DETAILED ACTION
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 § 102
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.
Claim(s) 1-2, 14, and 26 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Randall (US 12,468,754 B2).
Consider claim 1, Randall teaches a software application driven system comprising: a transceiver configured to receive a request to capture data associated with Unidentified Anomalous Phenomena (UAP) sighting from a user device (In response to alert signal 320 from a personal device 120, and with general knowledge of the GPS positions (locations) of all personal devices 120 in the network from their heartbeat transmissions 330 as explained above, the central server 110 transmits a notice signal to the other personal devices 120, nearby to the position indicated in said alert signal 320, indicating that a possible unusual aerial phenomenon (event of interest) may have been spotted. col. 3, lines 23-32; if other users of personal devices 120 equipped with the sensors 280 and app 600 are in the vicinity and either of their own volition or in response to the notification from the central server, point their personal devices 120 at the event of interest and initiate a recording session. col. 3, line 60 – col. 4, line 11. The alert signal is considered to be the request. The personal device is considered to be the transceiver); and a processor communicatively coupled to the transceiver (If a user of a personal device 120 observes an event of interest (e.g., an aerial phenomenon or object), the user can point the camera 230 of the personal device 120 toward the event of interest and invoke a recording session 500 of the app 600 on that personal device 120. In this recording mode 500 with the camera 230 of the personal device 120 pointed at the event of interest, the host processor 260 (FIG. 2) of that personal device 120 records data from its sensors 280 to its local memory 290. col. 2, line 66 – col. 3, line 11), wherein the processor is configured to: obtain the request from the transceiver (If a user of a personal device 120 observes an event of interest (e.g., an aerial phenomenon or object), the user can point the camera 230 of the personal device 120 toward the event of interest and invoke a recording session 500 of the app 600 on that personal device 120. In this recording mode 500 with the camera 230 of the personal device 120 pointed at the event of interest, the host processor 260 (FIG. 2) of that personal device 120 records data from its sensors 280 to its local memory 290. col. 2, line 66 – col. 3, line 11); cause the user device to collect UAP data (If a user of a personal device 120 observes an event of interest (e.g., an aerial phenomenon or object), the user can point the camera 230 of the personal device 120 toward the event of interest and invoke a recording session 500 of the app 600 on that personal device 120. In this recording mode 500 with the camera 230 of the personal device 120 pointed at the event of interest, the host processor 260 (FIG. 2) of that personal device 120 records data from its sensors 280 to its local memory 290. col. 2, line 66 – col. 3, line 11; if other users of personal devices 120 equipped with the sensors 280 and app 600 are in the vicinity and either of their own volition or in response to the notification from the central server, point their personal devices 120 at the event of interest and initiate a recording session. Col. 3, lines 60-65); obtain a trigger from the user device (In addition, host processor 260 under the direction of app 600 sends relatively slow, periodic, repeating alert signals 320 (FIG. 4) to the central server 110 through internet connection 270. Alert signal 320 as illustrated in FIG. 4 comprises a set of informative metrics regarding recording session 500. These informative metrics include but are not limited to the current time, average pointing angle, average GPS coordinates, and device ID. The central server 110 receives this information transmitted from personal device 120 under the direction of app 600. The location information, i.e., GPS coordinates, in the alert signals 320 is used in the central server 110 to check if other users in the network are nearby based on the idle mode 410 periodic heartbeat 330 transmissions of position data of the other personal devices 120 in the network to the central server 110. col. 3, lines 7-23. The alert signal is considered to be the trigger); transmit a notification to other user devices to collect UAP data responsive to obtaining the trigger (In response to alert signal 320 from a personal device 120, and with general knowledge of the GPS positions (locations) of all personal devices 120 in the network from their heartbeat transmissions 330 as explained above, the central server 110 transmits a notice signal to the other personal devices 120, nearby to the position indicated in said alert signal 320, indicating that a possible unusual aerial phenomenon (event of interest) may have been spotted. The pointing angle and GPS location of personal device 120 as indicated in alert signal 320 sent to central server 110 as directed by the app 600 is interpreted by algorithms in server 110 to determine the pyramidal volume 720 (FIG. 6) that is used to inform other users where they might find said event of interest (aerial phenomenon or object) in the sky. Col. 3, lines 23-37; if other users of personal devices 120 equipped with the sensors 280 and app 600 are in the vicinity and either of their own volition or in response to the notification from the central server, point their personal devices 120 at the event of interest and initiate a recording session. Col. 3, lines 60-65); receive the UAP data from the user device and the other user devices responsive to the transmission of the notification (In this recording mode 500 with the camera 230 of the personal device 120 pointed at the event of interest, the host processor 260 (FIG. 2) of that personal device 120 records data from its sensors 280 to its local memory 290. In addition, host processor 260 under the direction of app 600 sends relatively slow, periodic, repeating alert signals 320 (FIG. 4) to the central server 110 through internet connection 270. col. 3, lines 4-11; if other users of personal devices 120 equipped with the sensors 280 and app 600 are in the vicinity and either of their own volition or in response to the notification from the central server, point their personal devices 120 at the event of interest and initiate a recording session 500, thus transmissions of alert signals 320 from their own personal devices 120 to the central server 110, the additional pointing angles obtained by the central server 110 from those additional alert signals 320 are used by algorithms in server 110 along with any additional location and pointing angles received from the personal device 120 that are transmitting periodic alert signals 320 to further refine the location of the event of interest to better inform additional other users of such personal devices 120 operating app 600 where to look for the event of interest.…. When a user stops the recording session 500 on a personal device 120, the app 600 on that personal device 120 creates an information packet 310 from data stored in the memory 290 during the recording session 500 and transmits the information packet 310 to the central server 110. col. 3, line 60 – col. 4, line 16); and store the UAP data (In this recording mode 500 with the camera 230 of the personal device 120 pointed at the event of interest, the host processor 260 (FIG. 2) of that personal device 120 records data from its sensors 280 to its local memory 290. col. 3, lines 4-11; col. 3, line 60 – col. 4, line 16).
