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 .
Introduction
The following is a final Office action in response to Applicant’s submission filed on 12/24/2025. Currently claims 1-10, 12-13, 15-17 are pending and claims 1 and 15 are independent. Claims 1 and 15 have been amended from the previous claim set dated 7/30/2024. Claims 16 and 17 are new and claims 11 and 14 have been cancelled.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. 371 of PCT/JP2022/013532, filed on 3/23/2022.
Response to Amendments
Applicant’s amendments are acknowledged and necessitated the new grounds of rejection in this Office Action.
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 1-10, 12-13, 15-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea), specifically an abstract idea, without significantly more. With respect to claims 1-10, 12-13, 15-17, following the guidance contained within MPEP 2106, the inquiry for patent eligibility follows two steps: Step 1: Does the claimed invention fall within one of the four statutory categories of invention? Step 2A (Prong 1): Is the claim “directed to” an abstract idea? Step 2A (Prong 2): Is the claim integrated into a practical application? Step 2B: Does the claim recite additional elements that amount to “significantly more” than the abstract idea?
In accordance with these steps, the Examiner finds the following:
Step 1: Claim 1 and its dependent claims (claims 2-10, 12, 13, 16, 17) are directed to a statutory category, namely a system/machine. Claim 15 is directed to a statutory category, namely a method.
Step 2A (Prong 1): Claims 1 and 15, which are substantially similar claims to one another, are directed to the abstract idea of “Mental processes”, or more particularly, “Concepts performed in the human mind (including an observation, evaluation, judgment, opinion) (See MPEP 2106).” In this application that refers to using a computer system to evaluate how busy/congested a train or subway car is. To clarify this further, the Applicant’s disclosed invention is a conceptual system meant to perform the same function that rider might perform when entering a subway station. The abstract elements of claims 1 and 15 recite in part “Identify target car…Generate congestion information…Determine passenger input…Transmit information…”. Dependent claims 2-10, 13, 16, 17 add to the abstract idea the following limitations which recite in part “Extract car history…Generate congestion information…Obtain count information…Operation conditions include…Congestion information includes…Calculate passenger count…Transmit congestion information…Determine time point information…Determine station…Transmit congestion information…Determine target car…”. All of these additional limitations, however, only serve to further limit the abstract idea, and hence are nonetheless directed towards fundamentally the same abstract idea as independent claims 1 and 15. Dependent claim 12 does not include any limitations that are directed toward the abstract idea and will be addresses in either the Step 2A (Prong 2) or Step 2B analysis below.
Step 2A (Prong 2): Independent claims 1 and 15, which are substantially similar claims to one another, do not contain additional elements, either considered individually or in combination, that effectively integrate the exception into a practical application of the exception. These claims do include the limitation that recites in part “Information processing device…Car identifying unit…Congestion information generating unit…Communication unit…External display device…” which limits the claims to a networked/computer based environment, but this is insufficient with respect to integration into a practical application because it is merely applying the abstract idea to a general computer (See MPEP 2106.05(f)).
Dependent claims 2, 4, 12, 16 add the additional element which recites in part “History information extracting unit…Congestion information generating unit…Communications unit…External display device…Terminal device…Control unit…Storage unit…External Terminal device…” which again limits the claims to a networked/computer based environment, but this is again insufficient with respect to integration into a practical application because it is also merely applying the abstract idea to a general computer (See MPEP 2106.05(f)).
Additionally, dependent claims 3, 5-10, 13, 17 do not include any additional elements to conduct a further Step 2A (Prong 2) analysis.
Step 2B: Independent claims 1 and 15, which are substantially similar claims to one another, include additional elements, when considered both individually and as an ordered combination, which are insufficient to amount to significantly more than the judicial exception. The additional elements of these claims recite in part “Information processing device…Car identifying unit…Congestion information generating unit…Communication unit…External display device…”. These items are not significantly more because these are merely the software and/or hardware components used to implement the abstract idea (evaluate how busy/congested a train or subway car is) on a general purpose computer (See MPEP 2106.05(f)). This is exemplified in the Applicant’s specification in [0016] – “the control unit 11 can be such a control device as a central processing unit (CPU) or a micro processing unit (MPUJ).”
