Information processing device, calculation method, and calculation program

Abstract

To increase a motivation for a user to watch an object on which the user is not focusing their attention.SOLUTION: An information processing device includes: a first acquisition unit that obtains measurement data for measuring or predicting a time when each of moving bodies moving on a course of a race reaches at a measurement point on the course; a second acquisition unit that obtains position information of a user; and a calculation unit that calculates a watching score for evaluating the watching degree of the user, based on the number of moving bodies whose predicted arrival positions predicted from the measurement data are within a predetermined range from the position information of the user.SELECTED DRAWING: Figure 4

Description

[Technical field]

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

[0002] As examples of technologies to support watching sports, conventional technologies have been proposed, such as a real-time location information providing system that provides the location information of athletes in real time, and a cheering system that calculates and displays the amount of cheering for each cheer target based on cheering input from the user's terminal device. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2020-176922 A [Patent Document 2] JP 2022-184698 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, the above conventional technologies only provide information and support for the target of the user's interest in the race. Therefore, the above conventional technologies have room for improvement in terms of increasing the motivation of the user to watch the target that the user is not interested in.

[0005] One aspect of the present disclosure aims to improve a user's motivation to watch an object that the user is not paying attention to. [Means for solving the problem]

[0006] An information processing device in one embodiment has a first acquisition unit that acquires measurement data that measures or predicts the time at which each moving object moving on a course on which a race is to arrive at a measurement point on the course, a second acquisition unit that acquires user position information, and a calculation unit that calculates a viewing score that evaluates the degree of viewing by the user based on the number of moving objects whose predicted arrival positions, predicted from the measurement data, are within a predetermined range from the user's position information.

[0007] In one embodiment, a calculation method involves a computer executing a process that acquires measurement data for each moving object moving along a course on which a race is to be run, measuring or predicting the time that the moving object will arrive at a measurement point on the course, acquires user location information, and calculates a viewing score that evaluates the degree of viewing by the user based on the number of moving objects whose predicted arrival positions, as calculated from the measurement data, are within a predetermined range from the user's location information.

[0008] A calculation program in one embodiment causes a computer to execute a process of acquiring measurement data for each moving object moving on a course on which a race is to be conducted, measuring or predicting the time that the moving object will arrive at a measurement point on the course, acquiring user location information, and calculating a viewing score that evaluates the degree of viewing by the user based on the number of moving objects whose predicted arrival positions, as calculated from the measurement data, are within a predetermined range from the user's location information. Effect of the Invention

[0009] According to one embodiment, it is possible to improve the user's motivation to watch a target that the user is not paying attention to. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a spectator support system. [Diagram 2] FIG. 2 is a diagram showing an example of transition of a screen displayed on a user terminal. [Diagram 3] FIG. 3 is a diagram showing a display example of the cheering score. [Figure 4] FIG. 4 is a block diagram illustrating an example of a functional configuration of the server device. [Diagram 5] FIG. 5 is a diagram showing an example of the arrival time DB. [Figure 6] FIG. 6 is a diagram showing an example of a section belonging to an unreached section. [Figure 7] FIG. 7 is a diagram (1) showing an example of calculation of the cheering score. [Figure 8] FIG. 8 is a diagram (2) showing an example of calculation of the cheering score. [Figure 9] FIG. 9 is a diagram (3) showing an example of calculation of the cheering score. [Figure 10] FIG. 10 is a diagram showing an example of the watching score DB. [Figure 11] FIG. 11 is a diagram showing an example of a ranking display of cheering scores. [Figure 12] FIG. 12 is a diagram illustrating an example of a player heat map. [Figure 13] FIG. 13 is a flowchart showing the procedure of the measurement data acquisition process. [Figure 14] FIG. 14 is a flowchart showing the procedure of the cheering score calculation process. [Figure 15] FIG. 15 is a diagram illustrating an example of a hardware configuration. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, an information processing device, a calculation method, and a calculation program according to the present disclosure will be described with reference to the accompanying drawings. Note that the embodiment merely illustrates one example or aspect, and the structure, action, function, nature, characteristics, method, use, and the like according to the present disclosure are not limited by such an example.

[0012] <System configuration> Fig. 1 is a diagram showing an example of the configuration of a spectating support system. Fig. 1 shows, as one example, a spectating support system 1 that provides a spectating support service that supports the spectating of a race.

[0013] Here, "race" refers to any competition in which participants compete by moving on a course. For example, the race may be a running competition such as a marathon. In addition, the race may be a bicycle race, a boat race, a car race, or a triathlon. The moving object moving on the course in this way is not necessarily limited to a person, but may be a bicycle, a car, or the like. Furthermore, "spectating" refers to the general act of viewing the course. For example, watching may include cheering, cheering, encouragement, and the like.

[0014] Below, as just one example of a use case, we will give an example in which the race targeted by the above-mentioned spectator support service is a "running event."

[0015] 1, the watching support system 1 may include a server device 10, measurement devices 30A-30M, and user terminals 50A-50N. Hereinafter, when it is not necessary to distinguish between the individual measurement devices 30A-30M, the measurement devices 30A-30M may be referred to as "measurement device 30." Also, when it is not necessary to distinguish between the individual user terminals 50A-50N, the user terminal 50A and the user terminal 50B may be referred to as "user terminal 50."

[0016] The server device 10, the measuring device 30, and the user terminal 50 may be communicatively connected via any network NW. For example, the network NW may be realized by any technology, whether wired or wireless, such as an intranet, the Internet, or a low-power wireless communication standard for the Internet of Things (IoT). The network NW may not be a single network, but may be an intranet and the Internet connected via a network device such as a gateway.

[0017] The server device 10 is an example of an information processing device that provides the above-mentioned spectating support service. For example, the server device 10 can be realized as a SaaS (Software as a Service), FaaS (Function as a Service), or Baas (Backend as a Service) type application. This allows the above-mentioned spectating support service to be provided as a cloud service. Additionally, the server device 10 can also be realized as a Web server that provides the above-mentioned spectating support service on-premise.

[0018] For example, the above-mentioned spectator support service may include a "tracking and display function," a "record list function," a "message sending function," and a "replay mode function." The "tracking and display function" is a function that tracks and displays one or more runners on a course map. The "record list function" is a function that provides a list of records in which each point is associated with the recorded time reached at that point. The "message sending function" is a function that sends messages to runners. The "replay mode function" is a function that replays the movements of runners after the race ends.

[0019] The measurement device 30 is a device that measures the time when a runner participating in a running competition reaches a measurement point on course C. In one aspect, in a running competition, a series of movements from arriving at a measurement point on course C to departing is continuous, so "arrival" here can also be rephrased as "passing through" or "departing." Hereinafter, the time when a runner reaches a measurement point on course C may be referred to as "arrival time."

[0020] Such measurement of the arrival time may be realized by any technology such as short-range wireless communication or position measurement. As an example, when short-range wireless communication is used, the arrival time can be measured by communication between a transmitter worn by the runner and a receiver installed at the measurement point. For example, in FIG. 1, a scene where two runners R1 and R2 arrive at a measurement point C1 is illustrated as a schematic diagram 20.

