Demand prediction system, demand prediction method, and program

Abstract

To provide a demand prediction system, a demand prediction method, and a program for reducing a processing load when predicting demands in a plurality of areas.SOLUTION: A demand prediction system includes monitoring means that monitors a usage status of wireless communication, detection means that detects an area in which wireless communication is frequently used among a plurality of areas in each of which a camera is disposed, determination means that performs image analysis on a video acquired from the camera disposed in the detected area and determines whether or not a predetermined situation occurs in the area, and prediction means that predicts a demand according to a determination result of whether or not the predetermined situation occurs.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a demand forecasting system, a demand forecasting method, and a program. [Background technology]

[0002] Patent Document 1 discloses a taxi dispatch system that grasps the distribution status of taxi users. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2013-130906 Summary of the Invention [Problem to be solved by the invention]

[0004] When forecasting demand by analyzing images of multiple areas, there is a problem in that the processing load of image analysis is large.

[0005] The present disclosure has been made to solve such problems, and aims to provide a demand forecasting system, a demand forecasting method, and a program that reduce the processing load when predicting demand in multiple areas. [Means for solving the problem]

[0006] The demand forecasting system according to the present disclosure includes: a monitoring means for monitoring the usage status of wireless communication; a detection means for detecting an area where wireless communication is frequently used among a plurality of areas in which cameras are installed; a determination means for performing image analysis on an image acquired from a camera disposed in the detected area and determining whether a predetermined situation is occurring in the area; a prediction means for predicting demand according to a determination result as to whether or not the predetermined situation has occurred; Equipped with.

[0007] The demand forecasting method according to the present disclosure includes: Monitor wireless communication usage, Among multiple areas where cameras are installed, the system detects areas with high wireless communication usage, performing image analysis on images acquired from cameras arranged in the detected area to determine whether a predetermined situation has occurred in the area; Demand is predicted according to the result of determining whether or not the predetermined situation has occurred.

[0008] The program according to the present disclosure is a process for monitoring wireless communication usage; A process of detecting areas with high wireless communication usage among multiple areas where cameras are installed; a process of performing image analysis on video captured by a camera disposed in the detected area and determining whether a predetermined situation is occurring in the area; a process of predicting demand according to a result of determining whether or not the predetermined situation has occurred; to be executed by the computer. [Effects of the Invention]

[0009] According to the present disclosure, it is possible to provide a demand forecasting system, a demand forecasting method, and a program that reduce the processing load when forecasting demand in multiple areas. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a block diagram illustrating an example of the configuration of a demand forecasting system according to the present disclosure. [Figure 2] 1 is a flowchart illustrating an example of the flow of a demand forecasting method according to the present disclosure. [Figure 3] 1 is a block diagram illustrating an example of the configuration of a demand forecasting system according to the present disclosure. [Figure 4]1 is a flowchart illustrating an example of the flow of a demand forecasting method according to the present disclosure. [Figure 5] FIG. 1 is a block diagram illustrating an example of a hardware configuration of a demand forecasting system according to the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0011] Embodiment 1 Hereinafter, a first embodiment will be described with reference to the drawings. FIG. 1 is a block diagram showing the configuration of a demand forecasting system 1 according to the present disclosure. The demand forecasting system 1 may be a computer device operated by a processor executing a program stored in a memory. The demand forecasting system 1 may be an information processing device, for example, a server device. The demand forecasting system 1 may also be composed of multiple computer devices. In this case, the components or functions constituting the demand forecasting system 1 may be distributed and arranged among the multiple computer devices. The multiple computers may be connected via a network or directly via a cable or the like.

[0012] The demand forecasting system 1 includes a monitoring unit 11, a detection unit 12, a determination unit 13, and a prediction unit 14. The monitoring unit 11, the detection unit 12, the determination unit 13, and the prediction unit 14 may be software or modules that are executed by a processor executing a program stored in a memory. Alternatively, the monitoring unit 11, the detection unit 12, the determination unit 13, and the prediction unit 14 may be hardware such as a circuit or a chip.

[0013] The monitoring unit 11, the detection unit 12, the determination unit 13, and the prediction unit 14 may be provided in a single physical device. Although the drawings below illustrate an example in which the units are provided in a single physical device, the functional units may be distributed and arranged in multiple physical devices. For example, these functions may be implemented by communication between a device including the monitoring unit 11 and the detection unit 12 and a device including the determination unit 13 and the prediction unit 14.

[0014] The monitoring unit 11 monitors the usage status of wireless communication. Monitoring means repeatedly collecting information (e.g., communication volume) that indicates the usage status of wireless communication. Specifically, the monitoring unit 11 repeatedly collects information that indicates the usage status of wireless communication and determines whether the usage of wireless communication has increased.

