DETAILED ACTION
Summary
This Office Action is in response to reply dated April 29, 2026. Claims 1-22 are currently pending.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim 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 (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 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-4, 9-15 and 20-22 are rejected under 35 U.S.C. 103 as being unpatentable over Read (WO 2022/266705 A1) in view of Altiner (WO 2021/216501 A1).
Regarding claim 1, Read discloses a method for automated animal detection (see at least Figures 1-6 | [0002] note that this invention is applicable in broader contexts and other applications, such as monitoring animal intrusion into a building), comprising:
receiving one or more data sets from one or more sensors associated with a security system, wherein the security system is configured to monitor an area for animal intrusions (see at least Figure 1, items 1000, 103, 105 and 3000 | [0003] note detecting pests | [0006] note detecting feral cats in an area with indigenous wildlife | [00105] | [00129] note detection of a fox or feral cat | [0055] note the apparatus 1000 uses at least the infrared image sensor 103 and additional sensors 105 to detect the presence of a target animal 3000 in a monitored environment 2000 | [0075-0076] note the processor 104 runs a neural network classifier 4000 that can take a virtually unlimited number of inputs such as data from the imaging device 103, the acoustic sensor 108, additional sensors 105, etc., to produce a determination of a presence and/or classification of an animal species),
generating an animal detection score (6005) for a detected animal (6004) based at least in part on the one or more data sets from the one or more sensors (see at least Figure 6, items 6004, 6005 and 6006 | [00119-00121] note a determination of whether an animal has been detected 6004 is based at least on the images from the infrared image sensor 103 and acoustic sensor 108 data | [00126-00128] note at step 6006, the processor 104 determines whether or not a target animal has been detected in the classification of step 6005, like with step 6004, this decision may be based on a confidence measure (exceeding a threshold) produced with the classification of shape or pattern recognition, acoustic recognition, thermal signature detection, and movement or motion detection, see [00121] | [0017-0018] note steps 6005-6006 can also be performed at the server | [0049] note steps 6007-6008+ can also be performed at the server); and
causing autonomous execution of one or more intrusion response actions associated with the monitored area based on the animal detection score satisfying a threshold detection score (see at least Figure 6, note optional actions taken in response to step 6006, such as count animal detection event, administer poison, and/or activate nearby sensors | [00130] note that if optional steps 6007 and 6008 are not taken, then action is taken in step 6009 | [00133] note response actions that can be taken in step 6009 can include notifying the owner of a pet, activating a live feed).
However, Read does not specifically disclose an area associated with a building for animal intrusions, and causing execution of one or more intrusion response actions associated with the building.
It is known for a system to be used in different ways (see at least [0002] of Read, note that this invention is applicable in broader contexts and other applications, such as monitoring animal intrusion into a building). For example, Altiner teaches a system that monitors an area associated with a building for animal intrusions, and causes execution of one or more intrusion response actions associated with the building (see at least see at least Figures 1-5 | [0064] note when a smaller pet is detected to be outside with a predator or larger unknown animal (e.g., a stray dog), the pet door 102 may be opened to a size to permit the pet to pass through but preventing the predator or unknown animal from passing through the pet door 102 | [0059] note images from cameras are used to distinguish between animals/pets | [0055] note the controller 104 may determine not to open the pet door 102 if a particular condition is present on the side of the pet door 102 opposite the pet (e.g., undesirable conditions such as a predator, an unauthorized or unknown animal, precipitation, a wet yard, a muddy yard, gate left open, invisible fence system is down) | [0063] note the process is automated, or can be commanded via a user | [0053] note a user can be notified of a predator such as a coyote, such as when Read’s owner or monitoring personnel is/are notified of a problematic feral cat, see [00133] of Read).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the features of Altiner into Read. This prevents Read’s problematic feral cat from tailgating a pet into the entrance of a home or building of the alerted pet owner or monitoring personnel (see [00133] of Read | [0064] of Altiner).
