices, the species-specific deterrence instructions comprising a species-specific ultrasound frequency value, and
operate the deterrence ultrasound device with the species-specific ultrasound frequency value of the species-specific deterrence instructions of the animal species profile corresponding the identified animal species of the detected animal.
Chung fails to disclose wherein the deterrence device is an ultrasound device; wherein the deterrence action is carried out by utilizing a species-specific ultrasound frequency value in the deterrence ultrasound device; wherein the species-specific output is ultrasound frequency value.
Gordon teaches an unmanned aerial vehicle (UAV) 102 for generating geolocation exclusion zones of animals, [fig. 1, 0031], in a monitored area 504, [fig. 5, 0097], defined using map coordinates, [0040]; wherein the system determines the type of animal based on the animal’s species, [0072], and determines a specific deterrent for an identified animal based on the species of the animal, [0084]; wherein the deterrence generator generates a sound signal with a frequency specific to the identified animal species, [0052].
It would have been obvious for one of ordinary skill in the art at the time of the filing of the claimed invention to combine the teachings of Chung with that of Gordon so that the system can use known characteristics of the animal species to determine the type of deterrent to use without harming the animal.
As to claim 32. Chung discloses The repellence system according to claim 24, wherein the repellence sub-system is configured to:
control movement of the unmanned vehicle towards the detected and identified animal in the predetermined geographical surveillance area, [0049, 0050], and
initiate the species-specific deterrence actions with the one or more deterrence devices during the movement of the unmanned vehicle towards the detected and identified animal, [0051]; or
control movement of the unmanned vehicle towards the detected and identified animal in the predetermined geographical surveillance area and measure distance between the unmanned vehicle and the animal, and
initiate the species-specific deterrence actions with the one or more deterrence devices when the distance between the unmanned vehicle and the animal is less than or equal to a predetermined deterrence distance threshold value.
As to claim 34. Chung discloses The repellence system according to claim 33, wherein the repellence sub-system is configured to:
determine moving direction of the detected and identified animal based on the image data from the imaging device, [0050], control the unmanned vehicle towards the detected and identified animal based on the moving direction of the detected and identified animal in the predetermined geographical surveillance area, [0050]; or
determine location and moving direction of the detected and identified animal based on the image data from the imaging device, control the unmanned vehicle towards the detected and identified animal based on the location and moving direction of the detected and identified animal in the predetermined geographical surveillance area; or
determine location and moving direction of the detected and identified animal in the predetermined geographical surveillance area in relation to the surveillance area border based on the image data from the imaging device, control the unmanned vehicle towards the detected and identified animal based on the location and moving direction of the detected and identified animal in the predetermined geographical surveillance area in the approach direction in which the detected and identified animal is located between the unmanned vehicle and the surveillance area border for repelling the animal out of the predetermined geographical surveillance area; or
determine location and moving direction of the detected and identified animal in the predetermined geographical surveillance area in relation to the surveillance area border based on the image data from the imaging device, control the unmanned vehicle towards the detected and identified animal based on the location and moving direction of the detected and identified animal in the predetermined geographical surveillance area in the approach direction in which the detected and identified animal is located between the unmanned vehicle and the surveillance area border for repelling the animal out of the predetermined geographical surveillance area, and
redetermine the location and moving direction of the detected and identified animal in the predetermined geographical surveillance area in relation to the surveillance area border based on the image data from the imaging device, adjusting the approach direction (D) based on the redetermined location and moving direction of the detected and identified animal in the predetermined geographical surveillance area such that the detected and identified animal is located between the unmanned vehicle and the surveillance area border for repelling the animal out of the predetermined geographical surveillance area, [0050] the animal is tracked in relation to the outside of the monitoring area s.
As to claim 35. Chung discloses The repellence system according to claim 24, wherein the unmanned vehicle is an unmanned aerial vehicle, [fig. 1] drone 100.
As to claim 37. Is rejected using the same prior arts and reasoning as to that of claim 24.
As to claim 39. Is rejected using the same prior arts and reasoning as to that of claim 37.
Claim(s) 36 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chung in view of Gordon as applied to claim 1 above, further in view of Santana et al. [US 20200154694].
As to claim 36. The combination of Chung and Gordon fails to disclose The repellence system according to claim 35, wherein the repellence sub-system is configured to:
control movement of the unmanned aerial vehicle in the predetermined geographical surveillance area at a patrolling altitude, and
control the unmanned aerial vehicle to a repellence altitude as a response to c) detecting the animal in the image data, the repellence altitude being less than the patrolling altitude.
Santana teaches a livestock management system comprising UAVs 105 to deter livestock from exiting a predetermined area of interest AOI, [0027], using a computer vision algorithm, [0019]; wherein the system adjusts the altitude of the UAV to a lower altitude to deter the livestock, [0027], and follow the heard at a high altitude, [0028].
It would have been obvious for one of ordinary skill in the art at the time of the filing of the claimed invention to combine the teachings of the combination of Chung and Gordon with that of Santana so that the system can provide the deterrent effectively.
Response to Arguments
Applicant's arguments filed 03/09/2026 have been fully considered but they are not persuasive.
Argument 1: Chung does not teach the claimed GNSS network.
Response 1: In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
The Office Action is relying on the teachings of Gordon to teach the above limitation. Wherein one of ordinary skill in the art can easily incorporate the GPS receiver from the drone of Gordon to the drone of Chung as nothing but using a widely used and known method of tracking self-location accurately.
Argument 2: Gordon does not teach or suggest surveillance of having a surveillance border defining a predetermined surveillance area.
Response 2: In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
The Office Action is relying on the teachings of Chung to teach the above limitation.
Argument 3: Gordon’s reference to “map coordinates” and GPS-associated image information does not teach or suggest that “the surveillance area border is predetermined based on GNSS coordinates” or that the movement of the vehicle is based on GNSS coordinates.
Response 3: Gordon, [0040], teaches use “geolocation information, such as map coordinates, to generate exclusion zones”; wherein the vehicle 102 has a system 300 with a GPS that provide the map coordinates, and uses the map coordinates to steer the vehicle [0067].
According to the current applications specification, in [0021], “The geographical location information of the predetermined geographical surveillance area is determined with global navigation satellite system (GNSS) coordinates, such as Global Navigation System (GPS) coordinates.”
Conclusion
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/Benyam Haile/Primary Examiner, Art Unit 2688
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