Information processing device, information processing method, and information processing program

Abstract

To provide an information processing device, information processing method, and information processing program. capable of providing a passenger with an appropriate advertisement.SOLUTION: An information processing device comprises a prediction unit, a selection unit, and a provision unit. The prediction unit predicts a place to get off where a passenger of a vehicle gets off a vehicle. The selection unit selects, as a provision advertisement, an advertisement corresponding to the place to get off where the passenger is predicted, by the prediction unit, to get off. The provision unit causes an advertisement notification device provided in the vehicle to provide the passenger with the provision advertisement selected by the selection unit.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] In recent years, with the rapid spread of the Internet, advertisement distribution via the Internet has become popular. As an example of such advertisement distribution, Patent Document 1 discloses a technology for providing advertisement content according to the attributes of passengers who board a taxi. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2020-144268 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, the above-mentioned conventional technology has room for improvement in terms of providing appropriate advertisements to passengers. For example, the above-mentioned conventional technology does not take into consideration the passenger's drop-off location, and when the advertisement provided to the passenger is an advertisement for a store, the effect of the advertisement desired by the advertiser may not be obtained. This is not limited to taxis, but also applies to other vehicles such as buses and trains.

[0005] The present application has been made in consideration of the above, and has an object to provide an information processing device, an information processing method, and an information processing program capable of providing appropriate advertisements to passengers. [Means for solving the problem]

[0006] The information processing device disclosed herein includes a prediction unit, a selection unit, and a provision unit. The prediction unit predicts an alighting location where a passenger of the vehicle will alight from the vehicle. The selection unit selects an advertisement corresponding to the alighting location predicted by the prediction unit where the passenger will alight from the vehicle as the advertisement to be provided. The provision unit causes an advertisement presentation device provided in the vehicle to provide the advertisement selected by the selection unit to the passenger before the passenger predicted by the prediction unit to alight at the alighting location alights from the vehicle. Effect of the Invention

[0007] According to one aspect of the embodiment, it is possible to provide passengers with appropriate advertisements. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of the configuration of an information processing system according to the embodiment. [Diagram 3] FIG. 3 is a diagram illustrating an example of the configuration of the information processing device according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of a passenger information table stored in the passenger information storage unit of the information processing device according to the embodiment. [Diagram 5] FIG. 5 is a diagram illustrating an example of an advertisement information table stored in the advertisement information storage unit of the information processing device according to the embodiment. [Figure 6] FIG. 6 is a flowchart showing an example of information processing by the processing unit of the information processing device according to the embodiment. [Figure 7] FIG. 7 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, the information processing device, the information processing method, and the information processing program according to the present application (hereinafter, referred to as "embodiments") will be described in detail with reference to the drawings. Note that the information processing device, the information processing method, and the information processing program according to the present application are not limited to these embodiments. In addition, each embodiment can be appropriately combined as long as the processing contents are not contradictory. In addition, the same parts in each of the following embodiments are given the same reference numerals, and duplicated explanations will be omitted.

[0010] [1. An example of information processing] First, an example of information processing according to the embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of information processing according to the embodiment, which is executed by an information processing device 1.

[0011] 1, an information processing device 1 acquires passenger identification information, which is information for identifying each passenger P, from a plurality of on-board devices 3 mounted on a vehicle 2 (step S1). The vehicle 2 is, for example, a public transportation vehicle such as a bus, a train, or a taxi. The plurality of on-board devices 3 are, for example, a wireless router, a non-contact IC card reader, an image recognition device, or the like.

[0012] The contactless IC card reader communicates with, for example, a contactless IC card such as FeliCa (registered trademark), a device equipped with RFID (Radio Frequency Identification), or NFC (Near Field Communication), etc. For example, the contactless IC card reader communicates with a contactless IC card that a passenger P brings close to board the vehicle 2 or a terminal device of the passenger P. The terminal device of the passenger P is, for example, a smartphone, a tablet PC (Personal Computer), etc.

[0013] The non-contact IC card reader transmits information indicating the identifier of the IC card to the information processing device 1. The information processing device 1 acquires the information indicating the identifier of the IC card transmitted from the non-contact IC card reader as passenger identification information.

[0014] The wireless router communicates with passenger P's terminal device via wireless LAN. Passenger P's terminal device can communicate with an information providing device that provides a website via the wireless router, and passenger P can display the website on passenger P's terminal device. The wireless router transmits information on the MAC (Media Access Control) address of passenger P's terminal device to the information processing device 1. The information processing device 1 acquires the information on the MAC address of passenger P's terminal device transmitted from the wireless router as passenger identification information.

[0015] The image recognition device recognizes a facial image of the passenger P, identifies the passenger P, and transmits identification information of the identified passenger P (e.g., a passenger ID that is an identifier of the passenger P) to the information processing device 1. The information processing device 1 acquires the identification information of the passenger P transmitted from the image recognition device as passenger identification information.

[0016] Next, the information processing device 1 acquires information on each passenger P based on the passenger identification information acquired in step S1 (step S2). For example, when the passenger identification information acquired in step S1 is information indicating an IC card identifier, the information processing device 1 determines the passenger ID of passenger P corresponding to the information indicating the IC card identifier, and acquires the information on passenger P linked to the determined passenger ID.

[0017] In addition, if the passenger identification information acquired in step S1 is the MAC address of passenger P's terminal device, the information processing device 1 determines the passenger ID of passenger P corresponding to the MAC address of passenger P's terminal device, and acquires information of passenger P linked to the determined passenger ID.

[0018] In addition, if the passenger identification information acquired in step S1 is identification information of passenger P, the information processing device 1 determines the passenger ID of passenger P corresponding to the identification information of passenger P, and acquires information of passenger P linked to the determined passenger ID.

[0019] The information of passenger P linked to the passenger ID is, for example, attribute information of passenger P, information on the behavioral history of passenger P, information on the schedule of passenger P, etc. The attribute information of passenger P is information indicating the attributes of passenger P (for example, age, gender, region, interests, consumption behavior, etc.).

[0020] The information on the behavioral history of passenger P is information on past behavior performed by passenger P, and examples of the past behavior performed by passenger P include the passenger P's past boarding position in vehicle 2, the passenger P's past boarding and disembarking of vehicle 2, the passenger P's past movements, the passenger P's past use of stores, the passenger P's past browsing of websites, the passenger P's past web searches, etc. The boarding position is detected by, for example, multiple NFC communication devices and image recognition devices mounted on the vehicle 2, but is not limited to such examples.

