DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Notice to Applicants
2. This communication is in response to the application filed on 10/22/2024.
3. Claims 1-20 are pending.
4. Limitations appearing inside {} are intended to indicate the limitations not taught by said prior art(s)/combinations.
Information Disclosure Statement
5. The information disclosure statement (IDS) submitted on 10/28/2024 has been considered by the examiner.
Claim Rejections - 35 USC § 101
6. 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.
7. Claims 1-20 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The analysis below follows Subject Matter Eligibility Test (See flowchart in MPEP 2106).
Step 1: Is the claim to a process, machine, manufacture or composition of matter? YES.
Step2A, Prong 1: Does the claim recite an abstract idea, law of nature, or natural phenomenon? YES. Claim 1 recites “A computer-implemented method comprising: identifying, by a computer executing a machine-learning model, a moveable object located within an area, wherein the machine-learning model is trained by applying the machine-learning model on historical data (1); identifying, by the computer executing the machine-learning model, movement of the object by a person (2); and in response to the movement of the object by a person, executing, by the computer executing the machine-learning model, a deterrence action. (3)” [emphasis added].
Limitation (1), (2), and (3) recite a mental process, directed toward the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)), and limitation (1) additional recites a mathematical calculation, directed toward the mathematical concepts grouping of abstract ideas (MPEP 2106.04(a)(2)). For the sake of compact prosecution and clarity, the examiner has treated limitation (1) as directed to a single abstract idea of a mental process. Specifically, a person can identify a movable object located within an area (e.g., after having been trained on historical data), and identify movement of the object by a person, and in response to the movement, execute a deterrence action. Specifically, a person could perform all such actions mentally (e.g., watch as a person approaches, watch as they pick up and/or move package, and give them a verbal warning).
Step2A, Prong 2: Does the claim recite an additional elements that integrate the judicial exception into a practical application? NO. Limitations (1) recites additional element “A computer-implemented method…”, “…by a computer executing a machine-learning model…”, and “…the machine-learning model is trained by applying the machine-learning model on historical data…”, which constitute a generic computer recitation (MPEP 2106.05(f)), mere instructions to apply the judicial exception to the field of machine learning (MPEP 2106.05(h)), and insignificant pre-solution data acquisition and training step that is well known and understood in the art (MPEP 2106.05(g)). Likewise, limitations (2), and (3) recite additional elements “…by the computer executing the machine-learning model…” which constitutes a generic computer recitation (MPEP 2106.05(f)), mere instructions to apply the judicial exception to the field of machine learning (MPEP 2106.05(h)).
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? NO. The claim’s additional elements, as stated in Prong 2, do not amount to significantly more than the judicial exception. Limitations (1), (2), and (3) lack sufficient structure to amount to significantly more than the judicial exception as described in Step2A. Furthermore, training machine learning to track objects is well-understood and routine within the industry. Therefore, limitations (1), (2), and (3) use well-understood, routine, and conventional activities previously known to the industry, specified at a high level of generality, to accomplish the judicial exception.
