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 Amendments
The amendment and response filed on November 11, 2025, to the Non-Final Office Action dated August 18, 2025 has been entered. Claims 1, 11, and 12 are amended. Claims 1 - 12 are pending in this application.
Response to Arguments
Applicant’s arguments and amendments, see pages 5-7, filed November 11, 2025, with respect to the 35 U.S.C. § 101 rejection since claim 11 have been considered but are not persuasive since this claim continues to recite a program embodied in a medium . The Examiner offers the following claim language as a possibility:” a non-transitory computer-readable medium storing instructions that, when executed by at least one processor, are configured to cause at least one processor to perform fishing tackle management … “.
Applicant’s arguments and amendments, see pages 5-7, filed November 11, 2025, with respect to the 35 U.S.C. § 103 rejection based on Kano et al (US-20230225305-A1), Motoki FURUKAWA (US-20220061295-A1), and Kuwata et al (US-20060253298-A1) have been considered and are persuasive. The 35 U.S.C. § 103 rejection of claims 1-12 has been withdrawn. However, upon further consideration, a new ground of rejection is made in view of further limiting amendments made, changing the scope of the claimed invention.
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.
Claim 11 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claim is directed to "fishing tackle management program ", can encompass non-statutory transitory forms of signal transmission, such as a propagating electrical or electromagnetic signal per se. (See In re Nuijten, 500 F.3d 1346, 84 USPQ2d 1495 (Fed. Cir. 2007).
Claim Rejections -- 35 U.S.C. § 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-9 and 11-12 are rejected under 35 U.S.C. 103 as being unpatentable over Kano et al (US-20230225305-A1)(“Kano”), Motoki FURUKAWA (US-20220061295-A1)(“Furukawa”), and Lee et al (KR-20210089416-A), machine translation is attached hereto.
Kano discloses a fishing tackle management system (Figure 1), comprising:
an identification unit to obtain identification results by identifying fishing tackle (Kano at Para. [0050] discloses acquiring tackle identification:" reel information may be stored in the terminal storage 33 of the terminal apparatus 3 possessed by a user of the fishing electric reel 2, or may be stored in the server storage 42 of the server apparatus 4 in association with identification information (user identification (ID) or the like) of the user of the fishing electric reel 2.”) ;
a determination unit to obtain determination results by determining fishing tackle matters based on the identification results of the identification unit (Kano at Figures 6, 9A, 11B and Para. [0050] disclosing data structure of fishing tackle matters:” reel information comprises model information, registration name information, real fishing history information, line input information, service history information, version information, or the like. The reel information is information stored in the reel storage 22. The reel information may be stored in the terminal storage 33 of the terminal apparatus 3 possessed by a user of the fishing electric reel 2, or may be stored in the server storage 42 of the server apparatus 4 in association with identification information (user identification (ID) or the like) of the user of the fishing electric reel 2.”); and
a notification unit to provide a notification to a user based on the determination results of the determination unit as notification information (Kano at Figures 7B & 8A, display unit 3, and Para. [0055] discloses how reel information is received by the user operating the fishing reel/tackle:” FIG. 7A is a diagram illustrating an example of the reel information request screen 700 displayed in the terminal apparatus 3. The reel information request screen 700 comprises, for example, a reel information request button 701. The reel information request button 701 is a button object for establishing short-range wireless communication between the fishing electric reel 2 and the terminal apparatus 3, and transmitting, to the fishing electric reel 2, a reel information request requesting that reel information be transmitted.”).
Kano does not disclose acquiring tackle information such as serial number and the like by using through an imaging unit like a camera. It is noted that Kano acquires such information through a storage of the information which in broadest sense it could be a marking at the reel that could be imaged using a mobile device like disclosed to acquire such information and would still be considered a storage of the identification.
Furukawa in the same field of endeavor discloses a fishing tool identification device where a mobile device like a smartphone acquires information from the tool that is then processed by a server to provide information to a user. See Figure 2 and Abstract.