Consider claim 2, Randall teaches a UAP signature generator for generating UAP signatures from collected UAP data (information packet. col. 4, lines 12-31); and at least one relational database capable of storing UAP data signatures (information packets for all recording sessions are saved at the server in a database. col. 6, lines 5-16).
Consider claim 14, Randall teaches a software driven system for capturing, processing (col. 2, lines 34-52; Fig. 2), and reporting data associated with observed events, including Unidentified Anomalous Phenomena (UAP) sightings (col. 2, lines 34-52; Fig. 2), comprising: a transceiver configured to receive a request to capture data associated with crowdsourced sighting data from a plurality of user devices within a crowdsourced network (In response to alert signal 320 from a personal device 120, and with general knowledge of the GPS positions (locations) of all personal devices 120 in the network from their heartbeat transmissions 330 as explained above, the central server 110 transmits a notice signal to the other personal devices 120, nearby to the position indicated in said alert signal 320, indicating that a possible unusual aerial phenomenon (event of interest) may have been spotted. col. 3, lines 23-32; if other users of personal devices 120 equipped with the sensors 280 and app 600 are in the vicinity and either of their own volition or in response to the notification from the central server, point their personal devices 120 at the event of interest and initiate a recording session. col. 3, line 60 – col. 4, line 11. The alert signal is considered to be the request. The personal device is considered to be the transceiver); and a processor communicatively coupled to the transceiver (If a user of a personal device 120 observes an event of interest (e.g., an aerial phenomenon or object), the user can point the camera 230 of the personal device 120 toward the event of interest and invoke a recording session 500 of the app 600 on that personal device 120. In this recording mode 500 with the camera 230 of the personal device 120 pointed at the event of interest, the host processor 260 (FIG. 2) of that personal device 120 records data from its sensors 280 to its local memory 290. col. 2, line 66 – col. 3, line 11), the processor is configured to perform the process recited in claim 1 (see rejection for claim 1).
Consider claim 26, Randall teaches an automated method of capturing, processing, and reporting data associated with Unidentified Anomalous Phenomena (UAP) sightings, comprising the following steps: providing a system of user devices capable of capturing moving image data with a user software application configured for capturing UAP sighting data wherein the user device further includes a transceiver for sending and receiving sets of user device instructions consistent with associated with Unidentified Anomalous Phenomena (UAP) sightings and receiving a request to capture UAP data from the user device (In response to alert signal 320 from a personal device 120, and with general knowledge of the GPS positions (locations) of all personal devices 120 in the network from their heartbeat transmissions 330 as explained above, the central server 110 transmits a notice signal to the other personal devices 120, nearby to the position indicated in said alert signal 320, indicating that a possible unusual aerial phenomenon (event of interest) may have been spotted. col. 3, lines 23-32; if other users of personal devices 120 equipped with the sensors 280 and app 600 are in the vicinity and either of their own volition or in response to the notification from the central server, point their personal devices 120 at the event of interest and initiate a recording session. col. 3, line 60 – col. 4, line 11. The alert signal is considered to be the request. The personal device is considered to be the transceiver); providing a processor communicatively coupled to the transceiver (If a user of a personal device 120 observes an event of interest (e.g., an aerial phenomenon or object), the user can point the camera 230 of the personal device 120 toward the event of interest and invoke a recording session 500 of the app 600 on that personal device 120. In this recording mode 500 with the camera 230 of the personal device 120 pointed at the event of interest, the host processor 260 (FIG. 2) of that personal device 120 records data from its sensors 280 to its local memory 290. col. 2, line 66 – col. 3, line 11), wherein the processor is configured to perform the process recited in claim 1 (see rejection for claim 1).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 3, 15, 27-28 is/are rejected under 35 U.S.C. 103 as being unpatentable over Randall (US 12,468,754 B2) in view of Bradley (US 2023/0409054 A1).
Consider claim 3, Randell teaches all the limitations in claim 2 but does not explicitly teach an authenticator for authenticating the collected UAP data before transmitting the notification by accessing the at least one relational database and comparing the UAP data collected by the user device to at least one UAP signature.
