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 .
Pursuant to communications filed on 08/08/2025, this is a First Action Non-Final Rejection on the Merits wherein claims 1-20 are currently pending in the instant application.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 08/13/2025 is/are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the Examiner.
Examiner's Note
Examiner has cited particular paragraphs and/or columns / lines numbers or figures in the reference(s) as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant, in preparing the responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner. Applicant is reminded that the Examiner is entitled to give the broadest reasonable interpretation to the language of the claims. Examiner has also cited references in PTO-892 but not relied on, which are relevant and pertinent to the applicant’s disclosure, and may also be reading (anticipatory/obvious) on the claims and claimed limitations. Applicant is advised to consider the references in preparing the response/amendments in-order to expedite the prosecution.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Kerzner et al (US 2016/0266577- “Kerzner” – from IDS).
Regarding claims 1, 8 and 15, Kerzner discloses a response system / the associated method / the associated non-transitory CRM for analyzing sensor data associated with one or more coverage areas, the response system/method/CRM (e.g., via robotic assistance in security monitoring) comprising:
an autonomous drone comprising at least one processor, a memory in communication with the at least one processor, and at least one drone sensor (see at least abstract, [0005-0006] disclosing monitor control unit may include a network interface, one or more processors, and one or more storage devices that include instructions that are operable, when executed by the one or more processors, to cause the one or more processors to perform operations… [0031] A fleet of robotic devices may include one or more robots, drones, or other machines that may be configured to navigate to a particular location and carry out a series of program instructions. The fleet of robotic devices may be comprised of robotic devices that may navigate through the air, on the ground, on top of a body of water, under the surface of a body of water, or any combination thereof. In some implementations, the fleet of robotic devices may include, for example, flying helicopter drones, flying quadcopter drones, rolling drones, submarine drones, bi-pedal humanoid robots, or the like.)
wherein the at least one processor is configured to:
in response to detecting a trigger event, navigate to one or more zones of a coverage area associated with the trigger event (see figure 3- item 310; figure 4-item 410; figure 5- items 510 and 570; figure 8- item 810- see at least [0031] disclosing The fleet of robotic devices may be deployed and supervised by a central monitor control unit based on the detection of one or more alarm events. The alarm events may be detected by multiple sensors that may be strategically placed throughout the property. A fleet of robotic devices may include one or more robots, drones, or other machines that may be configured to navigate to a particular location and carry out a series of program instructions. The fleet of robotic devices may be comprised of robotic devices that may navigate through the air, on the ground, on top of a body of water, under the surface of a body of water, or any combination thereof. In some implementations, the fleet of robotic devices may include, for example, flying helicopter drones, flying quadcopter drones, rolling drones, submarine drones, bi-pedal humanoid robots, or the like., See also [0039,0136,0166]);
collect drone sensor data of the one or more zones using the at least one drone sensor (see fig. 8: step 840; see [0161] disclosing the deployed robotic devices 280, 282 may investigate 840 the area of the property in the vicinity of the location of the sensor 220 that detected the alarm event. The investigation may include each deployed robotic device 280, 282 scanning the vicinity around the sensor location for any signs of an unauthorized object. Scanning the vicinity for an unauthorized object may include, for example, using a robotic device's 280, 282 camera to take images of the vicinity of the sensor 220 and analyzing the images for the presence of an object such as, for example, the presence of a person. Each robotic device 280, 282 may utilize image processing techniques to identify shapes in captured images that may resemble a human body. Similar image processing techniques may also be used to determine if a detected object has moved. Each deployed robotic device 280, 282 may “lock-on” to a moving object that has been detected, and then follow the moving object throughout the property such as, for example, property 101.);
build, using the collected drone sensor data, a virtual map of the one or more zones (see at least fig. 7: steps 720-730; see [0077] disclosing In addition, the robotic devices 280 and 282 may store data that describes attributes of the property. For instance, the robotic devices 280 and 282 may store a floorplan and/or a three-dimensional model of the property that enables the robotic devices 280 and 282 to navigate the property. During initial configuration, the robotic devices 280 and 282 may receive the data describing attributes of the property, determine a frame of reference to the data (e.g., a home or reference location in the property), and navigate the property based on the frame of reference and the data describing attributes of the property. Further, initial configuration of the robotic devices 280 and 282 also may include learning of one or more navigation patterns in which a user provides input to control the robotic devices 280 and 282 to perform a specific navigation action (e.g., fly to an upstairs bedroom and spin around while capturing video and then return to a home charging base). In this regard, the robotic devices 280 and 282 may learn and store the navigation patterns such that the robotic devices 280 and 282 may automatically repeat the specific navigation actions upon a later request.); and
verify that the built virtual map is up-to-date by comparing the built virtual map to a stored virtual map (see [0178] disclosing Each robotic device 280, 282 may evaluate 1030 the robotic device's 280, 282 performance during the test sequence. For instance, the robotic device's actual navigation pattern may be compared against the predetermined navigation pattern. Then, a performance error may be calculated based on the deviation in the two navigation patterns. See [0133] disclosing each robotic device may periodically update the monitor control unit 210 regarding the robotic device's current location. Alternatively, the monitor control unit 210 may periodically request the current location of each robotic device in the fleet. See [0146] disclosing The current location for each robotic device 280, 282 may be periodically updated based on movements of each robotic device 280, 282. Such updated locations may be periodically reported by each robotic device 280, 282.).