Kano does not disclose but Furukawa discloses an identification unit to acquire identification of a fishing tackle/reel from an image (Furukawa at Figures 1-2 and Para. [0013] includes various technologies for acquiring initial identification from the fishing tackle including the reading of codes inscribed on the tool:” fishing tool identification device according to an embodiment of the present disclosure, the identification tag is configured to be any one of a bar code, a QR-code® or a RFID tag. Further, in the fishing tool identification device according to an embodiment of the present disclosure, the tag identification portion is configured to be capable of reading at least one of a bar code, a QR code®, or a RFID tag.”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the fishing reel management system as taught by Kano with the tool identification method as taught by Furukawa with a reasonable expectation of success in order for the one or more steps to confirm the identity of a reel from a collection of fishing reels. The teaching suggestion/motivation to combine is that by physically recording the identification on a fishing reel, cost can be reduced by eliminating the need for storage on the fishing tool since an inscribed tag could be read by a mobile device. See Furukawa at Para. [0038].
Kano and Furukawa do not disclose the use of trained model that using captured images can identified a fishing tackle.
Lee discloses a system that using artificial intelligence such as a learned model can identify and recognize an object from an image acquired through a camera. Like Kano and Furukawa images of an object such as a fishing tackle and an aptly programmed computer can analyze the images to determine the identity of the fishing equipment.
Kano and Furukawa do not disclose, but Lee discloses a process for using a learned model trained to identify the fishing tackle in accordance with captured images input for the purpose of identifying the fishing tackle (Lee at Para. [0039] discloses the use of a learned model that trained with images to recognize an object:” the color or character of the block is recognized from the manipulation image, and also the arrangement of the block is identified. In order to identify and recognize an object from an image acquired through a camera, a pre-learned data-set is required. Therefore, identification items according to various combinations of colors, characters, and arrangements that can be implemented through these blocks are input as images in advance, and a model learned through machine learning is generated. The recognition of step S230 is performed using the machine learning model generated in this way.”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the reel information unit as taught by Kano and modified by Furukawa with the machine learning model for identifying objects as taught by Lee with a reasonable expectation of success in order for the one or more method steps to be performed by a learned model to identify a fishing reel. The teaching suggestion/motivation to combine is that by using an artificial intelligence (learned) model, recognition performance can be improved as taught by Lee at Para. [0049].
As per claim 2, Kano, Furukawa, and Lee disclose a fishing tackle management system, wherein the determination unit is configured to determine maintenance matters related to the fishing tackle (Kano at Figure 15B, process for acquiring maintenance matters, and Para. [0100] discloses steps for acquiring maintenance matters:” illustrated in FIG. 15B, first, in a case where a user has input an instruction to display the maintenance screen 1110, by using the terminal operating part 34 of the terminal apparatus 3, the display processing unit 361 of the terminal apparatus 3 extracts the reel information stored in the terminal storage 33 (step S501). The instruction to display the maintenance screen 1110 is input, for example, in a case where the user has operated the terminal operating part 34 to provide an instruction to the maintenance display button 904 in the menu screen 900 displayed in the terminal display unit 35.”).
As per claim 3, Kano, Furukawa, and Lee disclose a fishing tackle management system, wherein the fishing tackle is a fishing reel (Kano Figure 1, fishing reel 2.), and the determination unit is configured to determine reel maintenance matters related to the fishing reel (Kano at Figure 1, server 4, and Para. [0102] discloses determining maintenance matters for a fishing reel:” maintenance screen 1110, various types of display information may be displayed together with the reel information or instead of the reel information, and an example of the various types of display information is URL information for a transition to a home page screen for maintenance that can be downloaded from an external Web server apparatus.”).