Regarding claim 2, Read in view of Altiner teach wherein the animal detection score indicates a confidence level associated with a detection of the detected animal (see at least [00128] of Read).
Regarding claim 3, Read in view of Altiner teach wherein at least a first sensor of the one or more sensors is a thermal sensor (see at least [00119] of Read | [00121] of Read, note thermal signature detection | [0080] of Read) and at least a second sensor of the one or more sensors is a non-thermal sensor (see at least [00121] of Read note acoustic recognition | [0085] of Read, note the acoustic sensor 108).
Regarding claim 4, Read in view of Altiner teach detecting, based on a first data set of the thermal sensor and an output of a model trained for detecting animals in data from thermal sensors, the detected animal in the first data set from the thermal sensor prior to generating the animal detection score, wherein the first data set is from the one or more data sets (see at least Figure 6, items 6003-6004 occur prior to 6005-6006 of Read | [00118-00121] of Read, note thermal signature detection can be a result from a machine learning classifier).
Regarding claim 9, Read in view of Altiner teach wherein each sensor of the one or more sensors is associated with a set of user-configured attributes, and wherein a corresponding data set of each sensor associated with the one or more data sets includes one or more values for the set of user-configured attributes (see at least [0064] of Read | [00129] of Read, note target animals are stored in memory | [00126] of Read, note the animal’s shape, physical appearance and/or behavior, the size of the animal, walking patterns, gait, movement speed and characteristics such as the texture, skin/fur patterns and color of the animal can be used to identify the target animal stored in the memory | [00130] of Read, note physical markings can be stored for comparison | [00139] of Read, note the server can issue software updates to the various apparatus to, for example, update the classification algorithms to more accurately classify the current target animals or change the target animals to be classified | [00144] of Read, note the server’s management software may also include capability to upload and update sensor software and configurations using "over the air updates" | [00145] of Read, note capacity to connect to a network, for either upload, storage and classification of detection data, or download of new configurations and software to control the sensor).
Regarding claim 10, Read in view of Altiner teach wherein the one or more intrusion response actions include at least one of launching of one or more drones associated with the security system, powering on one or more lights associated with the security system, powering on one or more noise makers associated with the security system, powering on one or more sounders associated with the security system, locking one or more access doors or access gates associated with the security system, or transmitting alerts to one or more computing devices of personnel associated with the security system (see at least [00133] of Read, note alerting a server, deploying drones, issuing audio signals and alerting monitoring personnel).
Regarding claim 11, Read in view of Altiner teach receiving a configuration indicating a set of animals of interest, wherein the detected animal is one of the set of animals of interest (see at least [00129-00130] of Read, note a configuration indicating a set of animals of interest can include storing at least image of a plurality of target animals, such as a fox, a feral cat and endangered pygmy possum | [00131] of Read, note trained on images of individual animals).
Regarding claim 12, Read discloses an apparatus for automated animal detection (see at least Figures 1-6 | [0002]), comprising:
one or more memories storing instructions (see at least [0062] | [0090]); and
one or more processors coupled with the one or more memories (see at least [0063] | [00148-00149] | [0017-0018] note steps 6005-6006 can also be performed at the server | [0049] note steps 6007-6008+ can also be performed at the server) and, individually or in combination, configured to execute the instructions to:
receive one or more data sets from one or more sensors associated with a security system, wherein the security system is configured to monitor an area for animal intrusions (see at least Figure 1, items 1000, 103, 105 and 3000 | [0003] note detecting pests | [0006] note detecting feral cats in an area with indigenous wildlife | [00105] | [00129] note detection of a fox or feral cat | [0055] note the apparatus 1000 uses at least the infrared image sensor 103 and additional sensors 105 to detect the presence of a target animal 3000 in a monitored environment 2000 | [0075-0076] note the processor 104 runs a neural network classifier 4000 that can take a virtually unlimited number of inputs such as data from the imaging device 103, the acoustic sensor 108, additional sensors 105, etc., to produce a determination of a presence and/or classification of an animal species);
generate an animal detection score for a detected animal based at least in part on the one or more data sets from the one or more sensors (see at least Figure 6, items 6004, 6005 and 6006 | [00119-00121] note a determination of whether an animal has been detected 6004 is based at least on the images from the infrared image sensor 103 and acoustic sensor 108 data | [00126-00128] note at step 6006, the processor 104 determines whether or not a target animal has been detected in the classification of step 6005, like with step 6004, this decision may be based on a confidence measure (exceeding a threshold) produced with the classification of shape or pattern recognition, acoustic recognition, thermal signature detection, and movement or motion detection, see [00121] | [0017-0018] note steps 6005-6006 can also be performed at the server | [0049] note steps 6007-6008+ can also be performed at the server); and
cause autonomous execution of one or more intrusion response actions associated with the monitored area based on the animal detection score satisfying a threshold detection score (see at least Figure 6, note optional actions taken in response to step 6006, such as count animal detection event, administer poison, and/or activate nearby sensors | [00130] note that if optional steps 6007 and 6008 are not taken, then action is taken in step 6009 | [00133] note response actions that can be taken in step 6009 can include notifying the owner of a pet, activating a live feed).