[0015] The detection unit 12 detects an area where wireless communication is used frequently from among the multiple areas. Specifically, the detection unit 12 detects an area where wireless communication is used frequently in response to determining that the use of wireless communication has increased.

[0016] The determination unit 13 performs image analysis on the video captured by the camera placed in the area detected by the detection unit 12, and determines whether or not a predetermined situation is occurring in the area.

[0017] The prediction unit 14 predicts the demand according to the determination result as to whether or not the above-mentioned predetermined situation occurs.

[0018] 2 is a flowchart showing an example of the flow of the demand prediction method according to the present disclosure. First, the monitoring unit 11 monitors the usage status of wireless communication (step S11). Next, the detection unit 12 detects an area where wireless communication is frequently used (step S12). Next, the determination unit 13 performs image analysis on video acquired from a camera placed in the detected area, and determines whether a predetermined situation has occurred in the area (step S13). Next, the prediction unit 14 predicts demand according to the determination result of whether the predetermined situation has occurred (step S14).

[0019] As described above, the demand forecasting system 1 performs image analysis on video from cameras placed in areas where wireless communication usage is high. As a result, the demand forecasting system 1 can reduce the processing load when predicting demand in multiple areas. In other words, analyzing video from all areas imposes a processing load, but the demand forecasting system 1 analyzes video from areas where wireless communication usage is high, so the processing load is reduced compared to the processing load when analyzing video from all areas. Furthermore, the demand forecasting system 1 can improve the accuracy of demand forecasts by monitoring the usage status of wireless communication and analyzing video.

[0020] Embodiment 2 3 is a block diagram showing an example of the configuration of a demand forecasting system 10 according to the present disclosure. Embodiment 2 is a specific example of Embodiment 1. The demand forecasting system 10 is a specific example of the demand forecasting system 1. It is also possible to interpret the server 3 as a specific example of the demand forecasting system 1.

[0021] The demand forecasting system 10 includes a plurality of cameras 2 and a server 3. The cameras 2 and the server 3 are connected to each other so that they can communicate with each other via a network N. The network N may be, for example, a communication network such as the Internet, an intranet, a mobile phone network, or a LAN (Local Area Network). The network N may be wired or wireless.

[0022] One or more cameras 2 are placed in each area. The cameras 2 may be attached to traffic lights and capture images of people passing by on the road. In this case, the cameras 2 may be communicably connected to a base station installed at the traffic light or a base station installed near the traffic light. The cameras 2 may be installed, for example, near the ticket gates of a station, inside the station, or at a ticket counter. The cameras 2 may be cameras that capture images, such as visible light cameras, or cameras that capture temperature, such as thermal cameras. The type of camera 2 is not important as long as it can determine the status of people passing by.

[0023] The demand forecasting system 10 may also include multiple radio wave sensors. One or more radio wave sensors are placed in each area. The radio wave sensor may include, for example, an antenna, a filter that extracts only radio waves of a desired frequency from the radio waves received by the antenna, and a transmitter that transmits information indicating the intensity of the received radio waves to the server 3.

[0024] The monitoring of the usage status of wireless communication can be performed based on various information other than the sensing result of the radio wave sensor. For example, the monitoring of the usage status of wireless communication may be performed based on the number of communication terminals or the communication volume.

[0025] The server 3 may be a computer device that operates when a processor executes a program stored in memory. The server 3 includes a monitoring unit 31, a detecting unit 32, an acquiring unit 33, a determining unit 34, a predicting unit 35, and a notifying unit 36. Each of the components that make up the server 3 may be software or a module that performs processing when the processor executes a program stored in memory. Alternatively, each of the components that make up the server 3 may be hardware such as a circuit or a chip.

[0026] The monitoring unit 31 is a specific example of the monitoring unit 11. The monitoring unit 31 monitors the usage status of wireless communication. The monitoring unit 31 may monitor, for example, the number of communication terminals in each area, the communication volume, and the usage status of radio waves in the communication frequency band. The usage status of radio waves may be represented by the strength of radio waves. The number of communication terminals may be the number of communication terminals connected to the network N. The number of communication terminals connected to the network N is, for example, the number of communication terminals connected to a base station located in the above area. The communication volume may be the communication volume at the above base station. The communication volume may be the number of outgoing calls. The monitoring unit 31 may further monitor the movement of people in each area. The monitoring unit 31 can monitor the movement of people based on GPS (Global Positioning System) information collected from the communication terminals, etc.

[0027] The detection unit 32 is a specific example of the above-mentioned detection unit 12. The detection unit 32 detects an area among multiple areas where wireless communication is used frequently, based on the monitoring results of the monitoring unit 31. When a person located in a certain area wants to check information or send information, it is thought that the use of wireless communication in that area will increase.