Claim 2 recites additional limitation “wherein identifying the moveable object includes tracking movement of the object into the area.”, which is directed toward the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)). Specifically, a person can track a movement of the object into the area (e.g., using a pen and paper). Claim 3 recites additional limitation “wherein identifying the moveable object includes determining an object category of the object.”, which is directed toward the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)). Specifically, a person can determine they category of object (e.g., a box, an envelope, a plastic container, etc.). Claim 4 recites additional limitation “wherein identifying the movement of the object by the person includes determining that the person has entered the area.”, which is directed toward the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)). Specifically, a person can identify if a person has entered the area (e.g., if a person enters the porch area where a package may be placed, etc.). Claim 5 recites additional limitation “wherein identifying the movement of the object by the person includes determining a safe region for the object.”, which is directed toward the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)). Specifically, a person can identify a safe region for the object (e.g., in field of view, out of view of street, out of adverse weather conditions, etc.). Claim 6 recites additional limitation “…wherein identifying the movement of the object by the person includes determining a direction of the movement.”, which is directed toward the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)). Specifically, a person can determine a direction of movement of an object by a person using a pen and paper. Claim 7 recites “executing the deterrence action includes determining that the direction of the movement is away from a building associated with the area.”, which is directed toward the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)). Specifically, a person can determine a direction of movement is away from the house, and execute a deterrence action (e.g., scream to drop the package). Claim 8 recites “wherein executing the deterrence action includes emitting one or more audiovisual signals.”, which is directed toward the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)). Specifically, a person can emit audiovisual signals (e.g., make hand gestures and speak). Claim 9 recites “wherein executing the deterrence action includes generating, by the computer executing the machine-learning model, the one or more audiovisual signals.”, which constitutes a generic computer recitation (MPEP 2106.05(f)) and mere instructions to apply the judicial exception to the field of machine learning (MPEP 2106.05(h)). Claim 10 recites “wherein executing the deterrence action includes determining one or more characteristics of the person.”, which is directed toward the mental process grouping of abstract ideas (MPEP 2106.04(a)(2)). Specifically, a person can identify one or more characteristics of a person (e.g., if they are wearing a uniform belonging to postal services, etc.). Claims 11-20 recites analogous limitations to claims 1-10, and analogous analysis is applicable to claims 11-20. The examiner specifically notes in Claim 11 “An apparatus comprising: an image sensor; and a processor executing a machine-learning model to...”, which constitutes a generic computer recitation (MPEP 2106.05(f)) and mere instructions to apply the judicial exception to the field of machine learning (MPEP 2106.05(h)), wherein the remainder of the limitations of claims 11-20 are analogous to claims 1-10.
At least for these reasons, claims 1-20 are ineligible under 35 U.S.C. 101.
Claim Rejections - 35 USC § 103
8. 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.
9. Claims 1, 3, 5, 8-11, 13, 15, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over W.O. Publication No. 2022/245751 to Khalili et al. (hereinafter Khalili), and further in view of U.S. Publication No. 2023/0282026 to Madden et al. (hereinafter Madden).
10. Regarding Claim 1, Khalili discloses a computer-implemented method comprising ([par. 0007, ln. 1-6] “… a method may identifying one or more package candidates from an image. The method may further include determining an analysis frame from the image based at least in part on the one or more package candidates and executing a shared classifier on the analysis frame, the shared classifier to predict identification of packages and objects within the analysis frame. Further, the method may include outputting a prediction of the identification of the packages and the objects based at least in part on the execution of the shared classifier.”, [par. 0030, ln. 1-6] “The system 102 may include memory 104 and one or more processors 106 coupled to the memory 104. The memory 104 may include one or more computer-readable media. In some embodiments, the computer-readable media may comprise non-transitory computer-readable media. The memory 104 may have one or more instructions stored thereon, wherein the instructions, when executed by the system 102, may cause the system 102 to perform one or more of the operations disclosed herein.”):
identifying, by a computer executing a machine-learning model, a moveable object located within an area ([par. 0062, ln. 1-13] “In 904, the system may execute a classifier on candidates. For example, the system may execute the classifier on the set of pixels within the candidates (which may be the set of pixels with the removed pixels and the added additional pixels from 210 through 218) to determine whether the area captured by the candidate includes a package. The classifier executed by the system may include a classification model that the system utilizes to predict if the areas captured in each of the candidates includes a package. The classification model may comprise a model produced by machine learning. The classification model may have been trained based on a training set and/or variation set to identify packages within the areas captured in each of the candidates. In some embodiments, the training of the classification model by the system may include supervised learning, where desired results for the elements within the training set and/or the variation set may be indicated to the system… the system may use any machine learning technique (such as random forests, support vector machine, artificial neural networks, or some other machine learning technique) to train the classification model.”), wherein the machine-learning model is trained by applying the machine-learning model on {historical} data ([par. 0062, ln. 1-13]);
identifying, by the computer executing the machine-learning model, movement of the object by a person ([par. 0067, ln. 1-11] “…the system may further determine whether there are any other objects that overlap with a predicted package when the system predicts that a package has been delivered. For example, the system may analyze the candidate to determine whether there are any other objects, such as individuals and/or animals within an area of the predicted package. The system may identify the individual and/or animals based on the shape of the objects, the movement of the objects, and/or other defining characteristics of the objects detected within the area of the predicted package… the system may identify an individual within the area of the predicted package, and may determine that the package is being carried by the individual. Based on the determination that the package is being carried by the individual, the system may determine that the package has not been delivered and determine not to initiate a notification in 910 based on the package not having been delivered.”); {and in response to the movement of the object by a person, executing, by the computer executing the machine-learning model, a deterrence action}.