[0021] According to the example of the schematic diagram 20, runners R1 and R2 are fitted with RFID (Radio Frequency IDentification) tags 3. The RFID tags 3 may be fitted to specific parts of runners R1 and R2, such as their shoes or bibs. Meanwhile, an RFID reader 30B1 with a mat-shaped antenna is installed at the measurement point C1, as an example of a measurement device 30B. The RFID reader 30B1 can measure the arrival time as a timestamp when it reads information recorded in the RFID tag 3, such as a runner ID. The runner ID and the timestamp are uploaded to the server device 10 from the measurement device 30, as an example of measurement data, together with identification information of the measurement point, such as a point ID.

[0022] As an example, the arrival time at points other than these measurement points can be predicted based on one or more sections, i.e., the travel time between adjacent points, so-called lap time. For example, FIG. 1 shows an example in which measurement devices 30 are installed at some points among the start (finish) point C0, the 5 km point C1, the 10 km point C2, ..., and the 40 km point C9. That is, the start point C0, the 5 km point C1, the 25 km point C5, the 30 km point C6, the 35 km point C8, and the 40 km point C9 are set as measurement points, and measurement devices 30A, 30B, 30F, 30G, 30I, and 30J are installed. In this case, the arrival time at the 10 km point C2 can be predicted from the lap time from the start point C0 to the 5 km point C1. In addition, the arrival time at the 35 km point C7 can be predicted from the lap time from the start point C0 to the 5 km point C1, as well as the lap time from the 25 km point C5 to the 30 km point C6.

[0023] The user terminal 50 is a terminal device used by a user who receives the above-mentioned spectating support service. For example, the user terminal 50 may be realized by a mobile terminal device such as a smartphone, a tablet terminal, or a wearable terminal. Note that the user terminal 50 is not limited to a mobile terminal device, and may be realized by any computer including a desktop or laptop personal computer.

[0024] <One aspect of the issue> As explained in the Background Art section above, all of the above conventional technologies merely provide information and support for the subjects that the user is interested in during the race. Therefore, the above conventional technologies have room for improvement in terms of increasing the motivation of the user to watch subjects that the user is not interested in.

[0025] <One aspect of the problem-solving approach> Therefore, the server device 10 according to an embodiment of the present disclosure provides a calculation function that calculates a cheering score that evaluates the degree of cheering by a user based on the number of players the user has passed by. This cheering score has an aspect of counting the number of players the user has passed by. In view of this aspect, the calculation function according to an embodiment of the present disclosure may be referred to as a "cheering counter."

[0026] One aspect of the user is that they wait along the course to meet and cheer on their family and friends who are participating in the race, eagerly waiting for them to arrive. On the other hand, there is also an aspect where the user is so focused on cheering on their family and friends that they do not pay attention to other runners besides their family and friends.

[0027] From this perspective, the cheering counter provides each user with an incentive to cheer on players that the user is not paying attention to through the evaluation based on the cheering score. As a result, an environment can be created in which cheering on other players is more highly rated than wasting free time, such as waiting time for family and friends to arrive at the user, by operating the user terminal 50. Such an environment encourages an increase in cheering motivation, such as "I cheered for so many players" or "I'll cheer more."

[0028] Therefore, according to the cheering counter according to one embodiment of the present disclosure, it is possible to improve the motivation of the user to watch the event, even if the user is not paying attention to the event. By improving the motivation to watch the event, it is possible to improve the excitement of the event, such as a race. This can also lead to the creation of a sense of unity among the spectators.

[0029] Here, the cheering counter according to one embodiment of the present disclosure can unconditionally enable the count-up of the cheering score, but can also enable the count-up under certain conditions.

[0030] For example, the cheering action by the user, such as the action of shaking the user terminal 50, can be narrowed down to a state in which detection is made, and the count-up of the cheering score calculated by the cheering counter according to one embodiment of the present disclosure can be enabled.

[0031] This can increase the motivation of users to perform cheering actions, which can help to liven up the cheering at running events.

[0032] Next, an example of a conductor line for activating the cheering counter according to one embodiment of the present disclosure will be given. Fig. 2 is a diagram showing an example of a transition of a screen displayed on the user terminal 50. Fig. 2 illustrates a course map screen 41 as an example of a screen from which the cheering counter is activated, but it goes without saying that another screen can be used as the starting point.

[0033] As an example only, the user terminal 50 displays a course map screen 41 of the XXth XX Marathon. For example, the course map screen 41 is displayed when the "Course Map" menu is selected from the five types of bottom navigation. On such a screen as the course map screen 41, a banner 41A and an icon 41B are arranged as examples of GUI (Graphical User Interface) components that guide the user to start the cheering counter. When an operation is performed on the banner 41A or the icon 41B, the course map screen 41 transitions to the cheering counter screen 42.

[0034] The cheering counter screen 42 provides guidance on the trial experience of the cheering counter and on starting the cheering counter. For example, the cheering counter screen 42 displays a message "The number of runners (estimated value) that pass in front of you while you are cheering by shaking your smartphone along the road" as an example of guidance explaining the function of the cheering counter. Furthermore, the cheering counter screen 42 has a button 42A that guides you to the trial experience of the cheering counter and a button 42B that requests the start of the cheering counter. When the button 42A is operated, the screen transitions from the cheering counter screen 42 to the cheering counter screen 43. When the button 42B is operated, the trial experience is skipped and the cheering counter according to one embodiment of the present disclosure can be started.

[0035] The cheering counter screen 43 can provide a trial experience of the cheering action. For example, as an example of guidance to encourage the user to cheer, a message "Try holding your smartphone in your hand and shaking it lightly" is displayed. At this time, if the action of shaking the user terminal 50 is detected from the measurement value of the sensor device mounted on the user terminal 50, a predetermined sound, such as the sound of a cowbell, can be output from the user terminal 50. Then, if the action of shaking the user terminal 50 is successfully detected, the cheering counter screen 43 transitions to a cheering counter screen 44.

[0036] The cheering counter screen 44 provides guidance on starting the cheering counter. For example, the cheering counter screen 44 displays messages such as "Perfect!" and "Let's keep it up!" as examples of notifications that the cheering action was successfully detected. Furthermore, the cheering counter screen 44 has a button 44A for requesting the start of the cheering counter. When this button 44A is operated, the cheering counter according to one embodiment of the present disclosure can be started.

[0037] When the cheering counter is activated in this manner, the cheering counter starts counting up. FIG. 3 is a diagram showing an example of a cheering score display. FIG. 3 shows a course map screen 45 as an example of a screen after the cheering counter is activated. As shown in FIG. 3, after the cheering counter is activated, the cheering score is displayed in association with the cheering counter icon 45A. This cheering score display may be updated in conjunction with the counting up by the cheering counter. Such a cheering score display can encourage an improvement in cheering motivation, such as "I cheered for so many athletes" or "I'll cheer more."

[0038] The cheering counter may be packaged with the watching support service and provided as a part of the watching support service. Not limited to this, the cheering counter may be provided independently of the watching support service. In this case, the hardware resources that provide the watching support service and the cheering counter, such as physical devices and physical elements, may be different.