Bradley teaches an authenticator for authenticating the collected UAP data before transmitting the notification by accessing the at least one relational database (the event type data and the event location data may be received by a controller. In step 120, the method may include classifying an event of the surveilled area by determining a match between a total score of the event compared with event data of the one or more data feeds and one or more event types in the event database. For example, as soon as an event is detected, one or more UAVs can be immediately launched. [0101] and Fig. 1) and comparing the UAP data collected by the user device to at least one UAP signature (the event type data and the event location data may be received by a controller. In step 120, the method may include classifying an event of the surveilled area by determining a match between a total score of the event compared with event data of the one or more data feeds and one or more event types in the event database. For example, as soon as an event is detected, one or more UAVs can be immediately launched. [0101] and Fig. 1).
Therefore, 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 known technique of authenticating the data because such incorporation would improve event type identification and/or appropriate response actions. [0147].
Consider claim 15, the combination of Randall and Bradley teaches the processor is configured to access at least one relational database having a plurality of event data signatures (information packet. col. 4, lines 12-31; information packets for all recording sessions are saved at the server in a database. col. 6, lines 5-16), and further comprises a comparator for comparing the event data collected by the user device to the data signatures of the relational database (the event type data and the event location data may be received by a controller. In step 120, the method may include classifying an event of the surveilled area by determining a match between a total score of the event compared with event data of the one or more data feeds and one or more event types in the event database. For example, as soon as an event is detected, one or more UAVs can be immediately launched. [0101] and Fig. 1); and an authenticator for authenticating the collected event data prior to transmitting the notification and receiving a trigger (the event type data and the event location data may be received by a controller. In step 120, the method may include classifying an event of the surveilled area by determining a match between a total score of the event compared with event data of the one or more data feeds and one or more event types in the event database. For example, as soon as an event is detected, one or more UAVs can be immediately launched. [0101] and Fig. 1).
Therefore, 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 known technique of authenticating the data because such incorporation would improve event type identification and/or appropriate response actions. [0147].
Consider claim 27, Bradley teaches authenticating the collected UAP data before transmitting the notification by accessing the at least one relational database (the event type data and the event location data may be received by a controller. In step 120, the method may include classifying an event of the surveilled area by determining a match between a total score of the event compared with event data of the one or more data feeds and one or more event types in the event database. For example, as soon as an event is detected, one or more UAVs can be immediately launched. [0101] and Fig. 1) and comparing the UAP data collected by the user device to UAP signature data within the relational database (the event type data and the event location data may be received by a controller. In step 120, the method may include classifying an event of the surveilled area by determining a match between a total score of the event compared with event data of the one or more data feeds and one or more event types in the event database. For example, as soon as an event is detected, one or more UAVs can be immediately launched. [0101] and Fig. 1).
Therefore, 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 known technique of authenticating the data because such incorporation would improve event type identification and/or appropriate response actions. [0147].
Consider claim 28, Randall teaches generating UAP signatures from collected UAP data (information packet. col. 4, lines 12-31); and storing a UAP data signature in at least one relational database (information packets for all recording sessions are saved at the server in a database. col. 6, lines 5-16).
Claim(s) 4, 16-17, and 29 is/are rejected under 35 U.S.C. 103 as being unpatentable over Randall (US 12,468,754 B2) in view of Bradley (US 2023/0409054 A1) and Megginson et al. (US 9,723,693 B1).
Consider claim 4, the combination of Randall and Bradley teaches all the limitations in claim 3 but does not explicitly teach a discriminator operably connected to the UAP signature generator and the at least one relational database for comparing the authenticated collected UAP data to at least one designated UAP signature within the relational database and initiating the creation of a new UAP signature when the authenticated collected UAP data and corresponding signature differs from the designated signature.
Megginson teaches a discriminator operably connected to the UAP signature generator and the at least one relational database for comparing the authenticated collected UAP data to at least one designated UAP signature within the relational database (In step 420, it is determined whether any of the visual signatures generated match previously stored visual signatures, or are new visual signatures. If new visual signatures have been generated, they are stored in memory in step 422. In step 424, it is then determined whether any Bluetooth identification information was associated with any of the new visual signatures. If so, the processing system stores the Bluetooth identification information in association with the stored visual signatures in step 426. Col. 12, lines 38-46; In step 506, it is determined whether the stitched-together image contains a person who may be identified. If so, in step 508, the processing system creates a visual signature for each identifiable person. In step 510, it is determined whether the visual signatures created for each person match any previously stored visual signatures, or whether the created visual signatures are for new persons. If the visual signatures are new, the processing system stores the visual signatures in a record of signatures currently within the facility in step 512. If the visual signatures match previously stored visual signatures, then the current location of the person corresponding to that visual signature is updated in step 514. Col. 13, lines 33-45) and initiating the creation of a new UAP signature when the authenticated collected UAP data and corresponding signature differs from the designated signature (In step 420, it is determined whether any of the visual signatures generated match previously stored visual signatures, or are new visual signatures. If new visual signatures have been generated, they are stored in memory in step 422. In step 424, it is then determined whether any Bluetooth identification information was associated with any of the new visual signatures. If so, the processing system stores the Bluetooth identification information in association with the stored visual signatures in step 426. Col. 12, lines 38-46; In step 506, it is determined whether the stitched-together image contains a person who may be identified. If so, in step 508, the processing system creates a visual signature for each identifiable person. In step 510, it is determined whether the visual signatures created for each person match any previously stored visual signatures, or whether the created visual signatures are for new persons. If the visual signatures are new, the processing system stores the visual signatures in a record of signatures currently within the facility in step 512. If the visual signatures match previously stored visual signatures, then the current location of the person corresponding to that visual signature is updated in step 514. Col. 13, lines 33-45).