[0021] Next, the information processing device 1 predicts the disembarking locations where each passenger P of the vehicle 2 gets off from the vehicle 2 based on the information of the passenger P acquired in step S2 (step S3). For example, the information processing device 1 predicts the disembarking locations of the passengers P based on the information of the behavior history of the passengers P acquired in step S2.

[0022] For example, the information processing device 1 predicts passenger P's disembarking location based on one or more of the following information: information on passenger P's past boarding and disembarking of vehicle 2, information on passenger P's past boarding positions in vehicle 2, information on passenger P's past travel routes, information on passenger P's past store use, information on passenger P's past site browsing, and information on passenger P's past web searches.

[0023] The information processing device 1 has, for example, a prediction model that inputs information about the passenger P as a feature amount and outputs information indicating the disembarking location, and can predict the disembarking location of the passenger P using such a prediction model.

[0024] In addition, the information processing device 1 can predict the disembarking location of passenger P as the most common past disembarking location of passenger P among the past boarding locations of passenger P into vehicle 2 and the past boarding locations of passenger P in the vehicle that match the combination of the current boarding location of passenger P into vehicle 2 and the current boarding position in the vehicle.

[0025] For example, assume that the location where passenger P boarded vehicle 2 boarded vehicle 2 is location X1, and the boarding position of passenger P within vehicle 2 is location Y1. In this case, the information processing device 1 can predict the disembarking location of passenger P based on the location where passenger P most frequently disembarked when the boarding location of passenger P in the past boarded vehicle 2 was location X1 and the boarding position was Y1.

[0026] The boarding position is, for example, a seat unit area in the seating area, and a region divided into multiple areas in the non-seat area (aisle area), but is not limited to such an example. For example, the boarding position may be multiple areas divided into two or more areas in the vehicle 2, such as a front area in the vehicle 2, a central area in the vehicle 2, a rear area in the vehicle 2, or an area of ​​a group of seats or an area other than the group of seats (for example, an aisle area). The information processing device 1 can also predict the disembarking location of the passenger P without using the boarding position.

[0027] Furthermore, the information processing device 1 can also predict the disembarking location of the passenger P, for example, based on information related to the schedule of the passenger P. The information related to the schedule of the passenger P includes, for example, information indicating the location of the store reserved by the passenger P and the reservation date and time, information indicating the location of the facility reserved by the passenger P and the reservation date and time, information indicating the location of the event reserved by the passenger P and the event date and time, etc.

[0028] The information processing device 1 can predict, for example, as the drop-off location of the passenger P, the closest drop-off location to the location of a store, facility, or event that will occur on the reserved date and time or the date and time of the event within a predetermined period.

[0029] Next, before the passenger P predicted to get off at the alighting location in step S3 gets off the vehicle 2, the information processing device 1 selects an advertisement corresponding to the alighting location where the passenger P is predicted to get off in step S3 as the presented advertisement (step S4).

[0030] For example, the information processing device 1 selects, as the advertisement to be presented, an advertisement according to the information of the passenger P predicted in step S3 as a passenger who will get off the vehicle 2 at the alighting location and the alighting location of the passenger P predicted in step S3.

[0031] For example, the information processing device 1 selects as the advertisements to be presented one or more advertisements corresponding to the information of passenger P who will be a disembarking passenger predicted in step S3 from among multiple advertisements related to stores, facilities, or events within a predetermined range from the disembarking location of passenger P predicted in step S3.

[0032] The one or more advertisements based on passenger P's information may be, for example, advertisements related to stores, facilities, or events that passenger P has used in the past, advertisements that are presumed to be of interest or concern to passenger P, and advertisements related to stores, facilities, or events that passenger P has not used in the past, but are not limited to such examples.

[0033] In addition, when the information processing device 1 predicts in step S3 that there are multiple passengers P who will have the same disembarking location, it can also select as the provided advertisement an advertisement corresponding to the information of these multiple passengers P and the disembarking location predicted to be the disembarking location in step S3.

[0034] Advertisements based on the information and disembarking location of multiple passengers P include, for example, advertisements for stores, facilities, or events within a predetermined range from the disembarking location of passenger P predicted in step S3, advertisements for stores, facilities, or events that multiple passengers P have commonly used in the past, advertisements that are estimated to be of common interest or concern to multiple passengers P, and advertisements for stores, facilities, or events that multiple passengers P have not commonly used in the past, but are not limited to such examples.

[0035] In addition, when multiple passengers P who are expected to get off at the same stop have a specific relationship with each other, the advertisement is for a store, facility, or event that some of the passengers P have used frequently (e.g., multiple times) in the past, but the remaining passengers P have not used in the past.

[0036] The specific relationship may be, for example, a relationship of having traveled the same route for a predetermined period of time from when the passenger P got into the vehicle 2, a family relationship, an employee of the same company, etc., but is not limited to such examples. The information processing device 1 can acquire information on the travel route of the passenger P for a predetermined period of time from when the passenger P got into the vehicle 2 from the passenger P's terminal device.

[0037] The information processing device 1 can also predict the probability of conversion due to multiple advertisements and select an advertisement whose predicted probability of conversion satisfies a predetermined condition as the advertisement to be presented. Conversion is an index related to the achievement of a goal (e.g., a conversion goal), and is, for example, the use of a store (including the purchase of a product or service), the use of a facility, or participation in an event.

[0038] For example, the information processing device 1 predicts the probability of conversion due to an advertisement according to the above-mentioned information of the passenger P and the drop-off location, and selects an advertisement whose predicted conversion probability satisfies a predetermined condition as an advertisement to be presented. The information processing device 1 predicts the probability of conversion due to an advertisement using a prediction model generated by machine learning. The feature quantities input to the prediction model are the information of the passenger P and the information on the location of the drop-off location.

[0039] The information processing device 1 can also select an advertisement including text and images generated by a generative AI (Artificial Intelligence) as the presented advertisement. For example, the information processing device 1 inputs the scenery and sounds inside and outside the vehicle seen by the passenger P in the vehicle 2 together with an instruction to create an advertisement to the generative AI, and selects an advertisement output from the generative AI as the presented advertisement.