As per claim 4, Kano, Furukawa, and Lee disclose a fishing tackle management system, wherein the reel maintenance matters include at least one of scratches of the fishing reel, distortion of parts of the fishing reel, fishing line issues of a fishing line wound on a spool, and reel setting state issues of the fishing reel (Kano at Figure 6, fields for after-sales service history, and Para. [0027] indicating services performed by and on the reel which reasonably includes repairs to scratches and the like:” reel information comprises, for example, model information indicating a product name of the fishing electric reel 2, registration name information indicating a registration name that has been set by a user, real fishing history information indicating real fishing history (a winding-up length, a time period of use, or the like), line input information indicating input history (a type and a number of a line, a wound-line length (m), and the like) relating to a fishing line that has been input in the past, service history information indicating after-sales service history that has been set by a person in charge of after-sales service, setting information (function setting information) of various functions that are achieved according to the reel control program, and version information indicating a version of the reel control program. Note that the reel information may include some of these various types of information, or may include another piece of information relating to the fishing electric reel 2.”).
As per claim 5, Kano, Furukawa, and Lee disclose a fishing tackle management system, wherein the fishing tackle is a fishing rod (Kano Figure 1, fishing reel/rod 2.), and the determination unit is configured to determine rod maintenance matters related to fishing rod (Kano at Figure 7B and Para. [0101] discloses displaying maintenance screen at the fishing reel/rod:” the terminal display unit 35 displays the maintenance screen 1110, and therefore a user can view various pieces of information (a model name (a product name), date of an input of the line input information, or the like).”) .
As per claim 6, Kano, Furukawa, and Lee disclose a fishing tackle management system, wherein the rod maintenance matters include at least one of scratches of the fishing rod, distortion of the fishing rod, and rod setting state issues of the fishing rod (Kano at Figure 6, fields for after-sales service history, and Para. [0027] indicating services performed by and on the reel which reasonably includes repairs to scratches and the like:” reel information comprises, for example, model information indicating a product name of the fishing electric reel 2, registration name information indicating a registration name that has been set by a user, real fishing history information indicating real fishing history (a winding-up length, a time period of use, or the like), line input information indicating input history (a type and a number of a line, a wound-line length (m), and the like) relating to a fishing line that has been input in the past, service history information indicating after-sales service history that has been set by a person in charge of after-sales service, setting information (function setting information) of various functions that are achieved according to the reel control program, and version information indicating a version of the reel control program. Note that the reel information may include some of these various types of information, or may include another piece of information relating to the fishing electric reel 2.”).
As per claim 7, Kano, Furukawa, and Lee disclose a fishing tackle management system, wherein the rod setting state matters include line guide issues or reel seat issues, the line guide issues including scratches or distortion of the line guide, and the reel seat issues including scratches or distortion of the reel seat (Kano at Para. [0105] with Figure 9A, line input, discloses displaying line information and other reel information:” displaying the reel information relating to the fishing electric reel 2 (the menu screen 900, the line input screen 910, the function setting screen 1010, the registration name setting screen 1100, and the maintenance screen 1110) to a screen that corresponds to the latest reel control program.”).
As per claim 8, Kano, Furukawa, and Lee disclose a fishing tackle management system, wherein the identification unit is configured to obtain identification results by identifying fishing tackle from operation sounds of the fishing tackle (Kano at Para. [0085] discloses using operation sound at the fishing reel/rod:” the first function selection object 1011 is a button object for setting whether alarm sound will be output in the fishing electric reel 2.”), and the determination unit is configured to obtain determination results by determining fishing tackle matters based on the identification results of the identification unit (Kano at Para. [0085] discloses determination of tackle matters based on the selected condition concerning sound and tackle pattern: ” illustrated in FIG. 10B, an output of alarm sound has been set in the function setting information, and therefore a corresponding button has been selected in the first function selection object 1011.”).
As per claim 9, Kano, Furukawa, and Lee disclose a fishing tackle management system, wherein the determination unit is configured to determine maintenance matters related to performance of maintenance work of the fishing tackle (Kano at Figure 6 and Para. [0050] discloses tracking service history of the fishing reel which broadly is the performance of maintenance work:” reel information comprises model information, registration name information, real fishing history information, line input information, service history information, version information, or the like.”).
