DETAILED ACTION
This Office Action is in response to Request for Continued Examination, and Applicant’s Amendment and Remarks filed on 06/04/2026.
Claim 21 have been cancelled.
Claims 1-20 are pending for examination.
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 .
Response to Argument
Applicant’s arguments, see pages 8-14, filed 06/04/2026, with respect to the rejections of claims 1-20 under U.S.C. 103 have been fully considered and persuasive. Therefore, the rejections have been withdrawn. However, upon further consideration, a new ground of rejection is made in view of Maki et al. (JP-2022035771; hereafter Maki) as evidenced by Shin et al. (KR 20180076583 A; hereafter Shin), further evidenced by Alon et al. (US 8549028 B1; hereafter Alon), and Max et al. (US 11953341 B2; hereafter Max).
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1, 8, and 15 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 8, and 15 recite “wherein the at least one of the plurality of vehicles determines a type of event from the signal…” however the type of event is already obtained from the server when the server transmits a signal to the plurality of vehicles which includes the time, the location, and the type of event. Therefore, the vehicles do not determine the type of event. The examiner suggests that this limitation be amended to recite “receives a type of event from the signal”.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
101 Analysis – Step 1
Claims 1, 8, and 15 are directed to an (apparatus, method, etc.) for claimed invention/solution. Therefore, claims 1, 8, and 15 is within at least one of the four statutory categories.
101 Analysis – Step 2A Prong I
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes. In this case, the independent claim(s) 1, 8, and 15 are directed to an abstract idea without significantly more. Specifically, the claims, under their broadest reasonable interpretation cover certain mental processes. The language of independent claim 1 is used for illustration:
A method, implemented by programmed one or more processors in a server, for collecting evidence to investigate an event, the method comprising:
obtaining a time, a location, and a type of the event for the event to be investigated, wherein the type of the event includes both a category and a sub-category;
transmitting a signal including the time, the location, and the type of the event for requesting sensor data corresponding to the event from a plurality of vehicles;
receiving the sensor data corresponding to the event from at least one of the plurality of vehicles based on the time, the location, and the type of the event of the signal; and
providing the received sensor data for investigating the event,
wherein the at least one of the plurality of vehicles determines a type of the event from the signal and determines a type of sensor data associated with the type of the event (a user would be able to mentally make a determination of the type of event from data received and determine what types of sensor data correspond to the sensor data), and provides the determined type of sensor data as the sensor data corresponding to the event, and
wherein the obtaining the time, the location, and the type of the event comprises performing keyword extraction on a report of the event to determine or extract the time, the location, and the type of the event from the report. (a user would be able to mentally determine keyword extraction by reading a report and mentally selecting keywords)
As explained above, independent claim 1 recites at least one abstract idea. The other independent claims 8 and 15, which are of similar scope to claim 1. Likewise recite at least one abstract idea under Step 2A, Prong I.
101 Analysis - Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a "practical application."
In this case, the mental processes/certain methods of organizing human activity/mathematical concepts judicial exception is/are not integrated into a practical application. For example, independent claims 1, 8, and 15 recite the additional elements of (recite all limitations from the illustrated independent claim AND the remaining independent claims which don’t recite a judicial exception). These limitations around to implementing the abstract idea on a computer, add insignificant extra solution activity, and /or generally link use of the judicial exception to a particular technological environment or field of use; see at least MPEP 2106.04(d). More specifically:
A method, implemented by programmed one or more processors in a server, for collecting evidence to investigate an event, the method comprising:
obtaining a time, a location, and a type of the event for the event to be investigated, wherein the type of the event includes both a category and a sub-category;
transmitting a signal including the time, the location, and the type of the event for requesting sensor data corresponding to the event from a plurality of vehicles;
receiving the sensor data corresponding to the event from at least one of the plurality of vehicles based on the time, the location, and the type of the event of the signal; and
providing the received sensor data for investigating the event,
wherein the at least one of the plurality of vehicles determines a type of the event from the signal and determines a type of sensor data associated with the type of the event (a user would be able to mentally make a determination of the type of event from data received and determine what types of sensor data correspond to the sensor data), and provides the determined type of sensor data as the sensor data corresponding to the event, and
wherein the obtaining the time, the location, and the type of the event comprises performing keyword extraction on a report of the event to determine or extract the time, the location, and the type of the event from the report. (a user would be able to mentally determine keyword extraction by reading a report and mentally selecting keywords)
Limitations “obtaining a time, a location, and a type of the event for the event to be investigated, wherein the type of the event includes both a category and a sub-category”, “transmitting a signal including the time, the location, and the type of the event for requesting sensor data corresponding to the event from a plurality of vehicles”, “receiving the sensor data corresponding to the event from at least one of the plurality of vehicles based on the time, the location, and the type of the event of the signal”, ” providing the received sensor data for investigating the event”, and “provides the determined type of sensor data as the sensor data corresponding to the event” are merely insignificant extra-solution activity of data transmission.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the 2019 PEG, the claims do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application in Step 2A, Prong II, the additional element of limiting the use of the idea to one particular environment employs generic computer functions to execute the abstract idea and, therefore does not add significantly more. Limiting the use of the abstract idea to a particular environment or field of use cannot provide an inventive concept. Additionally, as discussed above, the limitations “obtaining a time, a location, and a type of the event for the event to be investigated, wherein the type of the event includes both a category and a sub-category”, “transmitting a signal including the time, the location, and the type of the event for requesting sensor data corresponding to the event from a plurality of vehicles”, “receiving the sensor data corresponding to the event from at least one of the plurality of vehicles based on the time, the location, and the type of the event of the signal”, ” providing the received sensor data for investigating the event”, and “provides the determined type of sensor data as the sensor data corresponding to the event” as recited above, are considered insignificant extra solution activities.