[0040] In addition, the information processing device 1 can input to the generative AI the scenery and sounds inside and outside the vehicle seen by the passenger P riding in the vehicle 2, and information on stores, facilities, and events within a predetermined range from the location of the disembarkation location predicted in step S3, along with instructions for creating an advertisement, and select the advertisement output from the generative AI as the advertisement to be presented.

[0041] In addition, the information processing device 1 can select as the provided advertisement an advertisement related to the information input by the passenger P to the generative AI and which is about a store, facility, or event within a predetermined range of the disembarkation location predicted in step S3.

[0042] For example, the information processing device 1 selects as the advertisement to be presented an advertisement from among multiple advertisements, the conversion rate predicted by a prediction model having features that are the information input by passenger P to the generative AI and the information on the disembarkation location predicted in step S3, and that satisfies predetermined conditions.

[0043] Furthermore, the information processing device 1 can also select an advertisement to be provided based on the time period, day of the week, weather, the degree of congestion inside the vehicle 2, the attribute ratio (e.g., male / female ratio) of the passengers P inside the vehicle 2, and the travel speed of the vehicle 2. For example, the information processing device 1 can select an advertisement according to the above-mentioned information of the passenger P, the disembarking location, the time period, day of the week, weather, and the travel speed of the vehicle 2 as the advertisement to be provided.

[0044] In addition, the information processing device 1 can predict the probability of conversion due to an advertisement based on the above-mentioned information of the passenger P, the disembarking location, the time of day, the day of the week, the weather, and the travel speed of the vehicle 2, and select as the advertisement to be presented an advertisement whose predicted conversion probability satisfies predetermined conditions.

[0045] Next, the information processing device 1 causes the advertisement presentation device 4 provided in the vehicle 2 to present the provided advertisement selected in step S4 to the passenger P, who is predicted in step S3 to get off at the disembarking location, before the passenger P gets off the vehicle 2 (step S5). The advertisement presentation device 4 is a device including at least one of a display unit that displays the provided advertisement and an audio output unit that outputs the provided advertisement by audio.

[0046] A plurality of advertising notification devices 4 are arranged in the vehicle 2, and for example, each advertising notification device 4 is arranged at a position corresponding to each seat (for example, in front of or to the side of the seat, such as the back of the front seat), in each area of ​​the side wall of the vehicle 2, or in a position hung at a distance from the ceiling, but is not limited to such an example.

[0047] The information processing device 1, for example, causes the advertisement selected in step S4 to be provided from an advertisement presentation device 4 located within a predetermined range from the passenger P predicted to get off in step S3 among the multiple advertisement presentation devices 4. For example, the information processing device 1 causes the advertisement selected in step S4 to be provided from the advertisement presentation device 4 located in front of the vehicle 2 from the position of the passenger P.

[0048] Furthermore, the information processing device 1 provides the provided advertisement to the passengers P via the advertisement presentation device 4 at a timing based on the distance to the alighting location of the vehicle 2 and the number of passengers P predicted to get off at the alighting location. For example, the information processing device 1 provides the provided advertisement to the passengers P via the advertisement presentation device 4 from a position farther away from the alighting location of the vehicle 2 as the number of passengers P predicted to get off at the alighting location increases.

[0049] In addition, the information processing device 1 can also determine the timing to provide the advertisement based on the time of day, day of the week, weather, degree of congestion inside the vehicle 2, attribute ratios of passengers P inside the vehicle 2 (e.g., male / female ratio), and the travel speed of the vehicle 2.

[0050] For example, the information processing device 1 can input the number of passengers P predicted to get off at the drop-off location, the time of day, day of the week, weather, the degree of congestion in the vehicle 2, the attribute ratio of passengers P in the vehicle 2 (e.g., male / female ratio), and the travel speed of the vehicle 2 as features, and determine the timing to provide the provided advertisement using a model that outputs the distance from the vehicle 2 to the drop-off location that is the timing to provide the provided advertisement.

[0051] In this way, the information processing device 1 predicts the alighting location where the passenger P of the vehicle 2 will alight from the vehicle 2, selects an advertisement corresponding to the predicted alighting location as the advertisement to be provided, and causes the advertisement to be provided to the passenger P from the advertisement presentation device 4 provided in the vehicle 2 before the passenger P predicted to alight at the alighting location alights from the vehicle 2. In this way, the information processing device 1 can provide an appropriate advertisement to the passenger P.

[0052] In the above example, the information processing device 1 is disposed outside the vehicle 2. However, a part or the whole of the information processing device 1 may be disposed inside the vehicle 2.

[0053] The configuration of an information processing system including the information processing device 1 that performs such processing, the multiple mounted devices 3, and the multiple advertisement presentation devices 4 will be described in detail below.

[0054] 2. Configuration of the Information Processing System Fig. 2 is a diagram showing an example of the configuration of an information processing system according to an embodiment. As shown in Fig. 2, the information processing system 100 according to the embodiment includes an information processing device 1, a plurality of mounted devices 3, and a plurality of advertisement presentation devices 4.

[0055] The on-board device 3 may be, for example, a wireless router, a non-contact IC card reader, an image recognition device, etc., but it is not limited to the examples mentioned above as long as it is a device that can provide passenger identification information, which is information for identifying passenger P, to the information processing device 1.

[0056] The advertisement presentation device 4 includes at least one of a display unit that displays the provided advertisement provided by the information processing device 1 and an audio output unit that outputs the provided advertisement by audio. For example, the advertisement presentation device 4 is a digital signage having an audio output function, but is not limited to such an example.

[0057] A plurality of advertising notification devices 4 are arranged in the vehicle 2, and for example, each advertising notification device 4 is arranged at a position corresponding to each seat (for example, in front of or to the side of the seat, such as the back of the front seat), in each area of ​​the side wall of the vehicle 2, or in a position hung at a distance from the ceiling, but is not limited to such an example.

[0058] The information processing device 1, the mounted device 3, and the advertisement presentation device 4 are connected to each other so as to be able to communicate with each other by wire or wirelessly via a network N. Note that the information processing system 100 shown in FIG. 2 may include a plurality of information processing devices 1 and the like.

[0059] The network N includes, for example, a Wide Area Network (WAN) such as the Internet and mobile communication networks such as Long Term Evolution (LTE), 4th Generation (4G), and 5th Generation (5G: fifth generation mobile communication system).