Khalili does not specifically disclose wherein the model is trained using historical data, or wherein in response to the movement of the object by a person, executing a deterrence action. Specifically, Khalili only identifies if an object is being carried by a person (i.e., moved).
However, Madden specifically teaches wherein the machine learning model is trained by applying the machine learning model on historical data ([par. 0071, ln. 1-6] “…the monitoring system 110 may have a training phase. The training phase can be used to generate scene model data for storage in the scene model database 122, historical pickup data for storage in the historical pickup database 124, or both.”, [par. 0072, ln. 1-17] “…the training phase may be a period of multiple days or weeks. During the training phase, the monitoring system 110 can obtain images of all package pickups from the property 102. The monitoring system 110 can store images of pickup personnel and times of the pickups. The monitoring system 110 can also store locations of packages that are left for pickup during the training phase. For example, packages may be left for pickup at the porch 108, at a back door, or at a garage door of the property 102. In some examples, in addition to or instead of the training phase, the camera 104 and the monitoring system 110 can continuously record and store pickup times, personnel, and locations while in operation. The monitoring system 110 can analyze all pickups, or a selection of pickups… the monitoring system 110 can use electronic pickup notifications received from delivery services as ground truth labeling for the training data.”), and identifying movement of the object by a person, and in response to the movement of the object by a person, by the computer executing the machine-learning model, executing a deterrence action ([Fig. 2, see 12:00PM second image 216], [par. 0101, ln. 1-9] “FIG. 2 illustrates the example environment 100 in which monitoring system 110 can guard packages from pickup by unauthorized personnel using video. In the example of FIG. 2, a first image 205 shows two packages 211, 212 set out for delivery on the porch 108 at 7:30 am. A second image 216 shows a pickup person 203 approaching the property 102 at 12:00 pm. The pickup person 203 is driving an unmarked sedan 233 and is not wearing a uniform or a nametag.”, [par. 0102, ln. 1-13] “The package monitor 134 performs a verification process and determines that the pickup person 203 is unverified 240… 134 can determine that the pickup person 203 is unverified 240 based on determining that the pickup person 203 does not satisfy any verification criteria… 134 may determine that the sedan 233 does not display any logo or business name that matches an assigned delivery service… 134 may determine that the pickup person 203 is not wearing any uniform or nametag that corresponds to an assigned delivery service… 134 may determine that the pickup person 203 does not provide an accurate password or code.”, [par. 0103, ln. 1-12] “… 134 can determine that the pickup person 203 is unverified 240 based on determining that the pickup person 203 satisfies fewer than a required number of verification criteria. For example, the required number of verification criteria may be two verification criteria. The pickup person 203 may satisfy a first verification criterion by arriving within the expected pickup time window, but might not satisfy any second criterion. Thus, due to the pickup person 203 not satisfying at least the required number of verification criteria… 134 can determine that the pickup person 203 is unverified.”, [par. 0104, ln. 1-17] “When the pickup person 203 approaches the property 102… 134 can provide a warning 236 based on determining that the pickup person 203 is unverified 240. The warning 236 can include, for example, a verbal or visual prompt, e.g., challenge, presented through the signaling device 242. The prompt can include a request to provide a credential, e.g., by speaking the person's name, by speaking a password, or by presenting a visible code to the camera 104. If the pickup person 203 does not provide the requested credentials… 134 can provide an additional warning 236, e.g., including a verbal or textual instruction. The instruction may state, for example, “put the package down.” If the pickup person 203 picks up one of the packages without being verified… 134 can escalate the warning 236 to an alarm. The alarm can include, for example, a siren sound and/or a flashing light.”). One of ordinary skill in the art, before the effective filing date of the claimed invention, would recognize Khalili and Madden as within the same field of video processing for detecting and managing delivery packages, and as analogous to the claimed invention. Specifically, the motivation to combine is disclosed in Madden, wherein it prevents unauthorizes people from stealing packages ([par. 0101, ln. 1-9]). One of ordinary skill in the art, before the effective filing date of the claimed invention, would have combined the method of Khalili with the historical data training and package movement deterrence action of Madden through known means, with no change to their respective function, and the combination would had yielded nothing more than predicable results. Specifically, one of ordinary skill in the art would have combined the method of Khalili with the historical data training and package movement deterrence action of Madden such that the machine learning model of Khalili is trained using historical data and generates a deterrence action if an unauthorized individual is detected moving the package.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the method of Khalili with the historical data training and package movement deterrence action of Madden to obtain the invention as specified in claim 1.