Therefore, 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 teachings from Megginson into the combination of Randall and Bradley because such incorporation would facilitate identification of a person in a facility. Col. 12, lines 1-20.
Consider claim 16, the combination of Randall and Megginson teaches a signature generator for creating a new event signature when at least one designated signature within the relational database differs from similar data within the collected and authenticated event data (In step 420, it is determined whether any of the visual signatures generated match previously stored visual signatures, or are new visual signatures. If new visual signatures have been generated, they are stored in memory in step 422. In step 424, it is then determined whether any Bluetooth identification information was associated with any of the new visual signatures. If so, the processing system stores the Bluetooth identification information in association with the stored visual signatures in step 426. Col. 12, lines 38-46; In step 506, it is determined whether the stitched-together image contains a person who may be identified. If so, in step 508, the processing system creates a visual signature for each identifiable person. In step 510, it is determined whether the visual signatures created for each person match any previously stored visual signatures, or whether the created visual signatures are for new persons. If the visual signatures are new, the processing system stores the visual signatures in a record of signatures currently within the facility in step 512. If the visual signatures match previously stored visual signatures, then the current location of the person corresponding to that visual signature is updated in step 514. Col. 13, lines 33-45 of Megginson); and storing the authenticated event data and the newly created signature within the at least one relational database (information packets for all recording sessions are saved at the server in a database. col. 6, lines 5-16 of Randall).
Therefore, 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 teachings from Megginson into the combination of Randall and Bradley because such incorporation would facilitate identification of a person in a facility. Col. 12, lines 1-20.
Consider claim 17, Randall teaches the transceiver distributes the newly created data signature to the other user devices (When a user stops the recording session 500 on a personal device 120, the app 600 on that personal device 120 creates an information packet 310 from data stored in the memory 290 during the recording session 500 and transmits the information packet 310 to the central server 110. Col. 4, lines 12-16).
Consider claim 29, Megginson teaches generating a UAP signature from authenticated collected data (In step 420, it is determined whether any of the visual signatures generated match previously stored visual signatures, or are new visual signatures. If new visual signatures have been generated, they are stored in memory in step 422. In step 424, it is then determined whether any Bluetooth identification information was associated with any of the new visual signatures. If so, the processing system stores the Bluetooth identification information in association with the stored visual signatures in step 426. Col. 12, lines 38-46; In step 506, it is determined whether the stitched-together image contains a person who may be identified. If so, in step 508, the processing system creates a visual signature for each identifiable person. In step 510, it is determined whether the visual signatures created for each person match any previously stored visual signatures, or whether the created visual signatures are for new persons. If the visual signatures are new, the processing system stores the visual signatures in a record of signatures currently within the facility in step 512. If the visual signatures match previously stored visual signatures, then the current location of the person corresponding to that visual signature is updated in step 514. Col. 13, lines 33-45).
Therefore, 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 teachings from Megginson into the combination of Randall and Bradley because such incorporation would facilitate identification of a person in a facility. Col. 12, lines 1-20.
Claim(s) 5-6, 18-19, and 30-31 is/are rejected under 35 U.S.C. 103 as being unpatentable over Randall (US 12,468,754 B2) in view of Bradley (US 2023/0409054 A1) and Megginson et al. (US 9,723,693 B1) and Shah et al. (US 2023/0007342 A1).
Consider claim 5, the combination of Randall, Bradley, and Megginson teaches all the limitations in claim 4 but does not explicitly teach a comparator for comparing the signatures from the signature generator of a first user device to the signatures generated by the signature generator of a second user device and comparing the signatures to the stored authenticated UAP data and signatures in the at least one relational database, enabling the system to improve the authentications of the UAP data and the subsequent creation of UAP signatures for any given sequence of UAP data-generating events having a common UAP signature associated with a plurality of users.