[0039] <Configuration of Server Device 10> Next, a functional configuration example of the server device 10 according to one embodiment of the present disclosure will be described. Fig. 4 is a block diagram showing a functional configuration example of the server device 10. Fig. 4 shows a block diagram of functions of the server device 10 corresponding to the game watching support service.

[0040] Here, the cheering counter may be packaged with the watching support service and provided as a part of the watching support service. Not limited to this, the cheering counter may be provided independently of the watching support service. In this case, the hardware resources, such as physical devices and physical elements, that provide the watching support service and the cheering counter may be different.

[0041] As shown in Fig. 4, the server device 10 has a communication control unit 11, a storage unit 13, and a control unit 15. Note that Fig. 4 merely illustrates a selection of functional units related to the functions corresponding to the above-mentioned game watching support service, and the server device 10 may be provided with functional units other than those illustrated.

[0042] The communication control unit 11 is a functional unit that controls communication with other devices such as the measuring device 30 and the user terminal 50. As just one example, the communication control unit 11 can be realized by a network interface card.

[0043] As one aspect, the communication control unit 11 receives measurement data from the measurement device 30. In addition, the communication control unit 11 outputs to the measurement device 30 an instruction and settings for uploading the measurement data.

[0044] In another aspect, the communication control unit 11 accepts various requests and uploads of various information related to the above-mentioned watching support service and the above-mentioned cheering counter from the user terminal 50. In addition, the communication control unit 11 outputs processing results related to the above-mentioned watching support service and the above-mentioned cheering counter to the user terminal 50.

[0045] The storage unit 13 is a functional unit that stores various data. As an example, the storage unit 13 is realized by an internal, external, or auxiliary storage of the server device 10. For example, the storage unit 13 stores information such as an arrival time DB (DataBase) 13A, a predicted position DB 13B, and a watching score DB 13C. The arrival time DB 13A, the predicted position DB 13B, and the watching score DB 13C will be described later together with a scene where reference or registration is performed.

[0046] The control unit 15 is a functional unit that performs overall control of the server device 10. For example, the control unit 15 can be realized by a hardware processor. As shown in Fig. 4, the control unit 15 has a first acquisition unit 15A, a prediction unit 15B, a second acquisition unit 15C, a calculation unit 15D, a display control unit 15E, and an assignment unit 15F. The control unit 15 may be realized by hardwired logic or the like.

[0047] The first acquisition unit 15A is a processing unit that acquires measurement data. In one embodiment, the first acquisition unit 15A can acquire measurement data including a location ID, a runner ID, and a time stamp from the measurement device 30. When the measurement data is acquired in this manner, the first acquisition unit 15A searches for a data entry, a so-called record, corresponding to the runner ID included in the measurement data in the arrival time DB 13A stored in the storage unit 13. Then, the first acquisition unit 15A registers the arrival time corresponding to the time stamp included in the measurement data in a field corresponding to the location ID included in the measurement data in the record corresponding to the runner ID included in the measurement data.

[0048] The prediction unit 15B is a processing unit that predicts the arrival time at other points after the measurement point. In one aspect, when the measurement data is acquired by the first acquisition unit 15A, the prediction unit 15B predicts the arrival time at a point after the measurement point corresponding to the point ID included in the measurement data. Hereinafter, in order to distinguish the label of a point located after the measurement point where the arrival time has been measured from the measurement point, a point located after the measurement point where the arrival time has been measured may be referred to as an "unreached point".

[0049] For example, the prediction unit 15B can make predictions based on one or more sections, i.e., the travel time required between adjacent points for which the arrival time has already been measured, that is, so-called lap times. For example, the arrival time to the 10 km point C2 can be predicted using the lap time from the start point C0 to the 5 km point C1. In addition, the arrival time to the 35 km point C7 can be predicted using the lap time from the 25 km point C5 to the 30 km point C6 in addition to the lap time from the start point C0 to the 5 km point C1.

[0050] FIG. 5 is a diagram showing an example of the arrival time DB 13A. As shown in FIG. 5, the arrival time DB 13A may be a collection of data in which the arrival time at each point is associated with each runner. For example, FIG. 5 shows an example of a runner with a runner ID of "R11". Furthermore, FIG. 5 shows an example in which the arrival time at the 5km point C1, "08:50:00", has been acquired by the first acquisition unit 15A in a state in which the arrival time at the start point C0, "08:30:00", has already been registered.

[0051] In this case, the first acquisition unit 15A registers the arrival time "08:50:00" in the field of the 5 km point. After that, the prediction unit 15B predicts the arrival time from the 10 km point C2 to the finish point C0 based on the lap time from the start point C0 to the 5 km point C1.

[0052] More specifically, the lap time from the start point C0 to the 5km point C1 can be calculated by subtracting the arrival time at the start point C0 from the arrival time at the 5km point C1, i.e., "08:50:00-08:30:00", resulting in "00:20:00". Here, under the assumption that "marathon participants run at a roughly constant pace", the arrival time from the 10km point C2 to the finish point C0 is predicted based on the arrival time at the point immediately before the point to be calculated and the measured lap times.

[0053] For example, the arrival time at the 10km point C2 can be calculated as "09:10:00" by adding the lap time from the start point C0 to the 5km point C1 to the arrival time at the 5km point C1. Furthermore, the arrival time at the 15km point C3 can be calculated as "09:30:00" by adding the lap time from the start point C0 to the 5km point C1 to the arrival time at the 10km point C1. The arrival time from the 20km point C4 to the finish point C0 can also be predicted in a similar manner. In this way, the arrival time predicted for each point from the 10km point C2 to the finish point C0 is registered in the arrival time DB 13A. The calculation of the arrival time described above may be performed in the user terminal 50. By performing the calculation of the arrival time in the user terminal 50, it is possible to prevent the server device 10 from being overloaded with processing.

[0054] In FIG. 5, an example is given in which the arrival time at the 5 km point C1 is acquired as the measurement data. However, when measurement data at the start point C0 is acquired, the prediction unit 15B can predict the default arrival time according to the number of seconds from the starting gun. For example, the prediction unit 15B executes a prediction that brings the arrival time at each point closer to the fastest as the time difference between the time of the starting gun and the arrival time at the start point C0 becomes smaller. In addition, the prediction unit 15B executes a prediction that brings the arrival time at each point closer to the time limit as the time difference between the time of the starting gun and the arrival time at the start point C0 becomes larger. Such predictions have a certain level of accuracy because there is a high possibility that the runner who starts immediately after the starting gun is fired is a top-ranked runner such as an invited runner.

[0055] 1 shows an example in which the measurement device 30 is installed at the start point C0, but when the measurement device 30 is not installed at the start point C0, the prediction unit 15B can make the following prediction. That is, when measurement data is acquired at the first measurement point, the prediction unit 15B regards the gun time as the arrival time of the immediately preceding point, and can predict the arrival time of points after the first measurement point.

[0056] In addition, the prediction unit 15B can correct the predicted value of the arrival time according to the elevation difference of the section of the course C. For example, the prediction unit 15B can increase the predicted value of the arrival time as the elevation difference becomes larger. Also, the prediction unit 15B can decrease the predicted value of the arrival time as the elevation difference becomes smaller.