11. Regarding Claim 3, a combination of Khalili and Madden teaches the method of claim 1. Khalili further discloses wherein identifying the moveable object includes determining an object category of the object ([par. 0067, ln. 1-11], [par. 0068, ln. 1-7] “…the classifier may include a classification model that the system utilizes to predict if an area within the predicted packages includes an individual or an animal. The classification model may be implemented with the same classification model as the classification model used for predicting the packages or may be a separate classification model from the classification model used for predicting the packages. The classification model may have been trained based on a training set and/or variation set to identify individuals and/or animals within the areas captured in each of the candidates.”). Specifically, one of ordinary skill in the art, before the effective filing date of the claimed invention, would recognize Khalili discloses wherein the movable objects can further be categorized as an animal or person. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the method of Khalili with the historical data training and package movement deterrence action of Madden to obtain the invention as specified in claim 3.
12. Regarding Claim 5, a combination of Khalili and Madden teaches the method of claim 1. Khalili does not specifically disclose wherein identifying the movement of the object by the person includes determining a safe region for the object.
However, Madden specifically teaches wherein identifying the movement of the object by the person includes determining a safe region for the object ([par. 0044, ln. 11-20] “For example, when a person leaves a package on the porch 108 for pickup, the camera 104 can perform video analysis to track the person placing the package, detect the package placed on the ground within the camera field of view, and estimate an outline of the package based on a region of pixels that have changed compared to the background… the camera 104, the monitoring system 110, or both, can employ an object detection and/or scene segmentation network for detecting and tracking packages.”, [par. 0059, ln. 1-21] “…the different services can have different deliveries scheduled at the property 102. The monitoring system 110 can utilize camera 104 and other sensors throughout the property 102, to coordinate the pickup and deliveries from the multiple different services… if a delivery person places the newly delivered package on top of a package to be picked up, or if the delivery person turned to leave without picking up a package for their retrieval… 110 might remind the delivery person that a package is out for pickup. In the former instance, the reminder can cause the person to place the newly delivered package somewhere that is not on top of a package to be picked up. In the latter instance, the reminder can cause the person to retrieve the package… 110 can guide the delivery services to place packages in different physical areas that can represent pickup and drop off for respective services.”, [par. 0060, ln. 1-12] “…the monitoring system 110 can direct the pickup and drop off of packages through multiple presentation devices such as auditory prompts, displayed images, messages sent to the delivery person's device, visual prompts, or a combination of these… 110 can outline an area on the front porch with a laser grid such that the delivery person knows where to drop off a package… 110 can project a laser onto a second package that is meant for pickup… 110 can send a message alert to the delivery person's mobile device that can include information about the package to be picked up.”, [par. 0061, ln. 1-19] “…the monitoring system 110 can process visual information about the packages in order to track the multiple packages… 110 can track shape, color, size, identifying features, logos, or a combination of these from the packages and can identify key features of the environment such as patio furniture, plants, lights, or other more temporary objects such as bags, toys, coolers, or more. The visual tracking of the packages and the environment can provide for more accuracy in determining the number of packages for pickup and drop off compared to other systems… 110 can prompt a delivery person to leave the package on the brown chair by providing an audio prompt such as “Please leave the package on the brown chair.”… 110 can turn on a light illuminating the brown chair if, for example, the delivery were occurring in low light conditions… 110 can utilize the environment and the number of packages to coordinate the pickup and drop off”, [par. 0062, ln. 1-8] “The monitoring system 110 can track packages for drop off and pickup. For example, in areas where there is not enough space and packages may be stacked upon one another… 110 can keep track of the stacks of packages… 110 can present a notification that indicates that a delivery person should retrieve the third package from the bottom of a pile and place a package for delivery on the top of the pile.”). The motivation to combine would have been obvious to one of ordinary skill in the art, in that by determining a safe location you can help prevent unauthorized individuals from taking packages and prevent package damage (e.g., placing it out of street view, prevent stacking of fragile packages, etc.). One of ordinary skill in the art, before the effective filing date of the claimed invention, would have combined the method of Khalili with the historical data training, package movement deterrence action, and safe location determination of Madden through known means, with no change to their respective function, and the combination would had yielded nothing more than predicable results. Specifically, one of ordinary skill in the art would have combined the method of Khalili with the historical data training, package movement deterrence action, and safe location determination of Madden such that the packages are placed in a determined safe region (e.g., during drop-off).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the method of Khalili with the historical data training, package movement deterrence action, and safe location determination of Madden to obtain the invention as specified in claim 5.