[0060] The mounted device 3 and the advertisement presentation device 4 can be connected to the network N via short-range wireless communication such as a mobile communication network, Bluetooth (registered trademark), or a wireless LAN (Local Area Network), and can communicate with the information processing device 1. Note that the advertisement presentation device 4 may be a device that communicates with the information processing device 1 via the mounted device 3, which is a wireless router.

[0061] 3. Configuration of information processing device 1 3 is a diagram showing an example of the configuration of the information processing device 1 according to the embodiment. As shown in FIG. 3, the information processing device 1 includes a communication unit 10, a storage unit 11, and a processing unit 12.

[0062] [3.1. Communication unit 10] The communication unit 10 is realized by, for example, a communication module or a NIC (Network Interface Card). The communication unit 10 is connected to a network N by wire or wirelessly, and transmits and receives information to and from various other devices. For example, the communication unit 10 transmits and receives information to and from the mounted device 3 and the advertisement notification device 4 via the network N.

[0063] [3.2. Storage section 11] The storage unit 11 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 11 has a passenger information storage unit 20 and an advertisement information storage unit 21.

[0064] [3.2.1. Passenger information storage unit 20] The passenger information storage unit 20 stores various information related to the passenger P. Fig. 4 is a diagram showing an example of a passenger information table stored in the passenger information storage unit 20 of the information processing device 1 according to the embodiment.

[0065] 4, the passenger information table stored in the passenger information storage unit 20 includes information items such as "Passenger ID (Identifier)," "Attribute Information," "History Information," and "Schedule Information." The "Passenger ID" is an identifier that identifies a passenger P, and is information assigned to each passenger P.

[0066] The "attribute information" is attribute information indicating the attributes of the passenger P associated with the "passenger ID." The attributes of the passenger P are, for example, demographic attributes, psychographic attributes, etc. The demographic attributes are demographic attributes, and include, for example, multiple attribute items such as age, sex, occupation, place of residence, annual income, and family structure.

[0067] The psychographic attributes are psychological attributes, and include, for example, a plurality of attribute items related to lifestyle, values, interests, etc. For example, each of the plurality of attribute items in the psychographic attributes is an object of interest to the passenger P, such as a car, clothes, travel, games, camping, motorcycle, train, home appliance, or computer.

[0068] The "history information" includes information on the behavior history of the passenger P associated with the "passenger ID." The behavior history of the passenger P includes, for example, information on the behavior history of the passenger P in the real space and information on the behavior history of the passenger P in online services.

[0069] The information on the behavior history of the passenger P in the real space is, for example, information on past behaviors performed by the passenger P in the real space. The past behaviors performed by the passenger P in the real space are, for example, information indicating the past boarding position of the passenger P in the vehicle 2, the past boarding and disembarking of the passenger P in the vehicle 2, the past movements of the passenger P, the past use of stores by the passenger P, and the like, but are not limited to such examples.

[0070] The information on the passenger P's behavioral history in the online service includes, for example, search history information, browsing history information, delivery history information, and transaction history information in the online service of the passenger P. The search history information of the passenger P includes, for example, information on the search history by the passenger P in the web search service.

[0071] The browsing history information of the passenger P includes, for example, information on the browsing history of content by the passenger P in the online service. The distribution history information includes information on the distribution history of the distribution content distributed to the terminal device of the passenger P. The transaction history information includes information on the transaction history of goods by the passenger P in the online service.

[0072] "Schedule information" is information about passenger P's schedule associated with "passenger ID," and may include, for example, information indicating the location of the store reserved by passenger P and the date and time of the reservation, information indicating the location of the facility reserved by passenger P and the date and time of the reservation, information indicating the location of the event reserved by passenger P and the date and time of the event, but is not limited to such examples.

[0073] 3.2.2. Advertising information storage unit 21 The advertisement information storage unit 21 stores various pieces of information related to advertisements. Fig. 5 is a diagram showing an example of an advertisement information table stored in the advertisement information storage unit 21 of the information processing device 1 according to the embodiment.

[0074] In the example shown in FIG. 5, the advertisement information table stored in the advertisement information storage unit 21 includes information of items such as "advertising ID" and "advertising". The "advertising ID" is an identifier that identifies an advertisement, and is information attached to the advertisement. The "advertising" is an advertisement associated with the "advertising ID", and is, for example, a video advertisement or an animation advertisement, but is not limited to such examples.

[0075] [3.3. Processing section 12] The processing unit 12 is a controller, and is realized, for example, by a CPU (Central Processing Unit) or an MPU (Micro Processing Unit) executing various programs stored in a storage device inside the information processing device 1 using a RAM as a working area.

[0076] The processing unit 12 may be partially or entirely realized by an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

[0077] 3, the processing unit 12 has an acquisition unit 30, a determination unit 31, a prediction unit 32, a selection unit 33, and a provision unit 34, and realizes or executes the functions and actions of information processing described below. Note that the internal configuration of the processing unit 12 is not limited to the configuration shown in FIG. 3, and may be other configurations as long as they perform the information processing described below.

[0078] [3.3.1. Acquisition part 30] The acquisition unit 30 acquires various pieces of information from an external information processing device or a terminal device of the passenger P via the communication unit 10, and stores the acquired information in the storage unit 11.

[0079] For example, the acquisition unit 30 acquires passenger information, which is information about passenger P, from an external information processing device or a terminal device of passenger P, etc., via the communication unit 10, and adds the acquired passenger information to a passenger information table in the passenger information storage unit 20. In addition, the acquisition unit 30 acquires advertising information, which is information about advertisements, from an external information processing device, etc., via the communication unit 10, and adds the acquired advertising information to the advertising information table in the advertising information storage unit 21.

[0080] The acquisition unit 30 also acquires passenger identification information, which is information for identifying each passenger P, from the multiple onboard devices 3 mounted on the vehicle 2. The passenger identification information is, for example, information indicating an IC card identifier, information on the MAC address of the terminal device of the passenger P, or identification information of the passenger P, but is not limited to these examples.

[0081] The acquisition unit 30 also acquires various information from the storage unit 11. For example, the acquisition unit 30 acquires passenger information, which is information about passenger P, from the passenger information storage unit 20 or the like. The passenger information acquired by the acquisition unit 30 includes, for example, a part or all of at least one of the above-mentioned attribute information, history information, and schedule information. The acquisition unit 30 also acquires advertising information, which is information about advertisements, from the advertising information storage unit 21 or the like.