[0057] In another aspect, the prediction unit 15B predicts, for each unreached section that has an unreached point as its end point, the passing time period during which a section belonging to the unreached section will be passed among sections into which a course map including all of course C or part of course C is divided.

[0058] FIG. 6 is a diagram showing an example of a section belonging to an unreached section. As shown in FIG. 6, a course map 60 including the course C is divided into a mesh shape. For example, the course map 60 is divided into sections each having a side length of 100 m. Such mesh division is performed in advance. Here, the sections at 5 km point C1 and 10 km point C2 are given as examples of unreached sections. In this case, the unreached section includes a section including at least a part of the unreached section of the course C, that is, the section shown by hatching in FIG. 6. In this way, for each section shown by hatching, a passing time period including a running start time at which the running of the section starts and a running end time at which the running of the section ends is predicted. These running start time and running end time can be calculated based on, for example, the arrival time at the point C1 immediately before the unreached point C2, the distance from the point C1 immediately before the unreached point C2 to the course start position or course end position within the section, and the measured lap time.

[0059] In this way, the passing time period predicted for each section belonging to the unreached section is registered in the predicted position DB 13B. For example, the predicted position DB 13B may be a collection of data in which the passing time period of each section is associated with each runner ID. Among the records included in the predicted position DB 13B, the prediction unit 15B searches for a record corresponding to the runner ID included in the measurement data. Then, the prediction unit 15B registers the passing time period in the field of the section corresponding to the unreached section among the records corresponding to the runner ID included in the measurement data.

[0060] Returning to the description of FIG. 4, the second acquisition unit 15C is a processing unit that acquires the position information of the user terminal 50. In one embodiment, the second acquisition unit 15C can acquire the position information of the user terminal 50, such as coordinates of latitude and longitude, from the user terminal 50 of a user who has an account for the above-mentioned watching support service. As one example, the upload of the position information between the user terminal 50 and the server device 10 can be accepted under a specific condition, such as a certain period, after accepting a request to start the cheering counter. For example, the above period can be 10 seconds or 1 minute. Such a period may be set based on an interval at which a runner with a lower limit of ability among participants participating in a running competition, such as a runner running at a speed corresponding to the upper limit of the time limit set for the race, can complete the movement of one or more sections. This prevents the same runner from being counted twice in the same section.

[0061] The calculation unit 15D is a processing unit that calculates a cheering score that evaluates the degree of cheering by the user. As one aspect, the calculation unit 15D calculates the cheering score based on the number of players whose predicted arrival positions, which are predicted from the measurement data acquired by the first acquisition unit 15A, are within a predetermined range from the user's position information acquired by the second acquisition unit 15C.

[0062] More specifically, when the second acquisition unit 15C acquires the position information of the user U at time t, the calculation unit 15D determines whether the spectator mode of the user U is set to manual mode. The "spectator mode" here may include a manual mode in which the cheering action is manual and an auto mode in which the cheering action is automatic. In the auto mode (when S302 shown in FIG. 14 is No), the cheering score is calculated based on the spectator section of the user U and the predicted arrival position of the player, regardless of whether the user terminal 50 is shook. When the spectator mode of the user U is set to manual mode, the calculation unit 15D determines whether the user terminal 50 is shook when the position information of the user U is measured. For example, the calculation unit 15D can detect whether the user terminal 50 is shook based on the measured value measured by a sensor device mounted on the user terminal 50. Examples of such a sensor device include a motion sensor such as an acceleration sensor or a gravity sensor, or a gyro sensor. Then, when a motion of shaking the user terminal 50 is detected when measuring the position information of the user U, the calculation unit 15D enables the count-up of the cheering score.

[0063] Here, in the manual mode, the enablement of the count-up of the cheering score can be realized in the following two patterns. The first pattern is pattern 1 in which, when the user terminal 50 detects a motion of shaking the user terminal 50, the user terminal 50 uploads location information to the server device 10. That is, in pattern 1, when the user terminal 50 is not detected to shake the user terminal 50, the location information is not uploaded. In this case, the count-up of the cheering score is suppressed. The second pattern is pattern 2 in which, when the server device 10 detects a motion of shaking the user terminal 50, the calculation of the cheering score is started. In this case, from the aspect of determining whether or not the user terminal 50 is shaken on the server device 10 side, the user terminal 50 may upload the measurement value of the sensor device together with the location information to the server device 10. Pattern 1, in which location information is sent to server device 10 on the condition that the user terminal 50 detects a shaking action of the user terminal, can reduce the amount of information (communication volume) exchanged between server device 10 and user terminal 50, compared to pattern 2, in which the measurement values ​​of the sensor device must be uploaded to server device 10.

[0064] When the count-up of the cheering score is thus enabled, the calculation unit 15D identifies the section that corresponds to the position information of the user U among the sections into which the course map is divided. Hereinafter, the section that corresponds to the position information of the user U may be referred to as a "spectating section" since it also has an aspect of being a section where the user U watches the race. Then, the calculation unit 15D counts the number of athletes participating in the running race whose predicted arrival position at the time t when the position information of the user U is acquired is included in the above-mentioned spectating section.

[0065] Here, the predicted arrival position of each runner at time t can be identified as follows. That is, the calculation unit 15D can identify, for each record included in the predicted position DB 13B, the section corresponding to the passing time zone to which the time t belongs, as the predicted arrival position. If the section identified as the predicted arrival position in this way coincides with and / or is adjacent to the viewing section of the user U, the runner ID of the runner whose predicted arrival position has been identified is extracted.

[0066] Thereafter, the calculation unit 15D calculates the added points of each player located in the spectating section of the user U. At this time, the calculation unit 15D can assign a weight corresponding to the popularity of the player. For example, the more the popularity of the player, the greater the weight can be assigned. In addition, the calculation unit 15D can assign a weight according to the spectating section of the user U. For example, the calculation unit 15D can assign a weight corresponding to the congestion degree of the spectating section of the user U. In this case, the lower the congestion degree of the spectating section, the greater the weight can be assigned. In addition, the calculation unit 15D can assign a weight corresponding to the relevance of the spectating section of the user U to the sponsor. In this case, the higher the relevance of the spectating section to the sponsor, the greater the weight can be assigned. Then, the calculation unit 15D calculates the added points of the player by adding the sum of the weight of the popularity, the weight of the congestion degree, and the weight of the sponsor relevance to the basic points of the player. Thereafter, the calculation unit 15D calculates the cheering score of the user U at time t by tallying up the added points of the players located in the spectating section. Then, the calculation unit 15D cumulatively adds the support score of the user U at time t to the cumulative support score accumulated up to time t.

[0067] 7 to 9 are diagrams showing examples of calculation of cheering scores. In Figs. 7 to 9, an example is given in which the popularity of a player is divided into two stages, "unknown" or "famous." Furthermore, in Figs. 7 to 9, an example is given in which the congestion level of a spectator section is divided into two stages, "not crowded" or "crowded." Furthermore, in Figs. 7 to 9, an example is given in which the sponsor relevance level of a spectator section is divided into two stages, "not relevant" or "relevant."