Regarding claims 2, 9 and 16, Kerzner discloses wherein the trigger event includes at least one of a home sensor detecting an abnormal condition or a wireless command from a user device instructing the autonomous drone to deploy (see [0006] disclosing The monitor control unit may include a network interface, one or more processors, and one or more storage devices that include instructions that are operable, when executed by the one or more processors, to cause the one or more processors to perform operations. The operations may include receiving data from the first sensor that is indicative of an alarm event, determining the location of the first sensor, determining a security strategy for responding to the alarm event, accessing information describing the capabilities of each of the robotic devices, selecting a subset of robotic devices from the plurality of robotic devices based on the security strategy, transmitting a command to each robotic device in the subset of robotic devices that instructs each respective robotic device to navigate to the location of the property that includes the first sensor.).
Regarding claims 3, 10 and 17, Kerzner, wherein the at least one processor is further configured to receive a wireless command from a security system in response to the security system detecting an abnormal condition, the wireless command including the one or more zones (see at least [0039] The robotic devices 108a, 108b, . . . 108o may be configured to receive, interpret, and execute commands from a central monitor control unit 102. Each robotic device 108a, 108b, 108o may be configured to communicate wirelessly with any other component of security monitoring system 100 via network 111. For instance, a particular robotic device 108d may detect an alert event being broadcast by a particular sensor 104b. Alternatively, or in addition, a particular robot 108b may stream a live video feed of a burglar 140a trying to break into a window 105a of property 101 to a property occupant's 150 virtual reality headset 154.).
Regarding claims 4, 11 and 18, Kerzner, wherein the at least one processor is further configured to navigate, or maintain a position of the autonomous drone in relation to the stored virtual map, using triangulation techniques (e.g. this technique is at least inherently executed in order to communicate between the plurality of sensors located at different locations through a property) with home sensors that are within wireless communication range of the autonomous drone (e.g., see figure 3-item 360; figure 6- item 650; figure 7- item 750; figure 9- item 920; see figure 10- item 1020; see [0031] disclosing The fleet of robotic devices may be deployed and supervised by a central monitor control unit based on the detection of one or more alarm events. The alarm events may be detected by multiple sensors that may be strategically placed throughout the property. A fleet of robotic devices may include one or more robots, drones, or other machines that may be configured to navigate to a particular location and carry out a series of program instructions….See also [0076-0077, 0082, 0086, 0108]).
Regarding claims 5, 12 and 19, Kerzner, wherein the at least one processor is further configured to: determine that an abnormal condition has occurred; and transmit the an incident verification to a security system to initiate a response to the abnormal condition (see at least Kerzner, Fig. 3, Item 320, Fig. 5, Items 520 and 570, Fig. 8, Item 820, see [0033], [0037], [0107], [0136] and [0187]).
Regarding claims 6, 13 and 20, Kerzner, wherein the at least one processor is further configured to: compare the collected drone sensor data to initial drone sensor data of the coverage area stored in the memory; and determine, based upon the comparison, that an abnormal condition has occurred (see [0147] disclosing The monitor control unit 210 may deploy 550 one or more of the robotic devices 280, 282 based on location information that is associated with each robotic device 280, 282. For instance, the monitor control unit 210 may compare the current location of each robotic device 280, 282 with the current location of a sensor 220 that broadcast an alarm event notification, as determined at 520. The monitor control unit 210 may then identify a subset of robotic devices that are closest in proximity to the sensor 220, based on the comparison. Then, the monitor control unit 210 may instruct the closest robotic device to the sensor 220, or two or more of the closest robotic devices to sensor 220, to navigate to the location associated with sensor 220 to investigate the alarm event.).
Regarding claims 7 and 14, Kerzner, wherein the at least one processor is further configured to: input initial drone sensor data into a machine learning program, the machine learning program trained using sample data; identify, using the machine learning program, at least one of home characteristics or personal articles included in the initial drone sensor data; generate an inventory list based upon the identified at least one home characteristic or personal article; and store the inventory list at a security system (see [0077] disclosing the learning feature and attributes of the property- in addition, the robotic devices 280 and 282 may store data that describes attributes of the property. For instance, the robotic devices 280 and 282 may store a floorplan and/or a three-dimensional model of the property that enables the robotic devices 280 and 282 to navigate the property. During initial configuration, the robotic devices 280 and 282 may receive the data describing attributes of the property, determine a frame of reference to the data (e.g., a home or reference location in the property), and navigate the property based on the frame of reference and the data describing attributes of the property. Further, initial configuration of the robotic devices 280 and 282 also may include learning of one or more navigation patterns in which a user provides input to control the robotic devices 280 and 282 to perform a specific navigation action (e.g., fly to an upstairs bedroom and spin around while capturing video and then return to a home charging base). In this regard, the robotic devices 280 and 282 may learn and store the navigation patterns such that the robotic devices 280 and 282 may automatically repeat the specific navigation actions upon a later request.).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See attached form PTO-892.
-. US 9633547 to Farrand et al – directed to Systems, methods, and software for monitoring and controlling a security system for a structure are provided herein. An exemplary method may include receiving sensor data from at least one first peripheral, the sensor data associated with at least one of activity inside and activity outside of a structure
-. US 10417883 to Bunker et al – directed to method for security and/or automation systems is described. In one embodiment, the method includes identifying image data from a signal, analyzing the image data based at least in part on a first parameter, identifying a presence of an object based at least in part on the analyzing, and detecting an object event based at least in part on the identifying.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jaime Figueroa whose telephone number is (571)270-7620. The examiner can normally be reached on Monday-Friday 9-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Wade Miles can be reached on 571-270-7777. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JAIME FIGUEROA/Primary Patent Examiner, Art Unit 3656
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