[0082] [3.3.2. Judgment unit 31] The determination unit 31 determines the passenger P aboard the vehicle 2 based on the passenger identification information acquired by the acquisition unit 30. For example, when the passenger identification information acquired by the acquisition unit 30 is information indicating an IC card identifier, the determination unit 31 determines the passenger ID of the passenger P corresponding to the information indicating the IC card identifier, thereby determining the passenger P aboard the vehicle 2.

[0083] In addition, when the passenger identification information acquired by the acquisition unit 30 is the MAC address of passenger P's terminal device, the determination unit 31 determines passenger P who is riding in vehicle 2 by determining the passenger ID of passenger P that corresponds to the MAC address of passenger P's terminal device.

[0084] In addition, when the passenger identification information acquired by the acquisition unit 30 is identification information of passenger P, the determination unit 31 determines the passenger ID of passenger P corresponding to the identification information of passenger P, thereby determining passenger P who is riding in vehicle 2.

[0085] In addition, when the acquisition unit 30 acquires information about the passenger P from the terminal device of the passenger P, the determination unit 31 can also determine the passenger P who is riding in the vehicle 2 based on the information about the passenger P.

[0086] [3.3.3. Prediction Unit 32] The prediction unit 32 predicts an alighting location where a passenger P of the vehicle 2 alights from the vehicle 2.

[0087] For example, the prediction unit 32 predicts an alighting location where the passenger P aboard the vehicle 2 alights from the vehicle 2 based on passenger information that is information about the passenger P acquired by the acquisition unit 30.

[0088] For example, the prediction unit 32 predicts the disembarking location of passenger P based on one or more of the following information: information on passenger P's past boarding and disembarking of vehicle 2, information on passenger P's past boarding positions in vehicle 2, information on passenger P's past travel routes, information on passenger P's past store use, information on passenger P's past site browsing, and information on passenger P's past web searches.

[0089] The prediction unit 32 has a prediction model that inputs, for example, information about the passenger P as a feature and outputs information indicating the disembarking location, and can predict the disembarking location of the passenger P using the prediction model. The prediction model is, for example, a linear regression model, a gradient boosting decision tree (GBDT), or recurrent neural networks (RNNs) such as a long short-term memory (LSTM) or a gated recurrent unit (GRU), but is not limited to these examples.

[0090] In addition, the prediction unit 32 can predict as the disembarking location of passenger P the most common past disembarking location of passenger P among the past boarding locations of passenger P into vehicle 2 and the past boarding locations of passenger P in the vehicle that match the combination of the current boarding location of passenger P into vehicle 2 and the current boarding position in the vehicle by passenger P.

[0091] For example, assume that the location where passenger P boarded vehicle 2 boarded vehicle 2 is location X1, and the boarding position of passenger P within vehicle 2 is location Y1. In this case, the prediction unit 32 can predict the disembarking location of passenger P as the location where passenger P most frequently disembarked when the boarding location of passenger P in the past boarded vehicle 2 was location X1 and the boarding position was Y1.

[0092] The boarding position is, for example, a seat unit area in the seat area, and a region divided into multiple areas in the non-seat area (aisle area), but is not limited to such an example. For example, the boarding position may be, for example, a multiple area divided into two or more areas in the vehicle 2, such as a front area in the vehicle 2, a central area in the vehicle 2, a rear area in the vehicle 2, or the like, or may be an area of ​​a group of seats, an area other than the group of seats (for example, an aisle area), or the like. The prediction unit 32 can also predict the disembarking location of the passenger P without using the boarding position.

[0093] The prediction unit 32 can also predict the drop-off location of the passenger P based on, for example, information related to the schedule of the passenger P. For example, the prediction unit 32 can predict, as the drop-off location of the passenger P, the drop-off location that is closest to the location of a store, facility, or event that will be booked on a reservation date and time or will be held on a date and time within a predetermined period.

[0094] The prediction unit 32 also predicts the probability of conversion due to the advertisement. Conversion due to the advertisement is an index related to reaching a goal (e.g., a conversion goal), and examples thereof include, but are not limited to, using a store (including purchasing a product or service), using a facility, and participating in an event.

[0095] For example, the prediction unit 32 predicts the probability of conversion due to the advertisement according to the above-mentioned information of the passenger P and the drop-off location, and selects an advertisement whose predicted conversion probability satisfies a predetermined condition as the presented advertisement. The prediction unit 32 predicts the probability of conversion due to the advertisement using a prediction model generated by machine learning. The feature amount input to the prediction model is the information of the passenger P and the information on the location of the drop-off location, but is not limited to this example, and may include information indicating the travel route of the vehicle 2, information indicating the location of the vehicle 2, etc.

[0096] [3.3.4. Selection unit 33] The selection unit 33 selects an advertisement corresponding to the alighting place predicted by the prediction unit 32 as the advertisement to be presented before the passenger P predicted by the prediction unit 32 to alight at the alighting place alights from the vehicle 2.

[0097] For example, before a passenger P predicted by the prediction unit 32 to get off at the alighting location gets off from the vehicle 2, the selection unit 33 selects an advertisement to be presented that corresponds to the information of the passenger P predicted by the prediction unit 32 to get off at the alighting location and the alighting location predicted by the prediction unit 32.

[0098] The information on passenger P used by the selection unit 33 includes one or more of information on the attributes of passenger P, information on the behavioral history of passenger P, and information on the schedule of passenger P. The information on the attributes of passenger P is, for example, passenger information acquired by the acquisition unit 30 from the passenger information storage unit 20, such as information on passenger P's age, gender, region, interests, consumption behavior, etc.

[0099] In addition, information on passenger P's behavioral history is information on past behavior performed by passenger P, and for example, past behavior performed by passenger P includes passenger P's past boarding position in vehicle 2, passenger P's past boarding and disembarking of vehicle 2, passenger P's past movements, passenger P's past use of stores, passenger P's past site browsing, passenger P's past web searches, etc.

[0100] The selection unit 33 selects, for example, from among a plurality of advertisements relating to stores, facilities, or events within a predetermined range from the disembarking location of the passenger P predicted by the prediction unit 32, one or more advertisements corresponding to information of the passenger P who is predicted by the prediction unit 32 to disembark at the disembarking location as advertisements to be provided.