[0068] As one embodiment, FIG. 7 shows an excerpt of a spectating section #11 corresponding to the position information of user U1 from among the sections into which the course map is divided. Here, spectating section #11 is classified as crowded and without sponsor relevance. Spectating section #11 includes the predicted arrival positions of three runners, runners R11, R12, and R13. All three runners are classified into the anonymous class.

[0069] In this case, the additional points for runner R11 are P R11 can be calculated as "1" by adding the basic point "1", the weight of the popularity of runner R11 "0", the weight of the congestion degree of spectator section #11 "0", and the weight of the sponsor relevance degree of spectator section #11 "0". In addition, the added point P R12 can be calculated as "1" by adding the basic point "1", the weight of the popularity of runner R12 "0", the weight of the congestion degree of spectator section #11 "0", and the weight of the sponsor relevance degree of spectator section #11 "0". Furthermore, the additional point P R13 The additional points P of these three runners can be calculated as "1" by adding the weight of the popularity of runner R13 ("0"), the weight of the congestion of spectator section #11 ("0"), and the weight of the sponsor relevance of spectator section #11 ("0"). R11 ~P R13 This gives the cheering score S of the user U11 at time t. U1 can be calculated as "3".

[0070] As another embodiment, FIG. 8 shows an excerpt of the spectating section #12 corresponding to the position information of user U2 from among the sections into which the course map is divided. Here, spectating section #12 is classified as not crowded and has sponsor relevance. The spectating section #12 includes the predicted arrival positions of three runners, runners R21, R22, and R23. All three runners are classified into the anonymous class.

[0071] In this case, the additional points for runner R21 are P R21 can be calculated as "3" by adding the basic point "1", the weight of the popularity of runner R11 "0", the weight of the congestion degree of spectator section #12 "1", and the weight of the sponsor relevance degree of spectator section #12 "1". In addition, the additional point P R22can be calculated as "3" by adding the basic point "1", the weight of the popularity of runner R22 "0", the weight of the congestion degree of spectator section #12 "1", and the weight of the sponsor relevance degree of spectator section #12 "1". Furthermore, the additional point P R23 The base point "1" can be calculated as "3" by adding the weight of the popularity of runner R23 "0", the weight of the congestion of spectator section #12 "1", and the weight of the sponsor relevance of spectator section #12 "1". R21 ~P R23 This gives the cheering score S of user U2 at time t. U2 can be calculated as "9".

[0072] As a further embodiment, FIG. 9 shows an excerpt of the spectator section #13 corresponding to the position information of user U3 from among the sections into which the course map is divided. Here, the spectator section #13 is classified as not crowded and has sponsor relevance. The spectator section #13 includes the predicted arrival positions of three runners, runners R31, R32, and R33. Of these three runners, runner R31 is classified into an unknown class. Meanwhile, runners R32 and R33 are classified into a famous class.

[0073] In this case, the additional points for runner R31 are P R31 can be calculated as "3" by adding the basic point "1", the weight of the popularity of runner R31 "0", the weight of the congestion degree of spectator section #13 "1", and the weight of the sponsor relevance degree of spectator section #13 "1". In addition, the additional point P R32 can be calculated as "4" by adding the basic point "1", the weight of the popularity of runner R32 "1", the weight of the congestion degree of spectator section #13 "1", and the weight of the sponsor relevance degree of spectator section #13 "1". Furthermore, the additional point P R33The added points P of these three runners are calculated as "4" by adding the weight of the popularity of runner R33 ("1"), the weight of the congestion of spectator section #13 ("1"), and the weight of the sponsor relevance of spectator section #13 ("1"). R31 ~P R33 This gives the cheering score S of user U3 at time t. U3 can be calculated as "11".

[0074] The cheering scores S shown in Figs. U1 , Cheer Score S U2 and Cheer Score S U3 The following is clear from the calculation results. As one aspect, by calculating the cheering score based on the weighting assigned to the popularity of the players, a calculation logic can be realized that provides an incentive to watch famous players. As another aspect, by calculating the cheering score based on the weighting assigned to the congestion degree of the user's viewing area, a calculation logic can be realized that guides the user to areas with relatively low congestion degrees. As a further aspect, by calculating the cheering score based on the weighting assigned to the sponsor relevance degree of the user's viewing area, a calculation logic can be realized that guides the user to stores related to sponsors.

[0075] Although Figs. 7 to 9 show an example in which the player's popularity is divided into two stages, it is not precluded that the popularity be divided into three or more stages. Also, Figs. 7 to 9 show an example in which the congestion level of the spectator section is divided into two stages, it is not precluded that the congestion level be divided into three or more stages. Furthermore, Figs. 7 to 9 show an example in which the sponsor relevance level of the spectator section is divided into two stages, it is not precluded that the sponsor relevance level be divided into three or more stages.

[0076] In addition, although Figures 7 to 9 show examples in which a total of three types of weighting are assigned, namely, a weighting of name recognition, a weighting of congestion, and a weighting of sponsor relevance, it is not necessary to assign any weighting, and it is also possible to assign one or more of the three types of weighting.

[0077] When the cumulative cheering score of user U at time t is calculated in this manner, the cumulative cheering score corresponding to user U among the cumulative cheering scores included in the watching score DB13C is updated to the cumulative cheering score of user U at time t. FIG. 10 is a diagram showing an example of the watching score DB13C. As shown in FIG. 10, the watching score DB13C may be a collection of data in which users and cheering scores are associated with each other. Note that, although FIG. 10 shows an example in which only the cumulative cheering score is managed, the breakdown of the popularity weight, the congestion weight, and the sponsor relevance weight may also be managed.

[0078] The display control unit 15E is a processing unit that executes display control for the user terminal 50. As one aspect, the display control unit 15E can display the watching score of the user on the user terminal 50. For example, the display control unit 15E can update the display of the cheering score on the user terminal 50 every time the calculation unit 15D calculates the latest cumulative cheering score. In addition, in one embodiment of the present invention, an example using the watching score DB is shown, but the watching score DB does not necessarily have to be used. Specifically, for example, at the timing when the user U wants to obtain his / her own score (the timing when the user U wants the cheering score to be displayed on the user terminal 50), the cheering score may be calculated each time from information on the watching position of the user U at the timing and before the timing and information on the predicted position of the player. As an example only, in the example shown in FIG. 3, an update may be performed to count up the display of the cheering score associated with the cheering counter icon 45A to the latest cumulative cheering score value.

[0079] As another aspect, the display control unit 15E can display the watching score calculated for each user in a ranking format. For example, the display control unit 15E sorts the cheering scores stored in the watching score DB 13C in descending order. This allows the users who use the cheering counter to be sorted in descending order of cheering scores. For example, in the example of the watching score DB 13C shown in FIG. 10, the users are sorted in the order of user U28, user U1, user U3, and user U2. Using the list of users sorted in descending order of cheering scores in this way, various ranking displays shown in FIG. 11 can be performed.