Dependent claims 2, 4, 12, 16 include additional elements, when considered both individually and as an ordered combination and in view of their respective independent claims, which are insufficient to amount to significantly more than the judicial exception. Specifically, dependent claims 2, 4, 11, 12 include the additional element which recites in part “History information extracting unit…Congestion information generating unit…Communications unit…External display device… Terminal device…Control unit…Storage unit…External Terminal device…” These are the similar additional elements to those that are addressed above in claims 1 and 15, and are not significantly more because these are again merely the software and/or hardware components used to implement the abstract idea (evaluate how busy/congested a train or subway car is) on a general purpose computer (See MPEP 2106.05(f)).
Additionally, dependent claims 3, 5-10, 13, 17 do not include any additional elements to conduct a further 2B analysis.
Accordingly, whether taken individually or as an ordered combination claims 1-10, 12-13, 15-17 are rejected under 35 USC § 101 because the claimed invention is directed to a judicial exception, an abstract idea, without significantly more.
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.
Claims 1, 7, 8, 9, 10, 12, 13, 15, 16, 17 are rejected under 35 U.S.C. 103 as being unpatentable over Kim et al. (KR 20220110399 A) in view of Meyer et al. (CN 112005562 A)
Regarding claims 1 and 15 (Amended), Kim discloses an information processing device (Kim ABS - A system for providing real-time public transport congestion comprises: a communication unit, a database, and a processor), comprising: a car being provided with a plurality of boarding doors (Kim - The raw data collected by the sensor includes the location data of the user terminal, data on the number of users getting on or off when opening and closing public transport doors, data on the number of users waiting on the platform, data on the number of users moving between compartments in public transportation, and public transportation at least one of internal seat availability data, total number of public transit users); and a congestion information generating unit configured to generate congestion information indicating a degree of congestion of interior areas each associated with one or a plurality of boarding doors of the target car running from the departure station to the destination station (Kim - FIG. 2A is a graph showing real-time congestion result data for each public transport entrance, and FIG. 2B is a graph showing real-time congestion result data for each public transport compartment) and a communications unit configured to transmit the congestion information to an external display device to display the congestion information (Kim ABS - the present invention properly distributes the number of users for each public transport compartment by using a color gradation display device installed in a platform).
Kim lacks a car identifying unit configured to identify a target car that a passenger gets on, in accordance with a departure station and a destination station of the passenger using a car, and with time point information, the departure station and the destination station are determined in accordance with an input by the passenger
Meyer, from the same field of endeavor, teaches a car identifying unit configured to identify a target car that a passenger gets on, in accordance with a departure station and a destination station of the passenger using a car, and with time point information (Meyer – Fig. 4 - For example, in some embodiments, the user may request to leave the vehicle congestion information of one or more specific traffic vehicles of the specific traffic station. For example, as depicted in FIG. 4, a user can select a specific traffic station (e.g., Maritime Museum Station). In some embodiments, a request from a user may include real-time location data for a particular user computing device. For example, a user at the maritime museum station may send a request for a traffic vehicle leaving the maritime museum station, and the request may include real-time location data for the user. In other user interface, the user can in other ways (such as access collection list, searching specific traffic vehicle and/or traffic station, selecting from the list of the previously riding traffic vehicle) to request the vehicle congestion degree information, or other types of request), the departure station and the destination station are determined in accordance with an input by the passenger (Meyer – Fig. 4)
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the train congestion methodology/system of Kim by including the real-time congestion techniques of Meyer because Meyer discloses “it can improve the whole efficiency of the traffic system (Meyer)”. Additionally, Kim further details that “The present disclosure relates to a system that provides real-time congestion and congestion prediction of public transportation such as subway and its platform, induces distribution of public transportation user density accordingly (Kim)” so it would be obvious to consider including the additional real-time congestion techniques that Meyer discloses because it would improve the efficiency of the system disclosed within Kim.
Regarding claim 7, Kim in view of Meyer discloses an information processing device (Kim ABS - A system for providing real-time public transport congestion comprises: a communication unit, a database, and a processor), comprising: a car being provided with a plurality of boarding doors (Kim - The raw data collected by the sensor includes the location data of the user terminal, data on the number of users getting on or off when opening and closing public transport doors, data on the number of users waiting on the platform, data on the number of users moving between compartments in public transportation, and public transportation at least one of internal seat availability data, total number of public transit users); and a congestion information generating unit configured to generate congestion information indicating a degree of congestion of interior areas each associated with one or a plurality of boarding doors of the target car running from the departure station to the destination station (Kim - FIG. 2A is a graph showing real-time congestion result data for each public transport entrance, and FIG. 2B is a graph showing real-time congestion result data for each public transport compartment).