13. Regarding Claim 8, a combination of Khalili and Madden teaches the method of claim 1. Khalili does not specifically disclose wherein executing the deterrence action includes emitting one or more audiovisual signals.
However, Madden specifically teaches wherein executing the deterrence action includes emitting one or more audiovisual signals ([par. 0104, ln. 1-17]). The motivation to combine remains analogous to claim 1. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have combined the method of Khalili with the historical data training, package movement deterrence action, and audiovisual signals of Madden through known means, with no change to their respective function, and the combination would had yielded nothing more than predicable results. Specifically, one of ordinary skill in the art, in combining the method of Khalili with the historical data training and package movement deterrence action of Madden, would have further included the one or more audiovisual signals of Madden as part of the deterrence action.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the method of Khalili with the historical data training, package movement deterrence action, and audiovisual signals of Madden to obtain the invention as specified in claim 8.
14. Regarding Claim 9, a combination of Khalili and Madden teaches the method of claim 8. Khalili does not specifically teach executing the deterrence action includes generating, by the computer executing the machine-learning model, the one or more audiovisual signals.
However, Madden specifically teaches executing the deterrence action includes generating, by the computer executing the machine-learning model, the one or more audiovisual signals ([par. 0031, ln. 1-16] “In general, the camera 104 captures images of a package left for pickup at the property 102. The package detector 130 of the monitoring system 110 detects the package, and the monitoring system 110 monitors the package using the camera 104 until the package is picked up. When a person arrives to pick up the package, the package monitor 134 of the monitoring system 110 verifies that the person is authorized to pick up the package. If the person is authorized to pick up the package, the monitoring system can provide pickup guidance 136 and provide a pickup notification 138 to a resident 150. Referring to FIG. 2, if the person is not authorized to pick up the package, the monitoring system 110 can provide a warning 236, provide an interference notification 238 to the resident 150, and/or perform other actions to deter the person from picking up the package”, [par. 0071, ln. 1-6], [par. 0072, ln. 1-17], [par. 0101, ln. 1-9], [par. 0104, ln. 1-17]). Specifically, one of ordinary skill in the art, before the effective filing date of the claimed invention, would recognize Madden discloses both package detection and deterrence actions are performed by monitoring system 110 ([par. 0031, ln. 1-16]). The motivations to combine remains analogous to claim 1. Furthermore, it would have been obvious to one of ordinary skill in the art, in that by performing the deterrence action by generating the audiovisual signals at the computer executing the machine learning model, you avoid further delay required to transmit detection results (e.g., because the deterrence action and machine learning are both performed on the same computer, the action is effectively immediate, whereas if they were performed on separate computers, a detection result would need to be sent to the other computer to perform the deterrence action). One of ordinary skill in the art, before the effective filing date of the claimed invention, would have combined the method of Khalili with the historical data training, package movement deterrence action, and audiovisual signals of Madden through known means, with no change to their respective function, and the combination would had yielded nothing more than predicable results. Specifically, one of ordinary skill in the art, in combining the method of Khalili with the historical data training and package movement deterrence action of Madden, would have further included the one or more audiovisual signals of Madden as part of the deterrence action, and performed both the machine learning of Khalili and the deterrence action of Madden on the same computer, as taught in Madden.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the method of Khalili with the historical data training, package movement deterrence action, and audiovisual signals of Madden to obtain the invention as specified in claim 9.