[0080] FIG. 11 is a diagram showing an example of a ranking display of cheering scores. In FIG. 11, three ranking screens 61 to 63 are illustrated as an example, which are displayed on the user terminal 50 of the user U1. As one embodiment, the display control unit 15E can display on the user terminal 50 a ranking screen 61 including the rank "2nd place" and cheering score "1245P" of the user U1. As another embodiment, the display control unit 15E can display on the user terminal 50 a ranking screen 62 including a list of users whose cheering scores are in a top predetermined number, for example, the top four, together with the rank "2nd place" and cheering score "1245P" of the user U1. Displaying these ranking screens 61 and 62 can encourage a competitive spirit in obtaining the cheering score. As a result, the excitement of the running event can be improved. As a further embodiment, the display control unit 15E can display a ranking screen 63 including a button 63A for sharing the cheering score together with the cheering score "1245P" of the user U1. By operating such button 63A, an API (Application Programming Interface) for posting the cheering score of user U1 to a social networking service (SNS) etc. can be called. This allows the excitement of the running event to be shared with a community other than the users of the above-mentioned spectating support service.

[0081] As a further aspect, the display control unit 15E can display a heat map in which the predicted arrival positions of the athletes are plotted on the course map. Hereinafter, the heat map in which the predicted arrival positions of the athletes are plotted may be referred to as a "athlete heat map." For example, the display control unit 15E plots sections corresponding to the predicted arrival positions of each athlete among the sections included in the course map. At this time, the display control unit 15E can distinguish the appearance form of the sections according to the number of athletes to be plotted. For example, the fill-in or hatching of the sections can be set to be darker as the number of athletes to be plotted increases. Also, the fill-in or hatching of the sections can be set to be lighter as the number of athletes to be plotted decreases. In addition, the predicted arrival positions of the athletes at any time from the start to the end of the running event can be plotted on the athlete heat map.

[0082] FIG. 12 is a diagram showing an example of athlete heat maps. FIG. 12 shows athlete heat maps 81, 82, and 83 30 minutes, 1 hour, and 1 hour and 30 minutes after the starting gun time "00:08:30" of the XXth XX Marathon. As shown in FIG. 12, the athlete heat maps 81, 82, and 83 can present the distribution of athletes on the course map in real time according to the time elapsed from the starting gun time. This can support the acquisition of cheering scores. For example, it is possible to provide a game-like feature in which an efficient cheering plan is made to raise the ranking of the cheering score. After the running competition is over, the athlete heat maps from start to finish can also be played back using the replay mode function described above.

[0083] As another aspect, the display control unit 15E can display a heat map in which the position information of each user is plotted on the course map. Hereinafter, the heat map in which the position information of the user is plotted may be referred to as a "supporter heat map". For example, the display control unit 15E plots sections corresponding to the position information of each user among sections included in the course map. At this time, the display control unit 15E can distinguish the appearance form of the section according to the number of plotted users. For example, the fill or hatching of the section can be set to be darker as the number of plotted users increases. Also, the fill or hatching of the section can be set to be lighter as the number of plotted users decreases. Displaying such a supporter heat map can help avoid congestion and discover hidden spots with relatively few supporters. Note that the supporter heat map can plot the position information of users at any time from the start to the end of the running event. The player heat map and / or supporter heat map make it easy to grasp the level of congestion, so by providing the player heat map and / or supporter heat map to tournament organizers, it is expected that the tournament will be run smoothly, such as by considering whether and when traffic restrictions are necessary and providing information on congested areas.

[0084] The granting unit 15F is a processing unit that grants a benefit to a user according to the user's cheering score. In one embodiment, the granting unit 15F grants a higher benefit as the user's cheering score increases. Also, the granting unit 15F grants a lower benefit as the user's cheering score decreases. Here, the benefit granted to the user may be a tangible object such as an item or an intangible object such as a digital coupon. By distributing such a benefit, an incentive can be given to the user to obtain a cheering score. As a result, it is possible to improve the user's motivation to cheer.

[0085] 4 shows an example in which the server device 10 has the display control unit 15E and the attachment unit 15F, but the server device 10 does not necessarily have to have both the display control unit 15E and the attachment unit 15F. For example, the server device 10 may have a functional configuration having only one of the display control unit 15E and the attachment unit 15F.

[0086] <Processing flow> Next, a process flow of the server device 10 according to an embodiment of the present disclosure will be described. Here, (1) a process for acquiring measurement data executed by the server device 10 will be described, and then (2) a process for calculating a cheering score will be described.

[0087] (1) Measurement data acquisition and processing 13 is a flowchart showing the procedure of the measurement data acquisition process. As an example, this process is started when the measurement data is acquired by the first acquisition unit 15A. As shown in FIG. 13, the first acquisition unit 15A acquires the measurement data including a point ID, a runner ID, and a timestamp from the measurement device 30 (step S101).

[0088] Next, the prediction unit 15B predicts the arrival time at an unreached point subsequent to the measurement point corresponding to the point ID included in the measurement data acquired in step S101 (step S102).

[0089] Then, the prediction unit 15B registers the arrival time of the measurement point acquired in step S101 and the arrival time of the unreached point predicted in step S102 in the arrival time DB 13A (step S103).

[0090] Thereafter, the prediction unit 15B executes loop process 1, which repeats the process of step S104 described below a number of times corresponding to the number K of unreached points. Furthermore, the prediction unit 15B executes loop process 2, which repeats the process of step S104 described below a number of times corresponding to the number M of sections belonging to the unreached section that includes the k-th unreached point as its end point.

[0091] That is, the prediction unit 15B predicts the passing time period when the athlete with the runner ID whose measurement data was acquired in step S101 will pass through the mth section out of M sections belonging to the unreached section whose end point is the kth unreached point, and registers the predicted position DB 13B (step S104).

[0092] By repeating such loop process 2, the passing time zones of M sections belonging to the unreached section that has the kth unreached point as its end point are registered in the predicted position DB 13B. Furthermore, by repeating loop process 1, the passing time zones of M sections are registered in the predicted position DB 13B for K unreached points.

[0093] Although FIG. 13 shows an example in which the process of step S104 is repeated, the process of step S104 can also be executed in parallel for each of K unreached points and each of M sections. Loop process 1 and loop process 2 do not necessarily have to be executed. That is, it is not necessarily required to calculate the passing time periods of all unreached points, and for example, only the passing time periods of arbitrary unreached points may be calculated. Specifically, for example, the passing time periods of only the sections adjacent to the measurement point for which the arrival time was obtained in step S101 may be calculated. Reducing or eliminating loop processes reduces the amount of calculation in the server device, which is expected to reduce redundant calculation resources and storage space and improve the response speed of services.

[0094] (2) Calculation of cheering score 14 is a flowchart showing the procedure of the calculation process of the cheering score. This process is started, for example, when the second acquisition unit 15C acquires the position information of the user U at time t.

[0095] As shown in FIG. 14, the second acquisition unit 15C acquires location information of the user U at time t from the user terminal 50 (step S301).

[0096] Next, the calculation unit 15D determines whether the watching mode of the user U is set to the manual mode (step S302). At this time, if the watching mode of the user U is set to the manual mode (step S302 Yes), the calculation unit 15D determines whether the action of shaking the user terminal 50 is detected when measuring the position information of the user U (step S303).