However, Read does not specifically disclose an area associated with a building for animal intrusions, and causing execution of one or more intrusion response actions associated with the building.
It is known for a system to be used in different ways (see at least [0002] of Read, note that this invention is applicable in broader contexts and other applications, such as monitoring animal intrusion into a building). For example, Altiner teaches a system that monitors an area associated with a building for animal intrusions, and causes execution of one or more intrusion response actions associated with the building (see at least see at least Figures 1-5 | [0064] note when a smaller pet is detected to be outside with a predator or larger unknown animal (e.g., a stray dog), the pet door 102 may be opened to a size to permit the pet to pass through but preventing the predator or unknown animal from passing through the pet door 102 | [0059] note images from cameras are used to distinguish between animals/pets | [0055] note the controller 104 may determine not to open the pet door 102 if a particular condition is present on the side of the pet door 102 opposite the pet (e.g., undesirable conditions such as a predator, an unauthorized or unknown animal, precipitation, a wet yard, a muddy yard, gate left open, invisible fence system is down) | [0063] note the process is automated, or can be commanded via a user | [0053] note a user can be notified of a predator such as a coyote, such as when Read’s owner or monitoring personnel is/are notified of a problematic feral cat, see [00133] of Read).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the features of Altiner into Read. This prevents Read’s problematic feral cat from tailgating a pet into the entrance of a home or building of the alerted pet owner or monitoring personnel (see [00133] of Read | [0064] of Altiner).
Regarding claim 13, Read in view of Altiner teach wherein the animal detection score indicates a confidence level associated with a detection of the detected animal (see at least [00128] of Read).
Regarding claim 14, Read in view of Altiner teach wherein at least a first sensor of the one or more sensors is a thermal sensor (see at least [00119] of Read | [00121] of Read, note thermal signature detection | [0080] of Read) and at least a second sensor of the one or more sensors is a non-thermal sensor (see at least [00121] of Read, note acoustic recognition | [0085] of Read, note the acoustic sensor 108).
Regarding claim 15, Read in view of Altiner teach detect, based on a first data set of the thermal sensor and an output of a model trained for detecting animals in data from thermal sensors, the detected animal in the first data set from the thermal sensor prior to generating the animal detection score, wherein the first data set is from the one or more data sets (see at least Figure 6, items 6003-6004 occur prior to 6005-6006 of Read | [00118-00121] of Read, note thermal signature detection can be a result from a machine learning classifier).