A conclusion that an additional element is insignificant extra solution activity in Step 2A must be re-evaluated in Step 2B to determine if the element is more than what is well-understood, routine, and conventional in the field. In this case, the additional limitations of “obtaining a time, a location, and a type of the event for the event to be investigated, wherein the type of the event includes both a category and a sub-category”, “transmitting a signal including the time, the location, and the type of the event for requesting sensor data corresponding to the event from a plurality of vehicles”, “receiving the sensor data corresponding to the event from at least one of the plurality of vehicles based on the time, the location, and the type of the event of the signal”, ” providing the received sensor data for investigating the event”, and “provides the determined type of sensor data as the sensor data corresponding to the event” are well-understood, routine, and conventional activities, because they have all been deemed insignificant extra solution activity by one or more Courts; see at least MPEP 2106.05(d) and MPEP 2106.05(g)
“obtaining a time, a location, and a type of the event for the event to be investigated, wherein the type of the event includes both a category and a sub-category”, “transmitting a signal including the time, the location, and the type of the event for requesting sensor data corresponding to the event from a plurality of vehicles”, “receiving the sensor data corresponding to the event from at least one of the plurality of vehicles based on the time, the location, and the type of the event of the signal”, ” providing the received sensor data for investigating the event”, and “provides the determined type of sensor data as the sensor data corresponding to the event”… is considered well-understood, routine, and conventional activity under Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016);
Because the claims fail to recite anything sufficient to amount to significantly more than the judicial exception, independent claims 1, 8, and 15 are patent ineligible under 35 U.S.C. 101.
Dependent claims 2-7, 9-14, and 16-20 do not recite any further limitations that cause the claim to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application. These claims merely provide additional data gathering means (dependent claims that fall under this category), or further narrow down the mental process (dependent claims that fall under this category), neither of which integrate the judicial exception into a practical application. Therefore, dependent claim(s) 2-7, 9-14, and 16-20 are not patent eligible under the same rationale as provided for in the rejection of independent claim(s) 1, 8, and 15.
Examiner encourages Applicant to set an interview to discuss potential amendments for overcoming the above rejections under 35 U.S.C. § 101.
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.
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.
Claims 1-3, 7-10, 14-17 are rejected under 35 U.S.C. 103 as being anticipated by Maki as evidenced by Shin and further evidenced by Alon.
Maki, Shin, and Alon were cited in the previous Office action.
Regarding claim 1, Maki discloses:
A method, implemented by programmed one or more processors in a server, for collecting evidence to investigate an event, the method comprising:
obtaining a time, a location, to be investigated ([0022]; “When a request for information is received from the police or other authorities, the service provider PC 100 or the customer PC 30 can search for video data that meets the conditions (retention conditions) within the recorded data of the vehicle-mounted device 10 installed in each vehicle 90, using the date (time information), location information (latitude and longitude information), and radius information as conditions.”);
transmitting a signal including the time, the location, for requesting sensor data corresponding to the event from a plurality of vehicles; ([0040]; “The communication unit 32 transmits, via the server 80, to the vehicle-mounted device 10, a data storage command (specification information) for specifying video data corresponding to the associated information that meets the storage conditions.”);
receiving the sensor data corresponding to the event from at least one of the plurality of vehicles based on the time, the location; and
([0061]; “Furthermore, according to this embodiment, the service provider PC 100 or the customer PC 30 searches for accompanying information that meets the retention conditions in the vehicle image list (stored data list 300 transmitted from multiple vehicle-mounted devices 10) stored in the database 85.”)