Shah teaches a comparator for comparing the signatures from the signature generator of a first user device to the signatures generated by the signature generator of a second user device and comparing the signatures to the stored authenticated UAP data and signatures in the at least one relational database, enabling the system to improve the authentications of the UAP data and the subsequent creation of UAP signatures for any given sequence of UAP data-generating events having a common UAP signature associated with a plurality of users (Such characteristics may be determined based on the video captured by the one or more cameras 320, 322, 324 and, where multiple cameras 320, 322, 324 are provided, comparing the captured videos, and/or from analysis of data received from a device 325 worn by the user 302 or held by the user 302 indicative of the first user's movements, such as a smartwatch or cellphone including an accelerometer or gyroscope. [0048]. The control circuitry of the user equipment 600 then compares the images captured by the cameras 620, 622, 624 to determine a portion of the display screen to which the first user 602 is pointing. For example, the control circuitry may determine coordinates of the portion based on orientations of the first user's finger as shown in the multiple images. [0059]. The control circuitry of the user equipment device 600 compares the images from the multiple cameras 620, 622, 626 and determines a portion of the display screen to which the first user 602 is pointing. For example, the control circuitry may determine from an orientation and size of the first user's finger in the captured video coordinates of a portion of the display screen to which the first user 602 is pointing. [0064]. The control circuitry of the user equipment 500 then compares the images captured by the cameras 820, 822, 824 to determine a portion of the display screen to which the first user 802 is pointing. For example, the control circuitry may determine coordinates of the portion based on orientations and sizes of the first user's finger shown in the multiple images. [0071]. The control circuitry of the user equipment device 800 compares the images from the multiple cameras 820, 822, 824 and determines a portion of the display screen to which the first user 802 is pointing. For example, the control circuitry may determine, from an orientation and size of the first user's finger in the captured video, coordinates of a portion of the display screen to which the first user 802 is pointing. [0080]).
Therefore, 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 known technique of comparing data from different devices because such incorporation would help determine reaction characteristics. [0048].
Consider claim 6, Randall teaches a report generator for generating a report of the authenticated collected UAP data and designated signatures received from a plurality of users corresponding to the same UAP event (col. 4, lines 12-37).
Consider claim 18, Shah teaches the signature generator further comprises: a discriminator for discriminating between signatures obtained from different user devices and comparing them to the stored authenticated event data and signatures before updating the at least one relational database with the newly collected authenticated data and corresponding signatures enabling the processor to improve the authentications of the event data and the subsequent creation of event signatures for any given sequence of event data-generating events having a common signature associated with a plurality of users (Such characteristics may be determined based on the video captured by the one or more cameras 320, 322, 324 and, where multiple cameras 320, 322, 324 are provided, comparing the captured videos, and/or from analysis of data received from a device 325 worn by the user 302 or held by the user 302 indicative of the first user's movements, such as a smartwatch or cellphone including an accelerometer or gyroscope. [0048]. The control circuitry of the user equipment 600 then compares the images captured by the cameras 620, 622, 624 to determine a portion of the display screen to which the first user 602 is pointing. For example, the control circuitry may determine coordinates of the portion based on orientations of the first user's finger as shown in the multiple images. [0059]. The control circuitry of the user equipment device 600 compares the images from the multiple cameras 620, 622, 626 and determines a portion of the display screen to which the first user 602 is pointing. For example, the control circuitry may determine from an orientation and size of the first user's finger in the captured video coordinates of a portion of the display screen to which the first user 602 is pointing. [0064]. The control circuitry of the user equipment 500 then compares the images captured by the cameras 820, 822, 824 to determine a portion of the display screen to which the first user 802 is pointing. For example, the control circuitry may determine coordinates of the portion based on orientations and sizes of the first user's finger shown in the multiple images. [0071]. The control circuitry of the user equipment device 800 compares the images from the multiple cameras 820, 822, 824 and determines a portion of the display screen to which the first user 802 is pointing. For example, the control circuitry may determine, from an orientation and size of the first user's finger in the captured video, coordinates of a portion of the display screen to which the first user 802 is pointing. [0080]).
Therefore, 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 known technique of comparing data from different devices because such incorporation would help determine reaction characteristics. [0048].
Consider claim 19, Randall teaches a report generator for generating a report of the common authenticated event data or designated signatures received from a plurality of users corresponding to the event (col. 4, lines 12-37).
Consider claim 30, Shah teaches comparing the signatures from a first user device to the signatures of a second user device and comparing the signatures to the stored authenticated UAP data and signatures in at least one relational database to improve the authentications of the UAP data and the subsequent creation of UAP signatures for any given sequence of UAP data-generating events having a common UAP signature associated with a plurality of users (Such characteristics may be determined based on the video captured by the one or more cameras 320, 322, 324 and, where multiple cameras 320, 322, 324 are provided, comparing the captured videos, and/or from analysis of data received from a device 325 worn by the user 302 or held by the user 302 indicative of the first user's movements, such as a smartwatch or cellphone including an accelerometer or gyroscope. [0048]. The control circuitry of the user equipment 600 then compares the images captured by the cameras 620, 622, 624 to determine a portion of the display screen to which the first user 602 is pointing. For example, the control circuitry may determine coordinates of the portion based on orientations of the first user's finger as shown in the multiple images. [0059]. The control circuitry of the user equipment device 600 compares the images from the multiple cameras 620, 622, 626 and determines a portion of the display screen to which the first user 602 is pointing. For example, the control circuitry may determine from an orientation and size of the first user's finger in the captured video coordinates of a portion of the display screen to which the first user 602 is pointing. [0064]. The control circuitry of the user equipment 500 then compares the images captured by the cameras 820, 822, 824 to determine a portion of the display screen to which the first user 802 is pointing. For example, the control circuitry may determine coordinates of the portion based on orientations and sizes of the first user's finger shown in the multiple images. [0071]. The control circuitry of the user equipment device 800 compares the images from the multiple cameras 820, 822, 824 and determines a portion of the display screen to which the first user 802 is pointing. For example, the control circuitry may determine, from an orientation and size of the first user's finger in the captured video, coordinates of a portion of the display screen to which the first user 802 is pointing. [0080]).