[0097] If the watching mode of the user U is set to the auto mode (No in step S302), or if the action of shaking the user terminal 50 is detected (Yes in step S303), the count-up of the cheering score is enabled.

[0098] In this case, the calculation unit 15D identifies, from among the sections into which the course map is divided, a spectating section that corresponds to the position information of the user U (step S304). Then, the calculation unit 15D counts, from among the runners participating in the running race, the number of runners whose predicted arrival positions at the time t when the position information of the user U is acquired are included in the spectating section identified in step S304 (step S305).

[0099] After that, the calculation unit 15D executes loop process 1 in which the processes from step S306 to step S309 described below are repeated a number of times corresponding to the number N of players located in the spectating section of the user U. Note that, although an example in which the processes from step S306 to step S309 described below are repeated is given here, the processes from step S306 to step S309 described below can also be executed in parallel for each of the N players.

[0100] That is, the calculation unit 15D assigns a weight corresponding to the popularity of the n-th player (step S306). Furthermore, the calculation unit 15D assigns a weight corresponding to the congestion degree of the spectator section of the user U (step S307). Furthermore, the calculation unit 15D assigns a weight corresponding to the relevance to sponsors in the spectator section of the user U (step S308).

[0101] Then, the calculation unit 15D calculates the additional points of the nth player by adding the sum of the popularity weight assigned in step S306, the congestion weight assigned in step S307, and the sponsor relevance weight assigned in step S308 to the player's basic points (step S309).

[0102] By repeating this loop process 1, the added points are calculated for each of the N players.

[0103] After that, the calculation unit 15D calculates the cheering score of the user U at time t by tallying up the added points of the N players located in the spectating section identified in step S304 (step S310).

[0104] Then, the calculation unit 15D cumulatively adds the support score of the user U at time t to the cumulative support score accumulated up to time t, thereby calculating the latest cumulative support score of the user U (step S311).

[0105] Then, the display control unit 15E updates the display of the support score on the user terminal 50 of the user U to the latest value of the accumulated support score of the user U calculated in step S311 (step S312), and ends the process.

[0106] <One aspect of the effect> As described above, the server device 10 according to the first aspect has a first acquisition unit that acquires measurement data that measures or predicts the time when each runner moving along the course on which the race is to arrive at a measurement point on the course, a second acquisition unit that acquires the user's location information, and a calculation unit that calculates a cheering score that evaluates the degree of cheering by the user based on the number of runners whose predicted arrival positions, as predicted from the measurement data, are within a predetermined range from the user's location information. As a result, as one aspect, an environment can be created in which cheering for other runners is more highly evaluated than wasting free time, such as waiting time until family and friends arrive at the user's location, by operating the user terminal 50, etc. Therefore, the server device 10 according to the first aspect can improve the user's motivation to watch a race that is not being watched. Such an improvement in the spectator motivation can improve the excitement of a race or other competition. In turn, it can also lead to the creation of a sense of unity among spectators.

[0107] The server device 10 according to the second aspect may count the number of players whose predicted arrival positions are included in the section corresponding to the user's position information among sections into which a map including a part of the course is divided. This allows matching between the user and the player by matching the sections between them. Therefore, the accuracy of counting the number of players between users located in the same section is stable. Therefore, the server device 10 according to the second aspect can realize a fair calculation of the cheering score between users.

[0108] The server device 10 according to the third aspect may calculate the cheering score based on the weighting given according to the section corresponding to the user's position information. This makes it possible to differentiate the cheering scores calculated between sections. Therefore, the server device 10 according to the third aspect can provide a game-like element to the acquisition of the cheering score.

[0109] The server device 10 according to the fourth aspect may calculate the cheering score based on a weighting that corresponds to the congestion level of a section that corresponds to the user's location information. For example, a cheering score that is weighted more heavily as the congestion level of a spectator section decreases can be calculated. Therefore, the server device 10 according to the fourth aspect can realize a calculation logic that guides the user to a section that is relatively less crowded.

[0110] The server device 10 according to the fifth aspect may calculate the cheering score based on a weighting that corresponds to the degree of association of the race in the section corresponding to the user's location information with the sponsor. For example, the cheering score can be calculated with a higher weighting as the degree of association of the spectator section with the sponsor increases. Therefore, the server device 10 according to the fifth aspect can realize a calculation logic that guides the user to the sponsor's associated stores, etc.

[0111] The server device 10 according to the sixth aspect may calculate the cheering score based on the weighting given to the player whose predicted arrival position is included in the section corresponding to the user's position information. This makes it possible to differentiate the cheering scores calculated between the players. Therefore, the server device 10 according to the sixth aspect can provide a game-like element to the acquisition of the cheering score.

[0112] The server device 10 according to the seventh aspect may calculate the cheering score based on a weighting corresponding to the popularity of a player that is assigned to a player whose predicted arrival position is included in the section corresponding to the user's position information. For example, a cheering score can be calculated in which a larger weighting is assigned as the popularity of a player increases. Therefore, the server device 10 according to the seventh aspect can realize a calculation logic that provides an incentive to watch a famous player.

[0113] The server device 10 according to the eighth aspect may acquire location information measured by the user terminal 50 while the action of shaking the user terminal 50 is detected. This can improve the motivation of the user to perform the cheering action. Therefore, the server device 10 according to the eighth aspect can support the excitement of cheering at the site of a running event.

[0114] The server device 10 according to the ninth aspect may display the cheering score of the user on the user terminal 50. Therefore, according to the server device 10 according to the ninth aspect, it is possible to realize the presentation of the cheering score to the user.

[0115] The server device 10 according to the tenth aspect may display the cheering scores calculated for each user in a ranking format. This can encourage a competitive spirit in obtaining the cheering scores. Therefore, the server device 10 according to the tenth aspect can improve the excitement of the running event.

[0116] The server device 10 according to the eleventh aspect may display a heat map on a map including a part of the course, in which the predicted arrival positions correspond to the number of moving objects. Therefore, the server device 10 according to the eleventh aspect can support the acquisition of the cheering score.

[0117] The server device 10 according to the 12th aspect may display a heat map on a map including a part of the course, the location information of which corresponds to the number of users. Therefore, the server device 10 according to the 12th aspect can help avoid crowding and find little-known spots with relatively few supporters.

[0118] The server device 10 according to the thirteenth aspect may provide a benefit to the user according to the cheering score of the user. This makes it possible to provide an incentive for the acquisition of the cheering score. Therefore, the server device 10 according to the thirteenth aspect can improve the user's motivation to cheer.

[0119] <Other embodiments> Although the embodiments of the present disclosure have been described above, various applications are possible, and further, the present disclosure may be embodied in various different forms other than the above-described embodiments.

[0120] <Cheering Score> In the above embodiment, an example has been shown in which a cheering score is calculated and displayed for each user U, but for example, cheering scores may be added up for multiple users U (hereinafter also referred to as "teams"). By competing over the cheering scores added up for each team, motivation for watching (cheering) can be increased more effectively. The cheering scores may be added up for each specific race, or for multiple races held during a specific period.

[0121] When comparing cheer scores, the total cheer scores of multiple users U included in a team may be used, the average cheer scores of the multiple users U may be used, or the cheer scores of the multiple users U that are ranked a certain level or higher may be used.