Meyer further teaches the car identifying unit identifies the target car in accordance with an operation schedule including a time point at which cars depart from each of stations (Meyer – Fig. 4 - In some embodiments, as depicted in FIG. 4, can display information of a plurality of specific traffic vehicle in the user interface 400. For example, as depicted, six traffic vehicles 410A-F shown. can be, for example, traffic route (e.g., " B ", " F ", etc.), scheduling the leaving time (e.g., " 11: 15 ", etc.), traffic vehicle number (e.g., " 389 ", " 451 ", etc.), a traffic station (e.g., " Maritime Museum ") and/or other information to identify a particular traffic vehicle. In some embodiments, it may also provide additional information via user interface 400, such as a particular traffic vehicle is early, time or delay, traffic vehicle whether there is a barrier person can enter or other information).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the train congestion methodology/system of Kim by including the real-time congestion techniques of Meyer because Meyer discloses “it can improve the whole efficiency of the traffic system (Meyer)”. Additionally, Kim further details that “The present disclosure relates to a system that provides real-time congestion and congestion prediction of public transportation such as subway and its platform, induces distribution of public transportation user density accordingly (Kim)” so it would be obvious to consider including the additional real-time congestion techniques that Meyer discloses because it would improve the efficiency of the system disclosed within Kim.
Regarding claim 8, Kim in view of Meyer discloses the congestion information includes at least one of: an average congestion degree indicating an average of congestion degrees for each of the interior areas of the target car from the departure station to the destination station; or a maximum congestion degree indicating a maximum value of the congestion degrees for each of the interior areas of the target car from the departure station to the destination station (Kim - In addition, the data on public transportation congestion includes the average number of users of public transportation by time period, average congestion rate of public transportation by time period, public transportation congestion data by time period).
Regarding claim 9, Kim in view of Meyer discloses the congestion information generating unit: calculates an on-board passenger count for each of the interior areas of the target car in accordance with an image obtained by an interior imaging device provided in the target car; and generates the congestion information in accordance with the on-board passenger count (Kim - According to another embodiment, by installing an infrared sensor, a CO .sub.2 detection sensor, a face recognition sensor, a load sensor, etc. inside public transportation, it is possible to roughly collect the number of users for each compartment inside the current public transportation, and through this, the processor 120 can generate real-time congestion result data for each public transport car).
Regarding claim 10, Kim in view of Meyer discloses the congestion information generating unit: calculates a count of passengers getting on the target car at the departure station for each of the boarding doors of the target car, in accordance with an image obtained by a station imaging device provided to the departure station; and generates the congestion information in accordance with the count of the passengers getting on the target car at the departure station (Kim - In addition, referring to FIG. 4 , an infrared sensor, an electromagnetic wave sensor, or a facial recognition sensor is installed in the direction of the platform at each location where each train door enters, and the processor 120 collects the number of users to enter and exit each train door. Alternatively, congestion prediction data may be generated for each compartment, and the LED panel may be controlled to display public transportation congestion prediction data instead of real-time public transportation congestion result data).
Regarding claim 12, Kim in view of Meyer discloses the external display device includes at least any one or more of a terminal device used by the passenger, a ticket vending machine installed in the departure station, and an information display device installed in the departure station (Kim - The processor 120 may control data to be displayed on a display device of an external device through the communication unit 100. The external device may refer to a display device installed on at least one of a user terminal, public transportation, or a platform. The display device can display real-time public transport congestion result data and public transport congestion prediction data, and based on the data, the appropriate allocation data for the number of users for each public transport compartment in text, model, or color).
Regarding claim 13, Kim in view of Meyer discloses an information processing device (Kim ABS - A system for providing real-time public transport congestion comprises: a communication unit, a database, and a processor), comprising: a congestion information generating unit configured to generate congestion information indicating a degree of congestion of interior areas each associated with one or a plurality of boarding doors of the target car running from the departure station to the destination station (Kim - FIG. 2A is a graph showing real-time congestion result data for each public transport entrance, and FIG. 2B is a graph showing real-time congestion result data for each public transport compartment).