15. Regarding Claim 10, a combination of Khalili and Madden teaches the method of claim 1. Khalili does not specifically disclose executing the deterrence action includes determining one or more characteristics of the person.
However, Madden specifically teaches executing the deterrence action includes determining one or more characteristics of the person ([Fig. 2], [par. 0101, ln. 1-9], [par. 0102, ln. 1-13], [par. 0103, ln. 1-12], [par. 0104, ln. 1-17]). The motivation to combine remains analogous to claim 1, specifically, in that determining one or more characteristics of a person allows for determination as to their authorization to pick up the package ([par. 0101, ln. 1-9], [par. 0104, ln. 1-17]). One of ordinary skill in the art, before the effective filing date of the claimed invention, would have combined the method of Khalili with the historical data training, package movement deterrence action, and determination of characteristics of the person of Madden through known means, with no change to their respective function, and the combination would had yielded nothing more than predicable results. Specifically, one of ordinary skill in the art would have combined the method of Khalili with the historical data training and package movement deterrence action of Madden such that the deterrence action is executed based on one or more characteristics of the person as taught in Madden.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the method of Khalili with the historical data training, package movement deterrence action, and determination of characteristics of the person of Madden to obtain the invention as specified in claim 10.
16. Regarding Claim 11, the claim language is analogous to claim 1 with the exception of “An apparatus comprising: an image sensor; and a processor executing a machine-learning model to:”. Khalili further discloses an apparatus comprising: an image sensor; and a processor executing a machine-learning model ([par. 0030, ln. 1-6]). Rejections analogous to claim 1 are further applicable to the remainder of claim 11. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the apparatus of Khalili with the historical data training and package movement deterrence action of Madden to obtain the invention as specified in claim 11.
17. Regarding Claims 13, 15, and 18-20, a combination of Khalili and Madden teaches the apparatus of claim 11. The claim language of claims 13, 15, and 18-20 is analogous to claims 3, 5, and 8-10 respectively. Rejections analogous to claims 3, 5, and 8-10 are further applicable to claims 13, 15, and 18-20 in view of the apparatus of the combination of Khalili and Madden. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the apparatus of Khalili with the historical data training and package movement deterrence action of Madden to obtain the invention as specified in claim 13, 15, and 18-20.
18. Claim 2, 4, 12, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over W.O. Publication No. 2022/245751 to Khalili, and further in view of U.S. Publication No. 2023/0282026 to Madden, and further in view of U.S. Publication No. 2018/0349708 to van Hoof et al. (hereinafter van Hoof).
19. Regarding Claim 2, a combination of Khalili and Madden teaches the method of claim 1. Khalili and Madden do not specifically teach wherein identifying the moveable object includes tracking movement of the object into the area.
However, van Hoof specifically teaches wherein identifying the movable object includes tracking movement of the object into the area ([par. 0191, ln. 1-14] “…motion has been detected more than a threshold number of times in the first identified region of interest. A threshold number of times that motion is detected at an area of the field of view (more particularly, going into or out of the area) may be predefined, learned (e.g., from video/event history), etc. at the camera 118 or video server system 508. The camera 118 or video server system 508 may determine that a certain area of the field of view satisfies the threshold and determine that the area is a source (number of times motion detected going into the area satisfies the threshold) or sink (number of times motion detected going out of the area satisfies the threshold) of motion, and identify the source/sink area as a region of interest.”, [par. 0210, ln. 1-7] “…the detected motion includes motion starting from a region of interest and/or motion starting from an ingress/egress area. Detected motion may originate from a source area and/or terminate in a sink area, and the source/sink area may be identified as a region of interest based on motion originating or terminating in the area.”, [par. 0211, ln. 1-6] “…a region of interest may be identified based on automatic detection of objects in the field of view (e.g., region of interest created on mail package, region of interest created on car entering driveway); the region of interest is automatically identified based on the automatic object detection.”, [par. 0212, ln. 1-6] “…a region of interest is identified for a detected person or face associated with an automatically created region of interest (e.g., a stranger stealing a package taken out of an automatically created region of interest, a person entering or exiting a region of interest).”). One of ordinary skill in the art, before the effective filing date of the claimed invention, would recognize Khalili, Madden, and van Hoof as within the same field of video processing for detecting and managing delivery packages, and as analogous to the claimed invention. The motivation to combine would have been obvious to one of ordinary skill in the art, and is disclosed in van Hoof ([par. 0212, ln. 1-6]), in that by tracking movement of the object into and out of the area, you can ascertain theft of a package. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have combined the method of Khalili with the historical data training and package movement deterrence action of Madden, and further combined the method of the combination of Khalili and Madden with the movement tracking into an area of van Hoof, through known means, with no change to their respective function, and the combination would had yielded nothing more than predicable results. Specifically, one of ordinary skill in the art would have modified the method of the combination of Khalili and Madden to implement the movement tracking into an area of van Hoof to identify the object by tracking movement of the object (e.g., a package) into the area (e.g., from a source, like driveway, walkway, etc.).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the method of Khalili with the historical data training and package movement deterrence action of Madden, and the movement tracking into an area of van Hoof to obtain the invention as specified in claim 2.