Therefore, 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 known technique of comparing data from different devices because such incorporation would help determine reaction characteristics. [0048].
Consider claim 31, Randall teaches generating a report of the authenticated collected UAP data and designated signatures received from a plurality of users corresponding to the UAP event (col. 4, lines 12-37).
Claim(s) 7-13, 20-25, and 32-37 is/are rejected under 35 U.S.C. 103 as being unpatentable over Randall (US 12,468,754 B2) in view of Bradley (US 2023/0409054 A1), Megginson et al. (US 9,723,693 B1), Shah et al. (US 2023/0007342 A1), and Seeber et al. (US 2021/0025975 A1).
Consider claim 7, the combination of Randall, Bradley, Megginson, and Shah teaches all the limitations in claim 6 but does not explicitly teach a converter for converting the reported data into user device manipulation instructions and transmitting those instructions to the users to assist them with the collection of additional UAP data associated with the same UAP sighting event.
Seeber teaches a converter for converting the reported data into user device manipulation instructions and transmitting those instructions to the users to assist them with the collection of additional UAP data associated with the same UAP sighting event (the video data analysis process 700 may indicate if the tracks followed by the PTZ cameras include a UAV. In various embodiments, at step 1704 it is determined that if a UAV is identified within the track, the process may proceed to the PTZ tracking process 1800. [0174]; in response to appropriately evaluating the one or more received tracks for PTZ camera assignment based on the various aspects of the tracks (steps 1804-1814), at step 1816 the system may assign the one or more PTZ cameras to the tracks, where the PTZ cameras furthermore automatically follow their assigned tracks for collecting video/image frames for determining if the tracks include a UAV (e.g., verifying the tracks). [0182]. See also [0173] – [0185], Fig. 17-19).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 8, Seeber teaches the user device includes: a camera with adjustable camera settings configured to be responsive to the user device manipulation instructions associated with the authenticated data and designated signatures (in response to the PTZ camera being directed in the position of the predicted track position, the PTZ camera may capture video and/or image frames at the predicted track position to be processed at the video data analysis process 700. In at least one embodiment, the system may configure the PTZ zoom (and other configurations) such that the camera captures the least amount of pixels possible for verifying a UAV in a track. In various embodiments, directing the PTZ cameras may include instructing the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of each assigned track such that the tracks are “followed” over time. [0173] – [0185] Fig. 17-19).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 9, Seeber teaches the processor is configured to initiate the adjustment of the user device camera settings in response to the common authenticated data and the designated signatures further comprising: a UAP signature recognition algorithm capable of calculating signatures corresponding to UAP movement data and generating UAP movement predictions based on the calculations ([0014], [0055], [0184] – [0185]), and triggering responsive adjustments to the camera settings based on the movement predictions ([0014], [0055], [0184] – [0185]).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 10, Seeber teaches a tracker, for producing tracking data responsive to the camera adjustments, enabling the user device camera settings to track UAP movement in accordance with a set of UAP signatures for predictable UAP movements ([0173] – [0185], Fig. 17-19).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 11, Seeber teaches the processor for making movement predictions is operably configured to be responsive to at least one artificial intelligence (AI) algorithm (the process may proceed to step 1904, where the system performs object detection techniques on the one or more frames specifically for identifying UAVs, thus allowing the system to better follow the UAVs. According to various aspects of the present disclosure, the object detection techniques may include applying a neural network that has been trained for processing one or more image frames for identifying UAVs in an airspace, as well as for detecting objects that are easily confused with UAVs, within the frame. The neural network may be trained by using training data including historical images or streams with known successfully identified UAVs and erroneously identified UAVs. In a particular embodiment, the output from step 1804 may include one or more bounding boxes for encompassing the UAV (or other objects) within the frame, as well as one or more confidence scores indicative of the likelihood that the objects included in the bounding boxes are UAVs. [0184]) such that the generated camera adjustments are responsive to non-analogous signatures and authenticated UAP data to anticipate unpredictable movements of the UAP being observed (the process may proceed to step 1904, where the system performs object detection techniques on the one or more frames specifically for identifying UAVs, thus allowing the system to better follow the UAVs. According to various aspects of the present disclosure, the object detection techniques may include applying a neural network that has been trained for processing one or more image frames for identifying UAVs in an airspace, as well as for detecting objects that are easily confused with UAVs, within the frame. The neural network may be trained by using training data including historical images or streams with known successfully identified UAVs and erroneously identified UAVs. In a particular embodiment, the output from step 1804 may include one or more bounding boxes for encompassing the UAV (or other objects) within the frame, as well as one or more confidence scores indicative of the likelihood that the objects included in the bounding boxes are UAVs. For example, a PTZ captured frame processed at step 1904 may include both a UAV and a bird, and the system may recognize both as objects (or ROIs) within the frame to be encompassed with bounding boxes. The UAV included in the bounding box may be assigned an almost certain confidence score (e.g., 99%) in response to the UAV-specific object detection algorithms, while the bird may receive a lower confidence score (e.g., 5%), and thus the bird may be dismissed as a non-drone or non-UAV. [0184]) and the unpredictable movements become part of the predictable movement signatures for a previously recorded UAP sighting event wherein the unpredictable movement signature is sent to the user devices as an alternate set of tracking data if the observed UAP is no longer visible to any of the users ([0173] – [0185], Fig. 17-19); and the user device camera settings are adjusted to correspond to the alternate set of tracking data received ([0173] - [0185], Fig. 17-19).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 12, Randall teaches the report generator generates a report from the alternate set of tracking data when the user device UAP tracking data is authenticated as capable of tracking the UAP (col. 4, lines 12-50); and transmits the report to an independently configured responsive system capable of initiating an independent system response commensurate with its function (col. 4, lines 12-50).