[0062]; “The data may be transmitted from the vehicle-mounted device 10 to the service provider PC 100, and then transmitted from the service provider PC 100 to a communication terminal of an external organization.”)
providing the received sensor data for investigating the event. ([0062]; “The data may be transmitted from the vehicle-mounted device 10 to the service provider PC 100, and then transmitted from the service provider PC 100 to a communication terminal of an external organization.”)
wherein the obtaining the time, the location, and the type of the event comprises performing keyword extraction on a report of the event to determine or extract the time, the location, and the type of the event from the report. ([0055]; “Based on the information request, the service provider PC 100 inputs the latitude, longitude, time, and radius (xx m) as search keys (step S3), and executes a search (step S4).”
Note: Under the broadest reasonable interpretation, keyword extraction can merely be using keyword search functions that are readily available in typical computers and is considered common practice. It would be obvious to one of ordinary skill in the art to use such functions to gather the relevant keywords necessary from reports when requesting data from vehicles.)
Although Maki discloses requesting event data using parameters entered by the user as discussed above, Maki does not explicitly use an event type as one of the parameters.
However, Shin within the same field of endeavor does teach:
Obtaining a type of event ([0022]; “In a preferred embodiment, the application accesses the accident risk image database through the cloud server and outputs an accident search screen to the terminal for searching information, and the accident search screen includes an accident occurrence date and time and accident type input window for selecting and searching accident occurrence date and
time and accident type information”)
Transmitting a signal including the type of the event ([0020]; “In a preferred embodiment, the embedded board sends user information of the black box device, accident type information which is the type of the accident risk situation, accident occurrence date information, and accident occurrence location information to the cloud server along with accident risk image information.”)
Receiving the sensor data corresponding to the event from one of the plurality of vehicles based on the type of event of the signal ([0022]; “an accident occurrence list output window for outputting a list of accident occurrences searched through the accident occurrence date and time and accident type input window.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Maki with Shin. This modification would have been obvious as both Maki and Shin cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial for the user to specify an event type when requesting data to filter out unrelated data and only receive data relevant to the event being investigated.
Although Maki in combination with Shin teaches requesting event data using event types as a parameter entered by the user as discussed above, Maki in combination with Shin does not explicitly teach the use of both an event category and sub-category.
However, Alon within the same field of endeavor does teach:
Wherein the type of event includes both a category and a sub-category ([col. 16 lines 47-49]; “The sub-category section 544 provides information related to a sub-category within the selected main category that is selected for the currently displayed incident.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Maki with Shin and Alon. This modification would have been obvious as both Maki, Shin and Alon cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial for the user to specify an event type when requesting data to filter out unrelated data and only receive data relevant to the event being investigated.
Although Maki in combination with Shin and Alon teaches requesting event data using event types as a parameter entered by the user as discussed above, Maki in combination with Shin and Alon does not explicitly teach the vehicle determining the type of sensor data based on the type of the event.
However, Max within the same field of endeavor does teach:
wherein the at least one of the plurality of vehicles determines a type of the event from the signal and determines a type of sensor data associated with the type of the event, and provides the determined type of sensor data as the sensor data corresponding to the event ([col. 6 lines 25-30]; “The vehicle 2 reports available sensor data for a current route section and thus the type of sensors to the data-handling system 10 of the back-end computer 8, which communicates its requests or data wishes to the control apparatus 5 of the vehicle 2 via the vehicle management system 11.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Maki with Shin, Alon, and Max. This modification would have been obvious as both Maki, Shin, Alon and Max cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial for the vehicle to determine the relevant data type for the event.
Regarding claim 2, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 1. Additionally, Maki discloses the time comprises a time range corresponding to the event and/or the location comprises a location range corresponding to the event. ([0055]; “Based on the information request, the service provider PC 100 inputs the latitude, longitude, time, and radius (xx m) as search keys (step S3), and executes a search (step S4). The service provider PC 100 searches the recorded data in DB 85 (vehicle image list, stored data list 300 collected from each vehicle-mounted device 10) for data equivalent to the value entered in step S3 or this value with an error added (step S5). In step S5, the service providing PC 100 searches for data in which the recording start time 301 and the GPS 310 information (accompanying information) match the inputted value (+ error).”)
Regarding claim 3, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 1. Additionally, Maki discloses the sensor data comprises at least one of image data, LiDAR sensor data, accelerometer data, audio data, and infrared image data captured by onboard sensors of the vehicle. ([0026]-[0029]; “the camera I/F 16 has a function of taking in the image signals output by the cameras 23A and 23B, converting them into predetermined digital image data suitable for computer processing, and acquiring the image data.”)
Regarding claim 7, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 1. Additionally, Maki discloses performing, on the received sensor data, one or more of: pre-processing, converting, collating, and filtering. ([0028]; “…the camera I/F 16 has a function of taking in the image signals output by the cameras 23A and 23B, converting them into predetermined digital image data suitable for computer processing, and acquiring the image data.”)