20. Regarding Claim 4, a combination of Khalili and Madden teaches the method of claim 1. Khalili and Madden do not specifically disclose wherein identifying the movement of the object by the person includes determining that the person has entered the area.
However, van Hoof specifically teaches identifying the movement of the object by the person includes determining that the person has entered the area ([par. 0191, ln. 1-14], [par. 0210, ln. 1-7], [par. 0211, ln. 1-6], [par. 0212, ln. 1-6]). Specifically, the motivation to combine remains analogous to claim 2, and is disclosed in van Hoof ([par. 0212, ln. 1-6]), wherein tracking a person entering and leaving an area assists in determination of package theft. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have combined the method of Khalili with the historical data training and package movement deterrence action of Madden, and further combined the method of the combination of Khalili and Madden with the determination that a person has entered the area of van Hoof, through known means, with no change to their respective function, and the combination would had yielded nothing more than predicable results. Specifically, one of ordinary skill in the art would have modified the method of the combination of Khalili and Madden to implement the determination that a person has entered the area of van Hoof to identify movement of the object by a person by tracking movement of the person into the area (e.g., from a source to the package, to a sink with the package, etc.).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the method of Khalili with the historical data training and package movement deterrence action of Madden, and the determination that a person has entered the area of van Hoof to obtain the invention as specified in claim 4.
21. Regarding Claims 12 and 14, a combination of Khalili and Madden teaches the apparatus of claim 11. The claim language of claims 12 and 14 is analogous to claims 2 and 4 respectively. Rejections analogous to claims 2 and 4 are further applicable to claims 12 and 14 in view of the apparatus of the combination of Khalili and Madden. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the apparatus of Khalili with the historical data training and package movement deterrence action of Madden, and the determination that a person or object has entered the area of van Hoof to obtain the invention as specified in claims 12 and 14.
22. Claim 6, 7, 16, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over W.O. Publication No. 2022/245751 to Khalili, and further in view of U.S. Publication No. 2023/0282026 to Madden, and further in view of U.S. Publication No. 2018/0114420 to Siminoff et al. (hereinafter Siminoff).
23. Regarding Claim 6, a combination of Khalili and Madden teach the method of claim 1. Khalili and Madden do not specifically teach wherein identifying the movement of the object by the person includes determining a direction of the movement.