Consider claim 13, Seeber teaches the independently responsive system is: a defensive system ([0170]).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 20, Seeber teaches the processor converts the reported data into user device manipulation instructions and transmitting those instructions to the users to assist them with the collection of additional event data (the video data analysis process 700 may indicate if the tracks followed by the PTZ cameras include a UAV. In various embodiments, at step 1704 it is determined that if a UAV is identified within the track, the process may proceed to the PTZ tracking process 1800. [0174]; in response to appropriately evaluating the one or more received tracks for PTZ camera assignment based on the various aspects of the tracks (steps 1804-1814), at step 1816 the system may assign the one or more PTZ cameras to the tracks, where the PTZ cameras furthermore automatically follow their assigned tracks for collecting video/image frames for determining if the tracks include a UAV (e.g., verifying the tracks). [0182]. See also [0173] – [0185], Fig. 17-19).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 21, Seeber teaches the user device includes a camera with adjustable camera settings configured to be responsive to the device manipulation instructions received (in response to the PTZ camera being directed in the position of the predicted track position, the PTZ camera may capture video and/or image frames at the predicted track position to be processed at the video data analysis process 700. In at least one embodiment, the system may configure the PTZ zoom (and other configurations) such that the camera captures the least amount of pixels possible for verifying a UAV in a track. In various embodiments, directing the PTZ cameras may include instructing the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of each assigned track such that the tracks are “followed” over time. [0173] – [0185] Fig. 17-19); and adjusting the user device camera settings in response to the common authenticated data or the designated signatures ([0014], [0055], [0184] – [0185]).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 22, Seeber teaches the processor is responsible for adjusting the user device camera settings in response to the common authenticated data or the designated signatures further comprises: an event signature recognition algorithm capable of calculating signatures corresponding to pre-designated changes in continuous event data and generating event change predictions based on the calculations ([0014], [0055], [0184] – [0185]); and triggering responsive adjustments to the camera settings based on the change predictions ([0014], [0055], [0184] – [0185]).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 23, Seeber teaches the responsive adjustments to the camera settings based on the change predictions enable the user device camera settings to track the event changes in accordance with a set of signatures for predictable event changes ([0173] – [0185], Fig. 17-19).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 24, Seeber teaches the event change predictions are based upon at least one artificial intelligence (AI) algorithm (the process may proceed to step 1904, where the system performs object detection techniques on the one or more frames specifically for identifying UAVs, thus allowing the system to better follow the UAVs. According to various aspects of the present disclosure, the object detection techniques may include applying a neural network that has been trained for processing one or more image frames for identifying UAVs in an airspace, as well as for detecting objects that are easily confused with UAVs, within the frame. The neural network may be trained by using training data including historical images or streams with known successfully identified UAVs and erroneously identified UAVs. In a particular embodiment, the output from step 1804 may include one or more bounding boxes for encompassing the UAV (or other objects) within the frame, as well as one or more confidence scores indicative of the likelihood that the objects included in the bounding boxes are UAVs. [0184]) such that the generated camera adjustments are responsive to non-analogous signatures or authenticated event data in order to anticipate unpredictable event changes and the unpredictable event changes become part of the predictable change signatures for a previously recorded sighting event (the process may proceed to step 1904, where the system performs object detection techniques on the one or more frames specifically for identifying UAVs, thus allowing the system to better follow the UAVs. According to various aspects of the present disclosure, the object detection techniques may include applying a neural network that has been trained for processing one or more image frames for identifying UAVs in an airspace, as well as for detecting objects that are easily confused with UAVs, within the frame. The neural network may be trained by using training data including historical images or streams with known successfully identified UAVs and erroneously identified UAVs. In a particular embodiment, the output from step 1804 may include one or more bounding boxes for encompassing the UAV (or other objects) within the frame, as well as one or more confidence scores indicative of the likelihood that the objects included in the bounding boxes are UAVs. For example, a PTZ captured frame processed at step 1904 may include both a UAV and a bird, and the system may recognize both as objects (or ROIs) within the frame to be encompassed with bounding boxes. The UAV included in the bounding box may be assigned an almost certain confidence score (e.g., 99%) in response to the UAV-specific object detection algorithms, while the bird may receive a lower confidence score (e.g., 5%), and thus the bird may be dismissed as a non-drone or non-UAV. [0184]); the unpredictable event signature is sent to the user devices as an alternate set of monitoring data if the observed event is no longer visible to any of the users ([0173] – [0185], Fig. 17-19); and the user device camera settings are adjusted to correspond to the alternate set of monitoring data received ([0173] – [0185], Fig. 17-19).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 25, Randall teaches a report generator for generating a report from the alternate set of monitoring data when the user device monitoring data is authenticated as capable of monitoring the event (col. 4, lines 12-50); a transmitter for transmitting the report to an independently configured responsive system capable of initiating an independent system response commensurate with its function (col. 4, lines 12-50).