Regarding claim 8, Maki discloses:
A system for collecting evidence to investigate an event, the system comprising:
a memory storing instructions ([0010]; “a recording unit that records the vehicle operation information including the video data and the time information and the location information in a memory unit, and a management unit that deletes the vehicle operation information recorded in the memory unit in accordance with the specified conditions”); and
at least one programmed processor configured to execute the instructions ([0030]; “A control unit 11 that realizes the main functions of the vehicle-mounted device 10 is composed of electronic circuits mainly including a processor of a microcomputer (CPU). This microcomputer executes a program stored in advance in the non-volatile memory 26A or the like, thereby realizing a control function of the vehicle-mounted device 10, which will be described later.”) to:
obtain a time, a location, for the event to be investigated ([0022]; “When a request for information is received from the police or other authorities, the service provider PC 100 or the customer PC 30 can search for video data that meets the conditions (retention conditions) within the recorded data of the vehicle-mounted device 10 installed in each vehicle 90, using the date (time information), location information (latitude and longitude information), and radius information as conditions.”);
transmit a signal including the time, the location, for requesting sensor data corresponding to the event from a plurality of vehicles ([0022]; “When a request for information is received from the police or other authorities, the service provider PC 100 or the customer PC 30 can search for video data that meets the conditions (retention conditions) within the recorded data of the vehicle-mounted device 10 installed in each vehicle 90, using the date (time information), location information (latitude and longitude information), and radius information as conditions.”);
receive the sensor data corresponding to the event from at least one of the plurality of vehicles based on the time, the location; and
([0061]; “Furthermore, according to this embodiment, the service provider PC 100 or the customer PC 30 searches for accompanying information that meets the retention conditions in the vehicle image list (stored data list 300 transmitted from multiple vehicle-mounted devices 10) stored in the database 85.”)
[0062]; “The data may be transmitted from the vehicle-mounted device 10 to the service provider PC 100, and then transmitted from the service provider PC 100 to a communication terminal of an external organization.”)
provide the received sensor data for investigating the event. ([0062]; “The data may be transmitted from the vehicle-mounted device 10 to the service provider PC 100, and then transmitted from the service provider PC 100 to a communication terminal of an external organization.”)
wherein the obtaining the time, the location, and the type of the event comprises performing keyword extraction on a report of the event to determine or extract the time, the location, and the type of the event from the report. ([0055]; “Based on the information request, the service provider PC 100 inputs the latitude, longitude, time, and radius (xx m) as search keys (step S3), and executes a search (step S4).”
Note: Under the broadest reasonable interpretation, keyword extraction can merely be using keyword search functions that are readily available in typical computers and is considered common practice. It would be obvious to one of ordinary skill in the art to use such functions to gather the relevant keywords necessary from reports when requesting data from vehicles.)
Although Maki discloses requesting event data using parameters entered by the user as discussed above, Maki does not explicitly use an event type as one of the parameters.
However, Shin within the same field of endeavor does teach:
Obtaining a type of event ([0022]; “In a preferred embodiment, the application accesses the accident risk image database through the cloud server and outputs an accident search screen to the terminal for searching information, and the accident search screen includes an accident occurrence date and time and accident type input window for selecting and searching accident occurrence date and
time and accident type information”)
Transmitting a signal including the type of the event ([0020]; “In a preferred embodiment, the embedded board sends user information of the black box device, accident type information which is the type of the accident risk situation, accident occurrence date information, and accident occurrence location information to the cloud server along with accident risk image information.”)
Receiving the sensor data corresponding to the event from one of the plurality of vehicles based on the type of event of the signal ([0022]; “an accident occurrence list output window for outputting a list of accident occurrences searched through the accident occurrence date and time and accident type input window.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Maki with Shin. This modification would have been obvious as both Maki and Shin cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial for the user to specify an event type when requesting data to filter out unrelated data and only receive data relevant to the event being investigated.
Although Maki in combination with Shin teaches requesting event data using event types as a parameter entered by the user as discussed above, Maki in combination with Shin does not explicitly teach the use of both an event category and sub-category.
However, Alon within the same field of endeavor does teach:
Wherein the type of event includes both a category and a sub-category ([col. 16 lines 47-49]; “The sub-category section 544 provides information related to a sub-category within the selected main category that is selected for the currently displayed incident.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Maki with Shin and Alon. This modification would have been obvious as both Maki, Shin and Alon cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial for the user to specify an event type when requesting data to filter out unrelated data and only receive data relevant to the event being investigated.
Although Maki in combination with Shin and Alon teaches requesting event data using event types as a parameter entered by the user as discussed above, Maki in combination with Shin and Alon does not explicitly teach the vehicle determining the type of sensor data based on the type of the event.