[0101] The one or more advertisements based on passenger P's information may be, for example, advertisements related to stores, facilities, or events that passenger P has used in the past, advertisements that are presumed to be of interest or concern to passenger P, and advertisements related to stores, facilities, or events that passenger P has not used in the past, but are not limited to such examples.

[0102] In addition, when the prediction unit 32 predicts that there are multiple passengers P who will get off at the same location, the selection unit 33 can select as the advertisement to be provided an advertisement that corresponds to the information of these multiple passengers P and the alighting location predicted by the prediction unit 32.

[0103] Advertisements based on the information and disembarking location of multiple passengers P include, for example, advertisements related to stores, facilities, or events within a predetermined range from the disembarking location of passenger P predicted by the prediction unit 32, advertisements related to stores, facilities, or events that multiple passengers P have commonly used in the past, advertisements in which multiple passengers P are estimated to have a common interest or concern, and advertisements related to stores, facilities, or events that multiple passengers P have not commonly used in the past, but are not limited to such examples.

[0104] In addition, when multiple passengers P who are expected to get off at the same stop have a specific relationship with each other, the advertisement is for a store, facility, or event that some of the passengers P have used frequently (e.g., multiple times) in the past, but the remaining passengers P have not used in the past.

[0105] The specific relationship may be, for example, a relationship of having traveled the same route for a predetermined period from the time of getting on the vehicle 2, a family relationship, an employee of the same company, etc., but is not limited to such examples. The information processing device 1 can acquire information on the travel route of the passenger P for a predetermined period from the time of getting on the vehicle 2 from the terminal device of the passenger P.

[0106] Furthermore, the selection unit 33 can select, as the provided advertisement, an advertisement for which the probability of conversion predicted by the prediction unit 32 satisfies a predetermined condition.

[0107] The selection unit 33 can also select an advertisement including text and images generated by the generative AI as the presented advertisement. For example, the selection unit 33 inputs the scenery and sounds inside and outside the vehicle seen by the passenger P in the vehicle 2 together with an instruction to create an advertisement to the generative AI, and selects an advertisement output from the generative AI as the presented advertisement.

[0108] The generative AI includes, for example, a language model such as a transformer that is trained to estimate and output the next token from an input token sequence. Such a language model is in the information processing device 1 and is created independently by the operator of the information processing device 1. It is preferable that the input information is trained so as not to be used as a new answer, thereby concealing the input information, such as personal information.

[0109] The selection unit 33 can also input to the generation AI the scenery and sounds inside and outside the vehicle seen by the passenger P riding in the vehicle 2, and information on stores, facilities, and events within a predetermined range from the location of the disembarkation location predicted by the prediction unit 32, along with instructions for creating an advertisement, and select an advertisement output from the generation AI as the advertisement to be presented.

[0110] In addition, the selection unit 33 can select as the provided advertisement an advertisement related to the information input by the passenger P to the generation system AI and which is about a store, facility, or event within a predetermined range of the disembarking location predicted by the prediction unit 32.

[0111] For example, the selection unit 33 selects, from among a plurality of advertisements, an advertisement whose conversion rate predicted by a prediction model having features including the information input by the passenger P to the generation system AI and the information on the disembarking location predicted by the prediction unit 32 satisfies a predetermined condition as the advertisement to be presented.

[0112] The selection unit 33 can also select an advertisement to be provided based on the time period, day of the week, weather, the degree of congestion inside the vehicle 2, the attribute ratio of the passengers P inside the vehicle 2 (e.g., the ratio of males and females), and the travel speed of the vehicle 2. For example, the selection unit 33 can select an advertisement according to the above-mentioned information of the passenger P, the disembarking location, the time period, weather, day of the week, and the travel speed of the vehicle 2 as the advertisement to be provided.

[0113] The selection unit 33 can also predict the probability of conversion due to an advertisement based on the above-mentioned information of the passenger P, the disembarking location, the time of day, the day of the week, the weather, and the travel speed of the vehicle 2, and select as the advertisement to be presented an advertisement whose predicted conversion probability satisfies predetermined conditions.

[0114] [3.3.5.Providing Department 34] The providing unit 34 causes the advertisement selected by the selecting unit 33 to be provided to the passenger P from the advertisement notification device 4 provided in the vehicle 2 before the passenger P predicted by the predicting unit 32 to get off at the get-off location gets off the vehicle 2.

[0115] For example, before the passenger P predicted by the prediction unit 32 to get off at the alighting location gets off the vehicle 2, the provision unit 34 causes the advertisement to be provided, selected by the selection unit 33, to be provided from among the multiple advertisement presentation devices 4, an advertisement presentation device 4 that is within a predetermined range from the passenger P predicted by the prediction unit 32 to get off. For example, the provision unit 34 causes the advertisement to be provided, selected by the selection unit 33, to be provided from the advertisement presentation device 4 that is located in front of the vehicle 2 from the position of the passenger P.

[0116] Furthermore, the providing unit 34 provides the provided advertisement to the passengers P via the advertisement presentation device 4 at a timing based on the distance to the alighting location of the vehicle 2 and the number of passengers P predicted to get off at the alighting location. For example, the providing unit 34 provides the provided advertisement to the passengers P via the advertisement presentation device 4 from a position farther away from the alighting location of the vehicle 2 as the number of passengers P predicted to get off at the alighting location increases.

[0117] The providing unit 34 can also determine the timing to provide the provided advertisement based on the time period, the day of the week, the weather, the degree of congestion inside the vehicle 2, the attribute ratio (e.g., male / female ratio) of the passengers P inside the vehicle 2, and the moving speed of the vehicle 2. Such timing is the timing before the passengers P predicted by the prediction unit 32 to get off at the get-off location get off the vehicle 2, and for example, if the vehicle 2 is a bus, it is the timing from passing the previous stop to arriving at the next stop, but is not limited to such an example.

[0118] For example, the providing unit 34 can input the number of passengers P predicted to get off at the drop-off location, the time period, the day of the week, the weather, the degree of congestion in the vehicle 2, the attribute ratio of the passengers P in the vehicle 2 (e.g., the ratio of men to women), and the moving speed of the vehicle 2 as feature quantities, and can determine the timing to provide the provided advertisement using a model that outputs the distance to the drop-off location of the vehicle 2 that is the timing to provide the provided advertisement. Note that the providing unit 34 can also input the type and content of the advertisement to the model to determine the timing to provide the provided advertisement.