Regarding claim 20, Read in view of Altiner teach wherein each sensor of the one or more sensors is associated with a set of user-configured attributes, and wherein a corresponding data set of each sensor associated with the one or more data sets includes one or more values for the set of user-configured attributes (see at least [0064] of Read | [00129] of Read, note target animals are stored in memory | [00126] of Read, note the animal’s shape, physical appearance and/or behavior, the size of the animal, walking patterns, gait, movement speed and characteristics such as the texture, skin/fur patterns and color of the animal can be used to identify the target animal stored in the memory | [00130] of Read, note physical markings can be stored for comparison | [00139] of Read, note the server can issue software updates to the various apparatus to, for example, update the classification algorithms to more accurately classify the current target animals or change the target animals to be classified | [00144] of Read, note the server’s management software may also include capability to upload and update sensor software and configurations using "over the air updates" | [00145] of Read, note capacity to connect to a network, for either upload, storage and classification of detection data, or download of new configurations and software to control the sensor).
Regarding claim 21, Read in view of Altiner teach wherein the one or more intrusion response actions include at least one of launching of one or more drones associated with the security system, powering on one or more lights associated with the security system, powering on one or more noise makers associated with the security system, powering on one or more sounders associated with the security system, locking one or more access doors or access gates associated with the security system, or transmitting alerts to one or more computing devices of personnel associated with the security system (see at least [00133] of Read, note alerting a server, deploying drones, issuing audio signals and alerting monitoring personnel).
Regarding claim 22, Read in view of Altiner teach wherein the one or more processors, individually or in combination, are further configured to execute the instructions to: receive a configuration indicating a set of animals of interest, wherein the detected animal is one of the set of animals of interest (see at least [00129-00130] of Read, note a configuration indicating a set of animals of interest can include storing at least image of a plurality of target animals, such as a fox, a feral cat and endangered pygmy possum | [00131] of Read, note trained on images of individual animals).
Claims 5, 6, 16 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Read (WO 2022/266705 A1) in view of Altiner (WO 2021/216501 A1) as applied to claims 4 and 15, and in further view of Koishida (US 2018/0233142 A1).
Regarding claim 5, Read discloses wherein generating the animal detection score further comprises: generating, based on detecting the detected animal, a first score (see at least [00128]); detecting the detected animal in a second data set of the non-thermal sensor (see at least [00121] note acoustic recognition), wherein the second data set is from the one or more data sets (see at least [00121] | [0075] note unlimited inputs); and determining the animal detection score based at least in part on the second data set (see at least [00121] | [00128] note like with step 6004, which includes at least thermal signature detection, acoustic recognition, shape or pattern recognition, etc.).
However, Read in view of Altiner do not specifically teach updating, the first score to generate a second score; and determining the animal detection score based at least in part on the second score.
It is known to identify a monitored entity in different ways. For example, Koishida teaches a system that updates, a first score to generate a second score; and determines a detection score based at least in part on the second score (see at least [0046] | [0025]).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the features of Koishida into Read in view of Altiner. This provides the ability to fuse Read in view of Altiner’s data from multiple sensors in order to output more accurate predictions.
Regarding claim 6, Read in view of Altiner and Koishida teach wherein the second data set of the non-thermal sensor is generated within a threshold period of time as the first data set from the thermal sensor (see at least [0046] of Koishida, note the sounds received correspond to facial movements of the entity visible to the camera when the sounds were received, not some period of time after the sounds were received).
Regarding claim 16, Read in view of Altiner and Koishida, as addressed above, teach wherein to generate the animal detection score, the one or more processors, individually or in combination, are further configured to execute the instructions to: generate, based on detecting the detected animal, a first score; update, based on detecting the detected animal in a second data set of the non-thermal sensor, the first score to generate a second score, wherein the second data set is from the one or more data sets; and determine the animal detection score based at least in part on the second score (see at least [00128] of Read, note like with step 6004, which includes at least thermal signature detection, acoustic recognition, shape or pattern recognition, etc. | [00121] of Read, note acoustic recognition | [0075] of Read, note unlimited inputs [0046] of Koishida | [0025] of Koishida).
Regarding claim 17, Read in view of Altiner and Koishida, as addressed above, teach wherein the second data set of the non-thermal sensor is generated within a threshold period of time as the first data set from the thermal sensor (see at least [0046] of Koishida, note the sounds received correspond to facial movements of the entity visible to the camera when the sounds were received, not some period of time after the sounds were received).