Meyer further teaches a car identifying unit configured to identify a target car that a passenger gets on, in accordance with a departure station and a destination station of the passenger using a car, and with time point information (Meyer – Fig. 4 - For example, in some embodiments, the user may request to leave the vehicle congestion information of one or more specific traffic vehicles of the specific traffic station. For example, as depicted in FIG. 4, a user can select a specific traffic station (e.g., Maritime Museum Station). In some embodiments, a request from a user may include real-time location data for a particular user computing device. For example, a user at the maritime museum station may send a request for a traffic vehicle leaving the maritime museum station, and the request may include real-time location data for the user. In other user interface, the user can in other ways (such as access collection list, searching specific traffic vehicle and/or traffic station, selecting from the list of the previously riding traffic vehicle) to request the vehicle congestion degree information, or other types of request).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the train congestion methodology/system of Kim by including the real-time congestion techniques of Meyer because Meyer discloses “it can improve the whole efficiency of the traffic system (Meyer)”. Additionally, Kim further details that “The present disclosure relates to a system that provides real-time congestion and congestion prediction of public transportation such as subway and its platform, induces distribution of public transportation user density accordingly (Kim)” so it would be obvious to consider including the additional real-time congestion techniques that Meyer discloses because it would improve the efficiency of the system disclosed within Kim.
Regarding claim 16, Kim in view of Meyer discloses a control unit including the car identifying unit and the congestion information generation unit; and a storage unit comprising a memory storing the congestion information to be transmitted, wherein the control unit is connected to the communication unit, wherein the communication unit transmits the congestion information from the control unit to an external terminal device (Kim Figs. 1- 6)
Regarding claim 17, Kim in view of Meyer discloses he congestion information is requested from the external terminal device to the control unit via the communication unit, the communication unit includes hardware to communicate with the external terminal device that includes the external display device, wherein the congestion information transmitted to the external display device includes information to determine a selection of the target car (Kim Figs. 1- 6)
Claims 2-6 are rejected under 35 U.S.C. 103 as being unpatentable over Kim et al. (KR 20220110399 A) in view of Meyer et al. (CN 112005562 A) further in view of Yamamoto (JP 2018144729 A)
Regarding claim 2, Kim in view of Meyer discloses an information processing device (Kim ABS - A system for providing real-time public transport congestion comprises: a communication unit, a database, and a processor), comprising: a congestion information generating unit configured to generate congestion information indicating a degree of congestion of interior areas each associated with one or a plurality of boarding doors of the target car running from the departure station to the destination station (Kim - FIG. 2A is a graph showing real-time congestion result data for each public transport entrance, and FIG. 2B is a graph showing real-time congestion result data for each public transport compartment).
Kim in view of Meyer lacks a history information extracting unit configured to extract, from boarding history information, target car history information on the target car, the boarding history information indicating either a past on-board passenger count or a past boarding-and-alighting passenger count between stops of a car in operation, wherein the congestion information generating unit generates the congestion information in accordance with the target car history information.
Yamamoto, from the same field of endeavor, teaches a history information extracting unit configured to extract, from boarding history information, target car history information on the target car, the boarding history information indicating either a past on-board passenger count or a past boarding-and-alighting passenger count between stops of a car in operation, wherein the congestion information generating unit generates the congestion information in accordance with the target car history information (Yamamoto - Here, FIG. 5 is a diagram showing an example of the situation history information created by the history information creation unit 2041 and stored in the history information storage unit 2062 in the first embodiment. As shown in FIG. 5, the history information creation unit 2041 includes a date, time, day of the week, train number, train name, vehicle number, seat type, number of seats, and in-vehicle (in-vehicle) at the time of arrival at a specific station of the train. Number of station users 105 existing in the passenger and home (outside the vehicle), number of passengers in the vehicle (inside the vehicle) and departure from the specific station of the train, and number of station users 105 existing in the home (outside the vehicle), vacant seats The status history information in which the number, the congestion rate, and the accident / disaster category are associated is created and stored in the history information storage unit 206).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the train congestion methodology/system of Kim by including the congestion notification techniques of Yamamoto because Yamamoto discloses “the prospective rider can predict the trend of the time zone of the boarding time without being caught only by the current congestion status, and can select the boarding vehicle more optimally (Yamamoto)”. Additionally, Kim further details that “The present disclosure relates to a system that provides real-time congestion and congestion prediction of public transportation such as subway and its platform, induces distribution of public transportation user density accordingly (Kim)” so it would be obvious to consider including the additional congestion notification techniques that Yamamoto discloses because it would optimize the system disclosed within Kim by having riders choose the most optimal train car.