However, Max within the same field of endeavor does teach:
wherein the at least one of the plurality of vehicles determines a type of the event from the signal and determines a type of sensor data associated with the type of the event, and provides the determined type of sensor data as the sensor data corresponding to the event ([col. 6 lines 25-30]; “The vehicle 2 reports available sensor data for a current route section and thus the type of sensors to the data-handling system 10 of the back-end computer 8, which communicates its requests or data wishes to the control apparatus 5 of the vehicle 2 via the vehicle management system 11.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Maki with Shin, Alon, and Max. This modification would have been obvious as both Maki, Shin, Alon and Max cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial for the vehicle to determine the relevant data type for the event.
Regarding claim 9, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 8. Additionally, Maki discloses the time comprises a time range corresponding to the event and/or the location comprises a location range corresponding to the event. ([0055]; “Based on the information request, the service provider PC 100 inputs the latitude, longitude, time, and radius (xx m) as search keys (step S3), and executes a search (step S4). The service provider PC 100 searches the recorded data in DB 85 (vehicle image list, stored data list 300 collected from each vehicle-mounted device 10) for data equivalent to the value entered in step S3 or this value with an error added (step S5). In step S5, the service providing PC 100 searches for data in which the recording start time 301 and the GPS 310 information (accompanying information) match the inputted value (+ error).”)
Regarding claim 10, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 8. Additionally, Maki discloses the sensor data comprises at least one of image data, LiDAR sensor data, accelerometer data, audio data, and infrared image data captured by onboard sensors of the vehicle. ([0026]-[0029]; “the camera I/F 16 has a function of taking in the image signals output by the cameras 23A and 23B, converting them into predetermined digital image data suitable for computer processing, and acquiring the image data.”)
Regarding claim 14, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 8. Additionally, Maki discloses at least one programmed processor is further configured to execute the instructions to perform, on the received sensor data, one or more of: pre-processing, converting, collating, and filtering. ([0028]; “…the camera I/F 16 has a function of taking in the image signals output by the cameras 23A and 23B, converting them into predetermined digital image data suitable for computer processing, and acquiring the image data.”)
Regarding claim 15, Maki discloses:
A non-transitory computer-readable recording medium having recorded thereon instructions executable by at least one programmed processor to cause the at least one programmed processor to perform a method for collecting evidence to investigate an event ([0030]; “A control unit 11 that realizes the main functions of the vehicle-mounted device 10 is composed of electronic circuits mainly including a processor of a microcomputer (CPU). This microcomputer executes a program stored in advance in the non-volatile memory 26A or the like, thereby realizing a control function of the vehicle-mounted device 10, which will be described later.”), the method comprising:
obtaining a time, a location, for the event to be investigated; ([0022]; “When a request for information is received from the police or other authorities, the service provider PC 100 or the customer PC 30 can search for video data that meets the conditions (retention conditions) within the recorded data of the vehicle-mounted device 10 installed in each vehicle 90, using the date (time information), location information (latitude and longitude information), and radius information as conditions.”);
transmitting a signal including the time, the location, for requesting sensor data corresponding to the event from a plurality of vehicles; ([0022]; “When a request for information is received from the police or other authorities, the service provider PC 100 or the customer PC 30 can search for video data that meets the conditions (retention conditions) within the recorded data of the vehicle-mounted device 10 installed in each vehicle 90, using the date (time information), location information (latitude and longitude information), and radius information as conditions.”);
receiving the sensor data corresponding to the event from at least one of the plurality of vehicles based on the time, the location; and
([0061]; “Furthermore, according to this embodiment, the service provider PC 100 or the customer PC 30 searches for accompanying information that meets the retention conditions in the vehicle image list (stored data list 300 transmitted from multiple vehicle-mounted devices 10) stored in the database 85.”)
[0062]; “The data may be transmitted from the vehicle-mounted device 10 to the service provider PC 100, and then transmitted from the service provider PC 100 to a communication terminal of an external organization.”)
providing the received sensor data for investigating the event. ([0062]; “The data may be transmitted from the vehicle-mounted device 10 to the service provider PC 100, and then transmitted from the service provider PC 100 to a communication terminal of an external organization.”)
wherein the obtaining the time, the location, and the type of the event comprises performing keyword extraction on a report of the event to determine or extract the time, the location, and the type of the event from the report. ([0055]; “Based on the information request, the service provider PC 100 inputs the latitude, longitude, time, and radius (xx m) as search keys (step S3), and executes a search (step S4).”
Note: Under the broadest reasonable interpretation, keyword extraction can merely be using keyword search functions that are readily available in typical computers and is considered common practice. It would be obvious to one of ordinary skill in the art to use such functions to gather the relevant keywords necessary from reports when requesting data from vehicles.)