Consider claim 32, Seeber teaches converting the reported data into user device manipulation instructions and transmitting those instructions to the users to assist them with the collection of additional UAP data (the video data analysis process 700 may indicate if the tracks followed by the PTZ cameras include a UAV. In various embodiments, at step 1704 it is determined that if a UAV is identified within the track, the process may proceed to the PTZ tracking process 1800. [0174]; in response to appropriately evaluating the one or more received tracks for PTZ camera assignment based on the various aspects of the tracks (steps 1804-1814), at step 1816 the system may assign the one or more PTZ cameras to the tracks, where the PTZ cameras furthermore automatically follow their assigned tracks for collecting video/image frames for determining if the tracks include a UAV (e.g., verifying the tracks). [0182]. See also [0173] – [0185], Fig. 17-19).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 33, Seeber teaches adjusting the user device camera settings in response to the common authenticated data and designated signatures ([0014], [0055], [0184] – [0185]).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 34, Seeber teaches providing a UAP signature recognition algorithm capable of calculating signatures corresponding to UAP movement data and generating UAP movement predictions based on the calculations ([0014], [0055], [0184] – [0185]), and triggering responsive adjustments to the camera settings based on the movement predictions ([0014], [0055], [0184] – [0185]).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 35, Seeber teaches producing UAP tracking data responsive to the camera adjustments ([0014], [0055], [0184] – [0185]); and adjusting the user device camera settings to track UAP movement in accordance with a set of UAP signatures corresponding to predictable UAP movements ([0173] – [0185], Fig. 17-19).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 36, the combination of Randall and Seeber teaches providing at least one artificial intelligence (AI) algorithm responsive to non-analogous signatures and authenticated UAP data to anticipate unpredictable movements of the UAP being observed (the process may proceed to step 1904, where the system performs object detection techniques on the one or more frames specifically for identifying UAVs, thus allowing the system to better follow the UAVs. According to various aspects of the present disclosure, the object detection techniques may include applying a neural network that has been trained for processing one or more image frames for identifying UAVs in an airspace, as well as for detecting objects that are easily confused with UAVs, within the frame. The neural network may be trained by using training data including historical images or streams with known successfully identified UAVs and erroneously identified UAVs. In a particular embodiment, the output from step 1804 may include one or more bounding boxes for encompassing the UAV (or other objects) within the frame, as well as one or more confidence scores indicative of the likelihood that the objects included in the bounding boxes are UAVs. For example, a PTZ captured frame processed at step 1904 may include both a UAV and a bird, and the system may recognize both as objects (or ROIs) within the frame to be encompassed with bounding boxes. The UAV included in the bounding box may be assigned an almost certain confidence score (e.g., 99%) in response to the UAV-specific object detection algorithms, while the bird may receive a lower confidence score (e.g., 5%), and thus the bird may be dismissed as a non-drone or non-UAV. [0184]); recording the unpredictable movements ([0173] - [0185], Fig. 17-19); storing unpredictable movement signatures for a previously recorded UAP sighting event as predictable ([0173] - [0185], Fig. 17-19); converting the newly stored movement signature into a set of tracking data enabling the user device camera settings to be adjusted to correspond to the tracking data ([0173] - [0185], Fig. 17-19; the video data analysis process 700 may indicate if the tracks followed by the PTZ cameras include a UAV. In various embodiments, at step 1704 it is determined that if a UAV is identified within the track, the process may proceed to the PTZ tracking process 1800. [0174]; in response to appropriately evaluating the one or more received tracks for PTZ camera assignment based on the various aspects of the tracks (steps 1804-1814), at step 1816 the system may assign the one or more PTZ cameras to the tracks, where the PTZ cameras furthermore automatically follow their assigned tracks for collecting video/image frames for determining if the tracks include a UAV (e.g., verifying the tracks). [0182]. See also [0173] – [0185], Fig. 17-19); and distributing the tracking data to the users (col. 3, lines 11-60 of Randall).
Therefore, 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 known technique of converting the reported data into instructions for collecting additional UAP data because such incorporation would help instruct the PTZ cameras to pan, tilt, and/or zoom with respect to the predicted position of the assigned track. [0173].
Consider claim 37, Randall teaches generating a report from the tracking data when the user device UAP tracking data is authenticated as capable of tracking the UAP (col. 4, lines 12-50); and transmitting the report to an independently configured responsive system capable of initiating an independent system response commensurate with its function (col. 4, lines 12-50).
Conclusion
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/TAT C CHIO/Primary Examiner, Art Unit 2486