[0119] 4. Processing Procedure Next, a procedure of information processing by the processing unit 12 of the information processing device 1 according to the embodiment will be described. Fig. 6 is a flowchart showing an example of information processing by the processing unit 12 of the information processing device 1 according to the embodiment.

[0120] 6, the processing unit 12 of the information processing device 1 determines whether or not the processing timing has arrived (step S20). The processing timing is, for example, a timing that arrives at a predetermined cycle, or a timing when a passenger P gets on the vehicle 2, but is not limited to such examples.

[0121] When the processing unit 12 determines that the processing timing has come (step S20: Yes), the processing unit 12 acquires passenger identification information from the on-board device 3 (step S21). The processing unit 12 acquires information on each passenger P based on the passenger identification information acquired in step S21 (step S22).

[0122] The processing unit 12 predicts a drop-off location where each passenger P of the vehicle 2 gets off the vehicle 2 based on the information of each passenger P acquired in step S22 (step S23). Then, the processing unit 12 selects an advertisement to be provided based on the prediction result in step S23 (step S24), and provides the advertisement selected in step S24 to the passenger P (step S25).

[0123] When the process of step S25 is completed or when it is determined that the processing timing has not come (step S20: No), the processing unit 12 determines whether the operation end timing has come (step S26). The processing unit 12 determines that the operation end timing has come when, for example, the power supply of the information processing device 1 is turned off.

[0124] If the processing unit 12 determines that the operation end time has not arrived (step S26: No), it transitions to step S20, and if it determines that the operation end time has arrived (step S26: Yes), it terminates the processing shown in FIG. 6.

[0125] 5. Modifications In the above-described example, the advertisement presentation device 4 is located inside the vehicle 2, but the information processing system 100 may further include an advertisement presentation device 4 attached to the outer surface of the vehicle 2 on the exit door side.

[0126] In this case, the providing unit 34 can cause the advertisement presentation device 4 outside the vehicle 2 to provide the provided advertisement for a predetermined period of time after it is determined that the passenger P predicted to disembark by the prediction unit 32 has disembarked from the vehicle 2. The provided advertisement in this case is the same as the provided advertisement provided from the advertisement presentation device 4 inside the vehicle 2. The determining unit 31 determines whether or not the passenger P has disembarked from the vehicle 2 based on the passenger identification information provided from the on-board device 3 or the like.

[0127] In addition, the provision unit 34 can transmit the provided advertisement to the terminal device of the passenger P who has disembarked within a predetermined period of time after it is determined that the passenger P who is predicted to disembark by the prediction unit 32 has disembarked from the vehicle 2, and output the provided advertisement from the terminal device of the passenger P.

[0128] Furthermore, when another vehicle 2 is traveling parallel to the vehicle, the providing unit 34 can also display the provided advertisement on the advertisement notification device 4 attached to the outer surface of the exit door side of the other vehicle 2 traveling parallel to the vehicle. The acquiring unit 30 acquires other vehicle position information which is information indicating the position of the other vehicle 2, and the determining unit 31 determines whether or not the other vehicle 2 is traveling parallel to the vehicle itself based on the other vehicle position information acquired by the acquiring unit 30.

[0129] In addition, for example, when an advertising target (e.g., a store, facility, event, etc.) is present up to the drop-off location, the provision unit 34 can also cause the advertisement presentation device 4 to provide the provided advertisement by the time the position of the advertising target becomes perpendicular to the traveling direction of the vehicle 2.

[0130] Furthermore, in the above example, when the on-board device 3 is a wireless router, MAC address information is transmitted from the on-board device 3 to the information processing device 1 as passenger identification information, but IP address information may be transmitted as passenger identification information to the information processing device 1. The terminal device of passenger P transmits IP address information, passenger ID information, and the like to the information processing device 1, so that the information processing device 1 can identify the passenger ID.

[0131] [6. Hardware Configuration] The information processing device 1 according to the embodiment described above is realized by a computer 80 having a configuration as shown in Fig. 7. Fig. 7 is a hardware configuration diagram showing an example of the computer 80 that realizes the functions of the information processing device 1 according to the embodiment. The computer 80 has a CPU 81, a RAM 82, a ROM (Read Only Memory) 83, a HDD (Hard Disk Drive) 84, a communication interface (I / F) 85, an input / output interface (I / F) 86, and a media interface (I / F) 87.

[0132] The CPU 81 operates and controls each part based on a program stored in the ROM 83 or the HDD 84. The ROM 83 stores a boot program executed by the CPU 81 when the computer 80 is started up, and programs that depend on the hardware of the computer 80.

[0133] The HDD 84 stores programs executed by the CPU 81, data used by such programs, etc. The communication interface 85 receives data from other devices via the network N (see FIG. 2) and sends it to the CPU 81, and transmits data generated by the CPU 81 to other devices via the network N.

[0134] The CPU 81 controls output devices such as a display and a printer, and input devices such as a keyboard and a mouse, via the input / output interface 86. The CPU 81 acquires data from the input devices via the input / output interface 86. The CPU 81 also outputs data generated via the input / output interface 86 to the output devices.

[0135] The media interface 87 reads a program or data stored in a recording medium 88 and provides it to the CPU 81 via the RAM 82. The CPU 81 loads the program from the recording medium 88 onto the RAM 82 via the media interface 87 and executes the loaded program. The recording medium 88 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase change rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0136] For example, when the computer 80 functions as the information processing device 1 according to the embodiment, the CPU 81 of the computer 80 executes a program loaded onto the RAM 82 to realize the function of the processing unit 12. In addition, the HDD 84 stores data in the storage unit 11. The CPU 81 of the computer 80 reads and executes these programs from a recording medium 88, but as another example, these programs may be obtained from another device via the network N.

[0137] [7. Other] In addition, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by a known method. In addition, the information including the processing procedures, specific names, various data and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

[0138] In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc.

[0139] For example, the above-mentioned information processing device 1 may be realized by a terminal device and a server computer, or may be realized by multiple server computers. Also, depending on the functions, the configuration can be flexibly changed, such as by calling an external platform using an API (Application Programming Interface) or network computing.

[0140] Furthermore, the above-described embodiments and modifications can be appropriately combined as long as the processing contents are not contradictory.