Regarding claim 3, Kim in view of Meyer further in view of Yamamoto discloses the congestion information generating unit: obtains boarding-and-alighting passenger count information on a boarding-and-alighting passenger count for each of the boarding doors of the target car at stops from the departure station to the destination station (Kim - Here, the raw data collected by the sensor includes the location data of the user terminal, the number of users getting on or off when opening and closing public transportation doors, the number of users waiting on the platform, the number of users moving between compartments in public transportation, and public transportation), using the target car history information; and generates the congestion information in accordance with the boarding-and- alighting passenger count information for each of the boarding doors and with an on-board passenger count of passengers on board in each of the interior areas associated with one or the plurality of boarding doors of the target car (Kim - Here, the processor may generate the real-time public transport congestion result data by processing data on the number of users getting on or off when opening and closing the public transport door on the first platform, and based on the real-time public transport congestion result data and the first platform, the public By processing the data on the number of users waiting on the second platform where the traffic will next stop, the public transport congestion prediction data may be generated).
Regarding claim 4, Kim in view of Meyer further in view of Yamamoto discloses an information processing device (Kim ABS - A system for providing real-time public transport congestion comprises: a communication unit, a database, and a processor), comprising: a congestion information generating unit configured to generate congestion information indicating a degree of congestion of interior areas each associated with one or a plurality of boarding doors of the target car running from the departure station to the destination station (Kim - FIG. 2A is a graph showing real-time congestion result data for each public transport entrance, and FIG. 2B is a graph showing real-time congestion result data for each public transport compartment).
Yamamoto further teaches the history information extracting unit extracts the target car history information in accordance with an operation condition of the target car in operation (Yamamoto - Here, FIG. 5 is a diagram showing an example of the situation history information created by the history information creation unit 2041 and stored in the history information storage unit 2062 in the first embodiment. As shown in FIG. 5, the history information creation unit 2041 includes a date, time, day of the week, train number, train name, vehicle number, seat type, number of seats, and in-vehicle (in-vehicle) at the time of arrival at a specific station of the train. Number of station users 105 existing in the passenger and home (outside the vehicle), number of passengers in the vehicle (inside the vehicle) and departure from the specific station of the train, and number of station users 105 existing in the home (outside the vehicle), vacant seats The status history information in which the number, the congestion rate, and the accident / disaster category are associated is created and stored in the history information storage unit 206).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the train congestion methodology/system of Kim by including the congestion notification techniques of Yamamoto because Yamamoto discloses “the prospective rider can predict the trend of the time zone of the boarding time without being caught only by the current congestion status, and can select the boarding vehicle more optimally (Yamamoto)”. Additionally, Kim further details that “The present disclosure relates to a system that provides real-time congestion and congestion prediction of public transportation such as subway and its platform, induces distribution of public transportation user density accordingly (Kim)” so it would be obvious to consider including the additional congestion notification techniques that Yamamoto discloses because it would optimize the system disclosed within Kim by having riders choose the most optimal train car.
Regarding claim 5, Kim in view of Meyer further in view of Yamamoto discloses an information processing device (Kim ABS - A system for providing real-time public transport congestion comprises: a communication unit, a database, and a processor), comprising: a congestion information generating unit configured to generate congestion information indicating a degree of congestion of interior areas each associated with one or a plurality of boarding doors of the target car running from the departure station to the destination station (Kim - FIG. 2A is a graph showing real-time congestion result data for each public transport entrance, and FIG. 2B is a graph showing real-time congestion result data for each public transport compartment).