As per claim 11, Kano and Furukawa disclose a computer-readable medium storing instructions that, when executed by at least one processor, are configured to cause at least one processor to perform fishing tackle management of (See at least figures 1-2 & 13.) the fishing tackle management system, the fishing tackle management system, comprising an identification unit configured to obtain identification results by identifying fishing tackle from an image , a determination unit configured to obtain determination results by determining fishing tackle matters based on the identification results of the identification unit, and a notification unit configured to provide a notification to a user based on the determination results of the determination unit as notification information (See Above rejection of claim 1.).
Kano and Furukawa do not disclose the use of trained model that using captured images can identified a fishing tackle.
Lee discloses a system that using artificial intelligence such as a learned model can identify and recognize an object from an image acquired through a camera. Like Kano and Furukawa images of an object such as a fishing tackle and an aptly programmed computer can analyze the images to determine the identity of the fishing equipment.
Kano and Furukawa do not disclose, but Lee discloses a process for using a learned model trained to identify the fishing tackle in accordance with captured images input for the purpose of identifying the fishing tackle (Lee at Para. [0039] discloses the use of a learned model that trained with images to recognize an object:” the color or character of the block is recognized from the manipulation image, and also the arrangement of the block is identified. In order to identify and recognize an object from an image acquired through a camera, a pre-learned data-set is required. Therefore, identification items according to various combinations of colors, characters, and arrangements that can be implemented through these blocks are input as images in advance, and a model learned through machine learning is generated. The recognition of step S230 is performed using the machine learning model generated in this way.”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the reel information unit as taught by Kano and modified by Furukawa with the machine learning model for identifying objects as taught by Lee with a reasonable expectation of success in order for the one or more method steps to be performed by a learned model to identify a fishing reel. The teaching suggestion/motivation to combine is that by using an artificial intelligence (learned) model, recognition performance can be improved as taught by Lee at Para. [0049].
As per claim 12, Kano discloses a fishing tackle management system (Figure 1), comprising:
an identification means configured to obtain identification results by identifying fishing tackle (Kano at Para. [0050] discloses acquiring tackle identification:" reel information may be stored in the terminal storage 33 of the terminal apparatus 3 possessed by a user of the fishing electric reel 2, or may be stored in the server storage 42 of the server apparatus 4 in association with identification information (user identification (ID) or the like) of the user of the fishing electric reel 2.”)
a determination means configured to obtain determination results by determining fishing tackle matters based on the identification results of the identification unit (Kano at Figures 6, 9A, 11B and Para. [0050] disclosing data structure of fishing tackle matters:” reel information comprises model information, registration name information, real fishing history information, line input information, service history information, version information, or the like. The reel information is information stored in the reel storage 22. The reel information may be stored in the terminal storage 33 of the terminal apparatus 3 possessed by a user of the fishing electric reel 2, or may be stored in the server storage 42 of the server apparatus 4 in association with identification information (user identification (ID) or the like) of the user of the fishing electric reel 2.”); and
a notification means configured to provide a notification to a user based on the determination results of the determination unit as notification information (Kano at Figures 7B & 8A, display unit 3, and Para. [0055] discloses how reel information is received by the user operating the fishing reel/tackle:” FIG. 7A is a diagram illustrating an example of the reel information request screen 700 displayed in the terminal apparatus 3. The reel information request screen 700 comprises, for example, a reel information request button 701. The reel information request button 701 is a button object for establishing short-range wireless communication between the fishing electric reel 2 and the terminal apparatus 3, and transmitting, to the fishing electric reel 2, a reel information request requesting that reel information be transmitted.”).
Kano does not disclose acquiring tackle information such as serial number and the like by using through an imaging unit like a camera. It is noted that Kano acquires such information through a storage of the information which in broadest sense it could be a marking at the reel that could be imaged using a mobile device like disclosed to acquire such information and would still be considered a storage of the identification.