Although Maki discloses requesting event data using parameters entered by the user as discussed above, Maki does not explicitly use an event type as one of the parameters.
However, Shin within the same field of endeavor does teach:
Obtaining a type of event ([0022]; “In a preferred embodiment, the application accesses the accident risk image database through the cloud server and outputs an accident search screen to the terminal for searching information, and the accident search screen includes an accident occurrence date and time and accident type input window for selecting and searching accident occurrence date and
time and accident type information”)
Transmitting a signal including the type of the event ([0020]; “In a preferred embodiment, the embedded board sends user information of the black box device, accident type information which is the type of the accident risk situation, accident occurrence date information, and accident occurrence location information to the cloud server along with accident risk image information.”)
Receiving the sensor data corresponding to the event from one of the plurality of vehicles based on the type of event of the signal ([0022]; “an accident occurrence list output window for outputting a list of accident occurrences searched through the accident occurrence date and time and accident type input window.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Maki with Shin. This modification would have been obvious as both Maki and Shin cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial for the user to specify an event type when requesting data to filter out unrelated data and only receive data relevant to the event being investigated.
Although Maki in combination with Shin teaches requesting event data using event types as a parameter entered by the user as discussed above, Maki in combination with Shin does not explicitly teach the use of both an event category and sub-category.
However, Alon within the same field of endeavor does teach:
Wherein the type of event includes both a category and a sub-category ([col. 16 lines 47-49]; “The sub-category section 544 provides information related to a sub-category within the selected main category that is selected for the currently displayed incident.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Maki with Shin and Alon. This modification would have been obvious as both Maki, Shin and Alon cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial for the user to specify an event type when requesting data to filter out unrelated data and only receive data relevant to the event being investigated.
Although Maki in combination with Shin and Alon teaches requesting event data using event types as a parameter entered by the user as discussed above, Maki in combination with Shin and Alon does not explicitly teach the vehicle determining the type of sensor data based on the type of the event.
However, Max within the same field of endeavor does teach:
wherein the at least one of the plurality of vehicles determines a type of the event from the signal and determines a type of sensor data associated with the type of the event, and provides the determined type of sensor data as the sensor data corresponding to the event ([col. 6 lines 25-30]; “The vehicle 2 reports available sensor data for a current route section and thus the type of sensors to the data-handling system 10 of the back-end computer 8, which communicates its requests or data wishes to the control apparatus 5 of the vehicle 2 via the vehicle management system 11.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Maki with Shin, Alon, and Max. This modification would have been obvious as both Maki, Shin, Alon and Max cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial for the vehicle to determine the relevant data type for the event.
Regarding claim 16, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 15. Additionally, Maki discloses the time comprises a time range corresponding to the event and/or the location comprises a location range corresponding to the event. ([0055]; “Based on the information request, the service provider PC 100 inputs the latitude, longitude, time, and radius (xx m) as search keys (step S3), and executes a search (step S4). The service provider PC 100 searches the recorded data in DB 85 (vehicle image list, stored data list 300 collected from each vehicle-mounted device 10) for data equivalent to the value entered in step S3 or this value with an error added (step S5). In step S5, the service providing PC 100 searches for data in which the recording start time 301 and the GPS 310 information (accompanying information) match the inputted value (+ error).”)
Regarding claim 17, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 15. Additionally, Maki discloses the sensor data comprises at least one of image data, LiDAR sensor data, accelerometer data, audio data, and infrared image data captured by onboard sensors of the vehicle. ([0026]-[0029]; “the camera I/F 16 has a function of taking in the image signals output by the cameras 23A and 23B, converting them into predetermined digital image data suitable for computer processing, and acquiring the image data.”)
Claims 4, 11, and 18 are rejected under 35 U.S.C. 103 as being obvious in view of Maki as evidenced by Shin, Alon and Max as applied to claims 1, 8, and 15 above, and further evidenced by Walsh et al. (CA 3065731 A1; hereafter Walsh).
Walsh was cited in the previous Office action.
Regarding claim 4, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 1. Additionally, Walsh in the same field of endeavor teaches the receiving the sensor data comprises receiving the sensor data from another server that anonymizes the sensor data. ([0020]; “Secure data transmission protocols and/or encryption may be used in file transfers to protect the integrity of the data, for example, File Transfer Protocol (FTP), Secure File Transfer Protocol (SFTP), and/or Pretty Good Privacy (PGP) encryption.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Maki, Shin, Alon and Max with Walsh. This modification would have been obvious as both Maki, Shin, Alon, Max, and Walsh cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial to add the additional step of anonymizing the vehicle data to help protect the vehicle data from data breaches and ensures that the vehicle data is viewed only by intended individuals. SFTP and PGP are also encryption methods well known by those with ordinary skill in the art.