[0122] The composition of the teams competing for the cheering score is not particularly limited, but for example, categories may be set based on the number of team participants or categories based on team attributes (such as by company, local government, or industry), and the cheering score may be competed within those categories.

[0123] <Numbers, etc.> The matters described in the above embodiment, such as the number of measurement devices 30, the number of user terminals 50, and specific examples of weighting used in calculating the watching score, are merely examples and may be changed. In addition, the order of processing in the flowcharts described in the embodiment may be changed within a range that does not cause inconsistencies.

[0124] <System> The information including the processing procedures, control procedures, specific names, various data, and parameters shown in the above documents and drawings can be changed arbitrarily unless otherwise specified. For example, any one or more of the functional units of the first acquisition unit 15A, the prediction unit 15B, the second acquisition unit 15C, the calculation unit 15D, the display control unit 15E, and the attachment unit 15F of the server device 10 may be configured as separate devices.

[0125] 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. In other words, all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc. Each configuration may be a physical configuration.

[0126] Furthermore, each processing function performed by each device may be realized, in whole or in part, by a CPU (Central Processing Unit) and a program analyzed and executed by the CPU, or may be realized as hardware using wired logic.

[0127] <Hardware> Next, a hardware configuration example of the computer described in the above embodiment will be described. Fig. 15 is a diagram showing a hardware configuration example. As shown in Fig. 15, the information processing device 10 has a communication device 10a, a storage device 10b, a memory 10c, and a processor 100d. Note that each unit shown in Fig. 15 may be connected to each other via a bus or the like.

[0128] The communication device 100a is a network interface card, etc. The storage device 10b is a storage device such as a hard disk drive (HDD) or a solid state drive (SSD). For example, the storage device 10b stores a program or DB that operates the functions shown in FIG. 13 or FIG. 14.

[0129] The processor 10d reads out a program for executing the same processes as those of the processing units shown in FIG. 4 from the storage device 10b etc. and loads the program in the memory 10c, thereby operating the process for executing the functions described in FIG.

[0130] Such a process realizes the same functions as the processing unit of the server device 10. For example, the processor 10d reads out a program having the same functions as the first acquisition unit 15A, the prediction unit 15B, the second acquisition unit 15C, the calculation unit 15D, the display control unit 15E, the assignment unit 15F, etc. from the storage device 10b, etc. Then, the processor 10d executes a process that executes the same processing as the first acquisition unit 15A, the prediction unit 15B, the second acquisition unit 15C, the calculation unit 15D, the display control unit 15E, the assignment unit 15F, etc.

[0131] In this way, the information processing device 10 operates as an information processing device that executes a calculation method by reading and executing a program. The information processing device 10 can also realize functions similar to those of the above-mentioned embodiment by reading the program from a recording medium using a medium reading device and executing the read program. Note that the program in this other embodiment is not limited to being executed by the information processing device 10. For example, various functions of the present disclosure can be similarly applied to cases where another computer or server executes a program, or where these execute a program in cooperation with each other.

[0132] The above program can be distributed via a network such as the Internet. The above program can be recorded on any recording medium and executed by a computer by reading it from the recording medium. For example, the recording medium can be a hard disk, a flexible disk (FD), a CD-ROM, a magneto-optical disk (MO), a digital versatile disk (DVD), or the like.

[0133] The disclosed embodiments should be considered to be illustrative and not restrictive in all respects. Indeed, the above-described embodiments may be embodied in various forms. Furthermore, the above-described embodiments may be omitted, substituted, or modified in various forms without departing from the scope and spirit of the appended claims. [Explanation of symbols]

[0134] 1 Spectator Support System 10. Server device 11 Communication control section 13 Storage section 13A Arrival Time DB 13B Predicted position DB 13C Spectator Score DB 15 Control section 15A First Acquisition Section 15B Prediction Section 15C Second Acquisition Section 15D Calculation section 15E Display control unit 15F Granting Department 30 Measuring Equipment 50 User terminals

Claims

1. a first acquisition unit that acquires measurement data for each moving object moving on a course along which a race is to be run, the measurement data measuring or predicting a time at which the moving object will arrive at a measurement point on the course; A second acquisition unit that acquires location information of a user; a calculation unit that calculates a watching score that evaluates a level of watching by the user based on the number of moving objects whose predicted arrival positions, which are predicted from the measurement data, are within a predetermined range from the position information of the user; and An information processing device having the above configuration.

2. The information processing device according to claim 1 , wherein the calculation unit counts the number of moving objects whose predicted arrival positions are included in a section corresponding to the user's position information among sections into which a map including part of the course is divided.

3. The information processing device according to claim 2 , wherein the calculation unit calculates the watching score based on a weighting assigned in accordance with a section corresponding to the position information of the user.

4. The information processing device according to claim 3 , wherein the calculation unit calculates the watching score based on a weighting that corresponds to a congestion degree of a section that is assigned to the section that corresponds to the position information of the user.

5. The information processing device according to claim 3 , wherein the calculation unit calculates the watching score based on a weighting assigned to a section corresponding to the user's position information, the weighting corresponding to a degree of relevance to a sponsor of the race in the section.

6. The information processing device according to claim 2 , wherein the calculation unit calculates the watching score based on a weighting given to a moving object whose predicted arrival position is included in a section corresponding to the user's position information.

7. The information processing device according to claim 6 , wherein the calculation unit calculates the watching score based on a weighting corresponding to a popularity of a moving object that is assigned to a moving object whose predicted arrival position is included in a section corresponding to the user's position information.

8. The information processing apparatus according to claim 1 , wherein the second acquisition unit acquires position information measured by the terminal device while a motion of shaking the terminal device by the user is detected.

9. 9. The information processing device according to claim 1, further comprising a display control unit that displays the user's watching score on the terminal device of the user.

10. The information processing device according to claim 9 , wherein the display control unit displays the watching scores calculated for each user in a ranking format.

11. The information processing device according to claim 9 , wherein the display control unit displays a heat map on a map including a part of the course, the heat map being determined so that the predicted arrival positions correspond to the number of the moving objects.

12. The information processing device according to claim 9 , wherein the display control unit displays a heat map on a map including a part of the course, the heat map being displayed with the position information corresponding to the number of the users.

13. 9. The information processing device according to claim 1, further comprising an awarding unit that awards a benefit to the user according to the user's watching score.

14. acquiring measurement data for each moving object moving along a course along which a race is to be run, the measurement data measuring or predicting the time at which the moving object will arrive at a measurement point on the course; Obtain the user's location information, calculating a watching score for evaluating a degree of watching by the user based on the number of moving objects whose predicted arrival positions, which are predicted from the measurement data, are within a predetermined range from the position information of the user; A calculation method in which processing is carried out by a computer.

15. acquiring measurement data for each moving object moving along a course along which a race is to be run, the measurement data measuring or predicting the time at which the moving object will arrive at a measurement point on the course; Obtain the user's location information, calculating a watching score for evaluating a degree of watching by the user based on the number of moving objects whose predicted arrival positions, which are predicted from the measurement data, are within a predetermined range from the position information of the user; A calculation program that causes a computer to execute processing.

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