Yamamoto further teaches the operation condition includes at least any one of information on vacations of educational facilities, calendar information, operation status information, and weather information (Yamamoto - For example, in addition to the information shown in FIG. 5, information of “time zone” and “section indicating weekday or holiday” may be further included. The “time zone” may be divided into units of several hours in advance, and the history information creation unit 2041 may determine the “time zone” based on the time of the arrival / departure count information message. . As for “classification indicating weekday or holiday”, for example, the history information creation unit 2041 determines whether the date of the arrival / departure count information message is a weekday or a holiday from previously stored calendar information).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the train congestion methodology/system of Kim by including the congestion notification techniques of Yamamoto because Yamamoto discloses “the prospective rider can predict the trend of the time zone of the boarding time without being caught only by the current congestion status, and can select the boarding vehicle more optimally (Yamamoto)”. Additionally, Kim further details that “The present disclosure relates to a system that provides real-time congestion and congestion prediction of public transportation such as subway and its platform, induces distribution of public transportation user density accordingly (Kim)” so it would be obvious to consider including the additional congestion notification techniques that Yamamoto discloses because it would optimize the system disclosed within Kim by having riders choose the most optimal train car.
Regarding claim 6, Kim in view of Meyer further in view of Yamamoto discloses an information processing device (Kim ABS - A system for providing real-time public transport congestion comprises: a communication unit, a database, and a processor), comprising: a congestion information generating unit configured to generate congestion information indicating a degree of congestion of interior areas each associated with one or a plurality of boarding doors of the target car running from the departure station to the destination station (Kim - FIG. 2A is a graph showing real-time congestion result data for each public transport entrance, and FIG. 2B is a graph showing real-time congestion result data for each public transport compartment).
Yamamoto further teaches the boarding history information is data generated in accordance with either a past on-board passenger count or a past boarding-and-alighting passenger count in each of boarding areas of cars between the stops (Yamamoto - Here, FIG. 5 is a diagram showing an example of the situation history information created by the history information creation unit 2041 and stored in the history information storage unit 2062 in the first embodiment. As shown in FIG. 5, the history information creation unit 2041 includes a date, time, day of the week, train number, train name, vehicle number, seat type, number of seats, and in-vehicle (in-vehicle) at the time of arrival at a specific station of the train. Number of station users 105 existing in the passenger and home (outside the vehicle), number of passengers in the vehicle (inside the vehicle) and departure from the specific station of the train, and number of station users 105 existing in the home (outside the vehicle), vacant seats The status history information in which the number, the congestion rate, and the accident / disaster category are associated is created and stored in the history information storage unit 206).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the train congestion methodology/system of Kim by including the congestion notification techniques of Yamamoto because Yamamoto discloses “the prospective rider can predict the trend of the time zone of the boarding time without being caught only by the current congestion status, and can select the boarding vehicle more optimally (Yamamoto)”. Additionally, Kim further details that “The present disclosure relates to a system that provides real-time congestion and congestion prediction of public transportation such as subway and its platform, induces distribution of public transportation user density accordingly (Kim)” so it would be obvious to consider including the additional congestion notification techniques that Yamamoto discloses because it would optimize the system disclosed within Kim by having riders choose the most optimal train car.
Response to Arguments
Applicant's arguments filed 12/24/2025 have been fully considered but they are not persuasive and/or are moot in light of the new rejections addressed above.
Regarding the arguments related to the 35 USC § 101 rejections, as addressed above according to guidance for 35 USC § 101 rejections contained within MPEP 2106, the Examiner maintains that the claimed invention is an abstract idea, without significantly more, and not integrated into a practical application.
Applicant argues that the inclusion of the additional element display device, however, Examiner does not find this persuasive. As addressed above, the display device is interpreted as an additional element and not significantly more because it is simply the software and/or hardware components used to implement the abstract idea (evaluate how busy/congested a train or subway car is) on a general purpose computer (See MPEP 2106.05(f)).
Regarding the 35 USC § 103 rejections on the previous Office Action, Applicant amended the independent claims to further limit the claims with respect to the user inputs and displaying information. In light of this amendment, Examiner agrees that the original reference did specifically cite to this, however the amendment necessitated further search and consideration. As a result of this further search and consideration, the previously cited prior art was found to teach these limitations and now cited (Kim as discussed above). As such, Applicant’s arguments (with respect to the independent claims and their respective dependent claims) are unpersuasive.
Conclusion
THIS ACTION IS MADE FINAL. 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 Michael R Koester whose telephone number is (313)446-4837. The examiner can normally be reached Monday thru Friday 8:00AM-5:00 PM EST.
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/MICHAEL R KOESTER/Examiner, Art Unit 3624
/Jerry O'Connor/Supervisory Patent Examiner,Group Art Unit 3624