[0141] 8. Effects As described above, the information processing device 1 according to the embodiment includes a prediction unit 32 that predicts a disembarking place where a passenger P of a vehicle 2 will disembark from the vehicle 2, a selection unit 33 that selects an advertisement corresponding to the disembarking place predicted by the prediction unit 32 as an advertisement to be provided before the passenger P predicted by the prediction unit 32 to disembark at the disembarking place gets off the vehicle 2, and a provision unit 34 that causes the advertisement presentation device 4 provided in the vehicle 2 to provide the advertisement selected by the selection unit 33 to the passenger P. This allows the information processing device 1 to provide an appropriate advertisement to the passenger P.

[0142] Furthermore, the selection unit 33 selects, as the advertisement to be provided, an advertisement according to the information of the passenger P predicted by the prediction unit 32 to get off the vehicle 2 at the alighting location and the alighting location predicted by the prediction unit 32. This enables the information processing device 1 to provide an appropriate advertisement to the passenger P.

[0143] Furthermore, when the prediction unit 32 predicts that there are multiple passengers P who will get off at the same location, the selection unit 33 selects advertisements according to the information of the multiple passengers P and the alighting locations as advertisements to be presented. This allows the information processing device 1 to present appropriate advertisements to the passengers P.

[0144] Moreover, the information on the passenger P includes one or more pieces of information on the attributes of the passenger P and information on the behavior history of the passenger P. This allows the information processing device 1 to provide an appropriate advertisement to the passenger P.

[0145] Further, the prediction unit 32 predicts the probability of conversion due to the advertisement, and the selection unit 33 selects, as the advertisement to be provided, an advertisement for which the probability of conversion predicted by the prediction unit 32 satisfies a predetermined condition. This enables the information processing device 1 to provide an appropriate advertisement to the passenger P.

[0146] In addition, the providing unit 34 provides the advertisement to the passengers P via the advertisement presentation device 4 at a timing based on the distance to the drop-off location of the vehicle 2 and the number of passengers P predicted by the predicting unit 32 to get off at the drop-off location. This allows the information processing device 1 to provide appropriate advertisements to the passengers P.

[0147] In addition, the advertisement presentation device 4 includes at least one of a display unit that displays the provided advertisement and a voice output unit that outputs the provided advertisement by voice. This allows the information processing device 1 to provide an appropriate advertisement to the passenger P.

[0148] Furthermore, the selection unit 33 selects the advertisement to be provided based on the time period, the day of the week, the weather, and the travel speed of the vehicle 2. This enables the information processing device 1 to provide an appropriate advertisement to the passenger P.

[0149] The above describes the embodiment of the present application in detail based on the drawings, but this is merely an example, and the present invention can be implemented in other forms that include various modifications and improvements based on the knowledge of those skilled in the art, including the forms described in the Disclosure of the Invention section.

[0150] Furthermore, the above-mentioned "section, module, unit" can be read as "means" or "circuit", etc. For example, an acquisition section can be read as an acquisition means or an acquisition circuit. [Explanation of symbols]

[0151] 1. Information processing device 2 Vehicles 3. Onboard equipment 4. Advertising notification device 10. Communications Department 11 Storage section 12 Processing section 20 Passenger information storage unit 21 Advertising information storage unit 30 Acquisition Department 31 Judgment section 32 Prediction Department 33 Selection section 34 Providing Department 100 Information Processing Systems N Network

Claims

1. A prediction unit predicts an alighting location where a passenger of a vehicle will alight from the vehicle; a selection unit that selects, as an advertisement to be provided, an advertisement corresponding to the alighting location predicted by the prediction unit at which the passenger will alight from the vehicle; a providing unit that provides the advertisement selected by the selecting unit to the passenger from an advertisement presentation device provided in the vehicle before the passenger predicted by the predicting unit to get off at the get-off location gets off the vehicle.

23. An information processing apparatus comprising:

2. The selection unit is An advertisement according to information of the passenger predicted by the prediction unit to get off the vehicle at the alighting location and the alighting location predicted by the prediction unit is selected as the advertisement to be provided.

2. The information processing apparatus according to claim 1,

3. The selection unit is When the prediction unit predicts that a plurality of passengers will use the same location as the alighting location, advertisements corresponding to information of the plurality of passengers and the alighting location are selected as the advertisements to be provided.

3. The information processing apparatus according to claim 2.

4. The passenger information is: The information includes at least one of information on the attributes of the passenger and information on the behavior history of the passenger.

4. The information processing apparatus according to claim 2, wherein the information processing apparatus is a computer.

5. The prediction unit is Predict the probability of conversion due to advertising, The selection unit is An advertisement for which the probability of conversion predicted by the prediction unit satisfies a predetermined condition is selected as the advertisement to be provided.

4. The information processing apparatus according to claim 1, wherein the information processing apparatus is a computer.

6. The providing unit is The advertisement is provided to the passengers via the advertisement presentation device at a timing based on the distance of the vehicle to the alighting location and the number of passengers predicted by the prediction unit to alight at the alighting location.

4. The information processing apparatus according to claim 1, wherein the information processing apparatus is a computer.

7. The advertisement notification device includes: The apparatus includes at least one of a display unit that displays the provided advertisement and an audio output unit that outputs the provided advertisement by audio.

4. The information processing apparatus according to claim 1, wherein the information processing apparatus is a computer.

8. The selection unit is Selecting the advertisements to be served based on time of day, day of the week, weather, and the speed at which the vehicle is traveling.

4. The information processing apparatus according to claim 1, wherein the information processing apparatus is a computer.

9. 1. A computer-implemented information processing method, comprising: a prediction step of predicting an alighting location where a passenger of a vehicle will alight from said vehicle; a selection step of selecting, as an advertisement to be provided, an advertisement corresponding to the alighting location predicted by the prediction step at which the passenger will alight from the vehicle; and a providing step of providing the advertisement selected in the selection step to the passenger, who is predicted to get off at the alighting location by the prediction step, from an advertisement presentation device provided in the vehicle, before the passenger gets off the vehicle.

23. An information processing method comprising:

10. a prediction step of predicting alighting locations where passengers of a vehicle will alight from said vehicle; a selection step of selecting, as a provided advertisement, an advertisement corresponding to the alighting location predicted by the prediction step at which the passenger will alight from the vehicle; a provision step of providing the advertisement selected by the selection step to the passenger, who is predicted to get off at the alighting location by the prediction step, from an advertisement presentation device provided in the vehicle, before the passenger gets off the vehicle.

2. An information processing program comprising:

Images