Furukawa in the same field of endeavor discloses a fishing tool identification device where a mobile device like a smartphone acquires information from the tool that is then processed by a server to provide information to a user. See Figure 2 and Abstract.
Kano does not disclose but Furukawa discloses an identification unit to acquire identification of a fishing tackle/reel from an image (Furukawa at Figures 1-2 and Para. [0013] includes various technologies for acquiring initial identification from the fishing tackle including the reading of codes inscribed on the tool:” fishing tool identification device according to an embodiment of the present disclosure, the identification tag is configured to be any one of a bar code, a QR-code® or a RFID tag. Further, in the fishing tool identification device according to an embodiment of the present disclosure, the tag identification portion is configured to be capable of reading at least one of a bar code, a QR code®, or a RFID tag.”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the fishing reel management system as taught by Kano with the tool identification method as taught by Furukawa with a reasonable expectation of success in order for the one or more steps to confirm the identity of a reel from a collection of fishing reels. The teaching suggestion/motivation to combine is that by physically recording the identification on a fishing reel, cost can be reduced by eliminating the need for storage on the fishing tool since an inscribed tag could be read by a mobile device. See Furukawa at Para. [0038].
Kano and Furukawa do not disclose the use of trained model that using captured images can identified a fishing tackle.
Lee discloses a system that using artificial intelligence such as a learned model can identify and recognize an object from an image acquired through a camera. Like Kano and Furukawa images of an object such as a fishing tackle and an aptly programmed computer can analyze the images to determine the identity of the fishing equipment.
Kano and Furukawa do not disclose, but Lee discloses a process for using a learned model trained to identify the fishing tackle in accordance with captured images input for the purpose of identifying the fishing tackle (Lee at Para. [0039] discloses the use of a learned model that trained with images to recognize an object:” the color or character of the block is recognized from the manipulation image, and also the arrangement of the block is identified. In order to identify and recognize an object from an image acquired through a camera, a pre-learned data-set is required. Therefore, identification items according to various combinations of colors, characters, and arrangements that can be implemented through these blocks are input as images in advance, and a model learned through machine learning is generated. The recognition of step S230 is performed using the machine learning model generated in this way.”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the reel information unit as taught by Kano and modified by Furukawa with the machine learning model for identifying objects as taught by Lee with a reasonable expectation of success in order for the one or more method steps to be performed by a learned model to identify a fishing reel. The teaching suggestion/motivation to combine is that by using an artificial intelligence (learned) model, recognition performance can be improved as taught by Lee at Para. [0049].
Claim 10 is are rejected under 35 U.S.C. 103 as being unpatentable over Kano, Furukawa, and Lee as applied to claim 1 above, and further in view of Kuwata et al (US-20060253298-A1)(“Kuwata”).
As per claim 10, Kano, Furukawa, and Lee disclose a fishing tackle management system.
Kano, Furukawa, and Lee do not disclose but Kuwata discloses wherein the notification unit is configured to provide a user cost information based on maintenance matters determined by the determination unit (Kuwata at Figure 1, fishing gear estimation system 100, and Para. [0062] discloses the use of software for determining the cost of a maintenance procedure on fishing gear:” storage device 2 stores a maintenance cost estimation program necessary for management of the overhaul cost estimation Web pages and necessary data. The server 1 executes the overhaul cost estimation function and other functions by using the maintenance cost estimation program and data stored in the storage device 2. The server 1 has an information acceptance component 4, a replacement part determination component 5, a cost computation component 6 and display 7.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the cost estimation method taught in Kuwata in the fishing reel management system as taught by Kano, Furukawa, and Lee with a reasonable expectation of success because this results in the fishing tackle being maintained as uniformly as possible over time which increases the lifetime of the fishing equipment (see Kuwata at Para. [0008]).
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 ELLIS B. RAMIREZ whose telephone number is (571)272-8920. The examiner can normally be reached 7:30 am to 5:00pm.
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/ELLIS B. RAMIREZ/Examiner, Art Unit 3658