Regarding claim 11, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 8. Additionally, Walsh in the same field of endeavor teaches the receiving the sensor data comprises receiving the sensor data from another server that anonymizes the sensor data. ([0020]; “Secure data transmission protocols and/or encryption may be used in file transfers to protect the integrity of the data, for example, File Transfer Protocol (FTP), Secure File Transfer Protocol (SFTP), and/or Pretty Good Privacy (PGP) encryption.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Maki, Shin, Alon and Max with Walsh. This modification would have been obvious as both Maki, Shin, Alon, Max, and Walsh cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial to add the additional step of anonymizing the vehicle data to help protect the vehicle data from data breaches and ensures that the vehicle data is viewed only by intended individuals. SFTP and PGP are also encryption methods well known by those with ordinary skill in the art.
Regarding claim 18, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 15. Additionally, Walsh in the same field of endeavor teaches the receiving the sensor data comprises receiving the sensor data from another server that anonymizes the sensor data. ([0020]; “Secure data transmission protocols and/or encryption may be used in file transfers to protect the integrity of the data, for example, File Transfer Protocol (FTP), Secure File Transfer Protocol (SFTP), and/or Pretty Good Privacy (PGP) encryption.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Maki, Shin, Alon and Max with Walsh. This modification would have been obvious as both Maki, Shin, Alon, Max, and Walsh cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial to add the additional step of anonymizing the vehicle data to help protect the vehicle data from data breaches and ensures that the vehicle data is viewed only by intended individuals. SFTP and PGP are also encryption methods well known by those with ordinary skill in the art.
Claims 5, 12, and 19 are rejected under 35 U.S.C. 103 as being obvious in view of Maki as evidenced with Shin, Alon and Max as applied to claims 1, 8, and 15 above, and further in view of Moeller et al. (US 2022/0161760; hereafter Moeller).
Moeller was cited in the previous Office action.
Regarding claim 5, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 1. Additionally, Moeller in the same field of endeavor teaches processing the received sensor data, ([0028]; “sensor comprises an infrared camera and the method further comprises: A) reading, via the at least one computing device, a plurality of infrared frames from the infrared camera; B) identifying, via the at least one computing device, an area with a thermal variance in at least one of the plurality of infrared frames;”)
wherein the received sensor data comprises infrared image data ([0028]; “sensor comprises an infrared camera and the method further comprises: A) reading, via the at least one computing device, a plurality of infrared frames from the infrared camera; B) identifying, via the at least one computing device, an area with a thermal variance in at least one of the plurality of infrared frames;”), and
wherein the processing the received sensor data comprises determining whether the infrared image data includes a shape of an object with a temperature greater than a predetermined threshold. ([0028]; “C) monitor a temperature of the area with the thermal variance, wherein determining that the particular event has occurred further comprises determining that the temperature of the area exceeds a temperature threshold.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Maki, Shin, Alon and Max with Moeller. This modification would have been obvious as both Maki, Shin, Alon, Max, and Moeller cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial to include infrared image data/processing with the vehicle data/processing found in Maki in order to gather more information regarding the event. Adding additional data will provide the investigator with more evidence that may be crucial to their investigation.
Regarding claim 12, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 8. Additionally, Moeller in the same field of endeavor teaches process the received sensor data, ([0028]; “sensor comprises an infrared camera and the method further comprises: A) reading, via the at least one computing device, a plurality of infrared frames from the infrared camera; B) identifying, via the at least one computing device, an area with a thermal variance in at least one of the plurality of infrared frames;”)
wherein the received sensor data comprises infrared image data, and ([0028]; “sensor comprises an infrared camera and the method further comprises: A) reading, via the at least one computing device, a plurality of infrared frames from the infrared camera; B) identifying, via the at least one computing device, an area with a thermal variance in at least one of the plurality of infrared frames;”),
wherein the processing the received sensor data comprises determining whether the infrared image data includes a shape of an object with a temperature greater than a predetermined threshold. ([0028]; “C) monitor a temperature of the area with the thermal variance, wherein determining that the particular event has occurred further comprises determining that the temperature of the area exceeds a temperature threshold.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Maki, Shin, Alon and Max with Moeller. This modification would have been obvious as both Maki, Shin, Alon, Max, and Moeller cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial to include infrared image data/processing with the vehicle data/processing found in Maki in order to gather more information regarding the event. Adding additional data will provide the investigator with more evidence that may be crucial to their investigation.