Claims 7, 8, 18 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Read (WO 2022/266705 A1) in view of Altiner (WO 2021/216501 A1) as applied to claims 1 and 12, and in further view of Roberts (US 10,733,822 B1).
Regarding claim 7, Read in view of Altiner teach detecting, based at least in part on the one or more data sets from the one or more sensors, a second detected animal (see at least [00129] of Read, note a plurality of target animals can be stored in the memory, such as a fox, feral cat, possum, etc. | [0055] of Altiner, note determining the pet wants out but a predator or unauthorized animal is outside); monitoring the second detected animal within a building associated with the security system or outside of the building (see at least [00145] of Read, note a plurality of sensors spatially dispersed in the environment in order to detect more animals in a wider variety of locations, habitats and times | [0010-0011] of Read, note the environment, such as a forest, is outside of a building | Figure 1 of Altiner | [0055] of Altiner, note monitoring the pet trying to operate the pet door with a predator or unauthorized animal outside); and autonomously keeping shut or not opening one or more access doors or access gates associated with the second detected animal in response to determining that the second detected animal is within the building (see at least Figure 6, items 6006→optionally take action and 6009 of Read | [00133] of Read, note actions | [0055] of Altiner, note determining to not open the door).
However, Read in view of Altiner do not specifically teach autonomously locking one or more access doors or access gates associated with the second detected animal in response to determining that the second detected animal is within the building.
It is known to monitor animals in various environments. For example, Roberts teaches a system that determines whether a second detected animal is within a building associated with a security system or outside of the building; and autonomously locking one or more access doors or access gates associated with the second detected animal in response to determining that the second detected animal is within the building (see at least col. 10, lines 35-51 | col. 10, line 1 | col. 10, lines 10-21 | col. 4, lines 26-53).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the features of Roberts into Read in view of Altiner. This provides the ability to monitor Read in view of Altiner’s pets and lock them within a building if/when needed (e.g., in the event they may escape).
Regarding claim 8, Read in view of Altiner and Roberts teach transmitting an alert to a computing device associated with a personnel of the building in response to determining that the second detected animal is outside of the building, wherein the alert indicates at least one of a presence of the second detected animal outside of the building, or a location of the second detected animal (see at least col. 4, lines 26-41 of Roberts).
Regarding claim 18, Read in view of Altiner and Roberts, as addressed above, teach wherein the one or more processors, individually or in combination, are further configured to execute the instructions to: detect, based at least in part on the one or more data sets from the one or more sensors, a second detected animal; determine whether the second detected animal is within a building associated with the security system or outside of the building; and autonomously lock one or more access doors or access gates associated with the second detected animal in response to determine that the second detected animal is within the building (see at least [00129] of Read, note a plurality of target animals can be stored in the memory, such as a fox, feral cat, possum, etc. | [00145] of Read, note a plurality of sensors spatially dispersed in the environment in order to detect more animals in a wider variety of locations, habitats and times | [0010-0011] of Read, note the environment, such as a forest, is outside of a building | Figure 6 of Read, note items 6006→optionally take action and 6009 | [00133] of Read, note actions | [0055] of Altiner, note determining the pet wants out but a predator or unauthorized animal is outside, and determining to not open the door | col. 10, lines 35-51 of Roberts | col. 10, line 1 of Roberts | col. 10, lines 10-21 of Roberts | col. 4, lines 26-53 of Roberts).
Regarding claim 19, Read in view of Altiner Roberts, as addressed above, teach wherein the one or more processors, individually or in combination, are further configured to execute the instructions to: transmit an alert to a computing device associated with a personnel of the building in response to determining that the second detected animal is outside of the building, wherein the alert indicates at least one of a presence of the second detected animal outside of the building, or a location of the second detected animal (see at least col. 4, lines 26-41 of Roberts).
Response to Arguments
Applicant’s arguments filed April 29, 2026 have been fully considered but they are moot in view of the new ground of rejection.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/BRIAN WILSON/Primary Examiner, Art Unit 2689
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