However, Siminoff specifically teaches wherein identifying the movement of the object by the person includes determining a direction of the movement ([par. 0180, ln. 1-24] “…determining whether removal of the parcel from the area about the wireless A/V recording and communication device 130 was authorized may comprise detecting (or tracking) a direction of movement of the parcel. For example, when a parcel is left outside the front entrance of a home, the homeowner (or other occupant) will typically pick up the parcel and bring it inside the home. A parcel thief, by contrast, will typically pick up the parcel and carry it away from the home. Thus, if the wireless A/V recording and communication device 130 detects that the parcel is moving toward a structure to which the wireless A/V recording and communication device 130 is secured (or with which the wireless A/V recording and communication device 130 is associated), then the process may determine that the removal of the parcel from the area about the wireless A/V recording and communication device 130 is authorized. But, if the wireless A/V recording and communication device 130 detects that the parcel is moving away from the structure to which the wireless A/V recording and communication device 130 is secured (or with which the wireless A/V recording and communication device 130 is associated), then the process may determine that the removal of the parcel from the area about the wireless A/V recording and communication device 130 is unauthorized.”). One of ordinary skill in the art, before the effective filing date of the claimed invention, would recognize Khalili, Madden, and Siminoff as within the same field of video processing for detecting and managing delivery packages, and as analogous to the claimed invention. The motivation to combine is disclosed in Siminoff ([par. 0180, ln. 1-24]), wherein tracking the direction of the movement is helpful in determining if a movement of the object is a suspicious activity (e.g., package theft). One of ordinary skill in the art, before the effective filing date of the claimed invention, would have combined the method of Khalili with the historical data training and package movement deterrence action of Madden, and further combined the method of the combination of Khalili and Madden with the determination of movement direction of Siminoff, through known means, with no change to their respective function, and the combination would have yielded nothing more than predicable results. Specifically, one of ordinary skill in the art would have modified the method of the combination of Khalili and Madden to identify the movement of the object by an unauthorized person away from the house as a suspicious activity as taught in Siminoff.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the method of Khalili with the historical data training and package movement deterrence action of Madden, and the determination of movement direction of Siminoff to obtain the invention as specified in claim 6.
24. Regarding Claim 7, a combination of Khalili, Madden, and Siminoff teaches the method of claim 6. Rejections analogous to claim 6 are further applicable to claim 7. Specifically, Khalili does not specifically disclose executing the deterrence action includes determining that the direction of the movement is away from a building associated with the area. Madden teaches executing the deterrence action ([Fig. 2], [par. 0101, ln. 1-9], [par. 0102, ln. 1-13], [par. 0103, ln. 1-12], [par. 0104, ln. 1-17]), but does not specifically disclose that this is in response to determining that the direction of the movement is away from a building associated with the area, only in response to an unauthorized person picking up the package.
However, Siminoff specifically teaches executing a deterrence action in response to determining that the direction of the movement is away from a building associated with the area ([par. 0180, ln. 1-24], [par. 0194, ln. 1-23] “…the alert may comprise an audible alarm emitted from the speaker 152 of the wireless A/V recording and communication device 130. The audible alarm may be any loud noise likely to attract attention and/or startle the unauthorized person, making it more likely that he or she will flee without absconding with the parcel(s)… the alert may comprise an announcement emitted from the speaker 152 of the wireless A/V recording and communication device 130. The announcement may comprise a verbal warning that the area about the wireless A/V recording and communication device 130 is being recorded. The unauthorized person, upon being informed that the area about the wireless A/V recording and communication device 130 is being recorded, may decide to flee the scene without absconding with the parcel(s)… the alert may comprise both an audible alarm and an announcement in combination… the alert may comprise any combination of an alert signal sent to a client device, an audible alarm emitted from the speaker 152 of the wireless A/V recording and communication device 130, and an announcement emitted from the speaker 152 of the wireless A/V recording and communication device 130.”). The motivation to combine remains analogous to claim 6. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have combined the method of Khalili with the historical data training and package movement deterrence action of Madden, and further combined the method of the combination of Khalili and Madden with the determination of movement direction of Siminoff, through known means, with no change to their respective function, and the combination would have yielded nothing more than predicable results. Specifically, one of ordinary skill in the art would have modified the method of the combination of Khalili and Madden to identify the movement of the object by an unauthorized person away from the house as a suspicious activity, and to execute deterrence action in response as taught in Siminoff.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the method of Khalili with the historical data training and package movement deterrence action of Madden, and the determination of movement direction of Siminoff to obtain the invention as specified in claim 7.
25. Regarding Claims 16 and 17, a combination of Khalili and Madden teaches the apparatus of claim 11. The claim language of claims 16 and 17 is analogous to claims 2 and 4 respectively. Rejections analogous to claims 6 and 7 are further applicable to claims 16 and 17 in view of the apparatus of the combination of Khalili and Madden. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the apparatus of Khalili with the historical data training and package movement deterrence action of Madden, and the determination of movement direction of Siminoff to obtain the invention as specified in claims 16 and 17.
Conclusion
26. The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. See PTO-892.
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/PAULO ANDRES GARCIA/Examiner, Art Unit 2669 /CHAN S PARK/Supervisory Patent Examiner, Art Unit 2669
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