Regarding claim 19, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 15. Additionally, Moeller in the same field of endeavor teaches processing the received sensor data, ([0028]; “sensor comprises an infrared camera and the method further comprises: A) reading, via the at least one computing device, a plurality of infrared frames from the infrared camera; B) identifying, via the at least one computing device, an area with a thermal variance in at least one of the plurality of infrared frames;”)
wherein the received sensor data comprises infrared image data, and ([0028]; “sensor comprises an infrared camera and the method further comprises: A) reading, via the at least one computing device, a plurality of infrared frames from the infrared camera; B) identifying, via the at least one computing device, an area with a thermal variance in at least one of the plurality of infrared frames;”)
wherein the processing the received sensor data comprises determining whether the infrared image data includes a shape of an object with a temperature greater than a predetermined threshold. ([0028]; “C) monitor a temperature of the area with the thermal variance, wherein determining that the particular event has occurred further comprises determining that the temperature of the area exceeds a temperature threshold.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Maki, Shin, Alon and Max with Moeller. This modification would have been obvious as both Maki, Shin, Alon, Max, and Moeller cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial to include infrared image data/processing with the vehicle data/processing found in Maki in order to gather more information regarding the event. Adding additional data will provide the investigator with more evidence that may be crucial to their investigation.
Claims 6, 13, and 20 are rejected under 35 U.S.C. 103 as being obvious in view of Maki as evidenced by Shin and Alon as applied to claims 1, 8, and 15 above, and further in view of Castano et al. (US 2021/0097784; hereafter Castano).
Castano was cited in the previous Office action.
Regarding claim 6, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 1. Additionally, Castano in the same field of endeavor teaches processing the received sensor data, ([0027]; “The image sensor 108 may detect image data corresponding to light in one or more of the visible spectrum, the infrared spectrum, the ultraviolet spectrum, or any other light spectrum.”)
wherein the received sensor data comprises LiDAR sensor data ([0027]; “The image sensor 108 may include… ranging (LIDAR) sensor”), and
wherein the processing the received sensor data comprises determining whether the event is captured based on the LiDAR sensor data. ([0095]; “…the server may identify that image data immediately before and immediately after the event would assist in analyzing the vehicle event.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Maki, Shin, Alon and Max with Castano. This modification would have been obvious as both Maki, Shin, Alon, Max, and Castano cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial to include LiDAR sensor data/processing with the vehicle data/processing found in Maki in order to gather more information regarding the event. Adding additional data will provide the investigator with more evidence that may be crucial to their investigation.
Regarding claim 13, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 8. Additionally, Castano in the same field of endeavor teaches the at least one programmed processor is further configured to execute the instructions to:
process the received sensor data, ([0027]; “The image sensor 108 may detect image data corresponding to light in one or more of the visible spectrum, the infrared spectrum, the ultraviolet spectrum, or any other light spectrum.”)
wherein the received sensor data comprises LiDAR sensor data, and ([0027]; “The image sensor 108 may include… ranging (LIDAR) sensor”),
wherein the processing the received sensor data comprises determining whether the event is captured based on the LiDAR sensor data. ([0095]; “…the server may identify that image data immediately before and immediately after the event would assist in analyzing the vehicle event.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Maki, Shin, Alon and Max with Castano. This modification would have been obvious as both Maki, Shin, Alon, Max, and Castano cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial to include LiDAR sensor data/processing with the vehicle data/processing found in Maki in order to gather more information regarding the event. Adding additional data will provide the investigator with more evidence that may be crucial to their investigation.
Regarding claim 20, Maki in combination with Shin, Alon and Max teaches all of the limitations of claim 15. Additionally, Castano in the same field of endeavor teaches processing the received sensor data, ([0027]; “The image sensor 108 may detect image data corresponding to light in one or more of the visible spectrum, the infrared spectrum, the ultraviolet spectrum, or any other light spectrum.”)
wherein the received sensor data comprises LiDAR sensor data, and ([0027]; “The image sensor 108 may include… ranging (LIDAR) sensor”),
wherein the processing the received sensor data comprises determining whether the event is captured based on the LiDAR sensor data. ([0095]; “…the server may identify that image data immediately before and immediately after the event would assist in analyzing the vehicle event.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Maki, Shin, Alon and Max with Castano. This modification would have been obvious as both Maki, Shin, Alon, Max, and Castano cover subject matter within the same field of endeavor (vehicle event detection and analysis) and it would have been beneficial to include LiDAR sensor data/processing with the vehicle data/processing found in Maki in order to gather more information regarding the event. Adding additional data will provide the investigator with more evidence that may be crucial to their investigation.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRANDON SUNG EUN LEE whose telephone number is (571)272-5684. The examiner can normally be reached Monday - Friday 9:00 am - 5:00 pm.
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/B.S.L./Examiner, Art Unit 3668
/ABDHESH K JHA/Primary Examiner, Art Unit 3668
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