[0028] An area where wireless communication usage is high may be, for example, an area where the amount of wireless communication usage is greater than a predetermined value, or an area where the increase in the amount of wireless communication usage is greater than a predetermined value. Furthermore, an area where wireless communication usage is high may be an area where wireless communication usage is high for a certain period of time or more. If there are many people who cannot move from a certain area, it is considered that the amount of wireless communication usage will continue to be high. Furthermore, the detection unit 32 may detect an area where wireless communication usage is high and where there are many people standing still. If there are many people standing still due to precipitation, there is a high possibility that demand, such as demand for rides, will increase.

[0029] The acquisition unit 33 acquires information about the area detected by the detection unit 32. The information about the area may include, for example, at least one of information about the weather around the area (e.g., a station next to a station located in the area), information about events taking place around the area, and information about train operations that pass through the area.

[0030] The determination unit 34 is a specific example of the determination unit 13. The determination unit 34 acquires video from a camera placed in the area detected by the detection unit 32. The determination unit 34 then performs image analysis on the video to determine whether a predetermined situation has occurred in the area. The predetermined situation may be a situation in which demand (e.g., demand for taxi rides) increases. The demand may be other demands such as demand for delivery of goods, and is not limited to demand for taxi rides. The predetermined situation may also be a situation in which precipitation is occurring.

[0031] For example, the determination unit 34 may determine whether precipitation is occurring and many people do not have rain gear (e.g., umbrellas, raincoats, boots). Precipitation refers to the phenomenon of falling water droplets such as rain, snow, and hail. The determination of whether precipitation is occurring may be made, for example, by analyzing video captured by a visible light camera or a thermal camera to determine whether a road or the like is wet. The above determination may also be made by determining whether the temperature of a predetermined object (e.g., an umbrella) captured by a thermal camera is low.

[0032] The determination unit 34 may determine whether or not a situation has occurred in which many people are carrying large baggage. The determination unit 34 may determine whether or not a situation has occurred in which many people are standing still.

[0033] The prediction unit 35 is a specific example of the prediction unit 14. The prediction unit 35 predicts demand according to the determination result of the determination unit 34. For example, when the determination unit 34 determines that a predetermined situation has occurred, the prediction unit 35 may predict a high demand. The high demand may be a demand higher than a predetermined value.

[0034] The prediction unit 35 may predict demand further based on the information about the area acquired by the acquisition unit 33. For example, when the information about the area indicates an event that will lead to an increase in demand and the determination unit 34 determines that a predetermined situation has occurred, the prediction unit 35 may predict a high demand.

[0035] For example, weather around an area with precipitation may lead to increased demand in that area. For example, an event being held around an area may lead to increased demand in that area. For example, a temporary suspension of train service through the area may lead to increased demand in that area.

[0036] The prediction unit 35 can improve the accuracy of demand prediction by using information about the area. Furthermore, by using information about the area, it is also possible to reduce the load of image analysis. For example, when the information about the area indicates that the weather around the area is accompanied by precipitation and the determination unit 34 determines that there is a situation where many people do not carry rain gear (e.g., umbrellas), the prediction unit 35 may predict high demand. In this case, there is no need to determine the weather by image processing, and the load of image analysis is reduced.

[0037] The demand predicted by the prediction unit 35 is not limited to demand for taxi rides, but may also be demand for delivery of goods. The determination unit 34 determines whether or not precipitation is occurring. It is known that when precipitation occurs, demand for delivery of goods such as food and drink increases.

[0038] The notification unit 36 ​​notifies taxis of the ride demand predicted by the prediction unit 35. Specifically, the notification unit 36 ​​transmits the predicted ride demand to a communication terminal installed in the taxi. The notification unit 36 ​​may notify taxis of information indicating areas where ride demand is higher than a predetermined value. Note that, when demand other than ride demand (e.g., delivery demand) is predicted, the notification unit 36 ​​may notify businesses related to that demand (e.g., delivery personnel). When delivery demand is predicted, the notification unit 36 ​​may notify delivery vehicles or electronic devices (e.g., communication terminals carried by delivery personnel) used by delivery companies including transportation companies, retailers, etc. The notification unit 36 ​​may notify delivery vehicles or electronic devices of information indicating areas where delivery demand is high.

[0039] 4 is a flowchart showing an example of the flow of the demand forecasting method according to the present disclosure. First, the monitoring unit 31 of the server 3 monitors the usage status of wireless communication (step S21). The monitoring unit 31 may monitor, for example, the communication volume in each area and the number of terminals present in each area.

[0040] Next, the detection unit 32 of the server 3 detects an area where wireless communication is used frequently (step S22). The detection unit 32 may detect an area where the use of wireless communication has suddenly increased, for example.

[0041] Next, the acquisition unit 33 of the server 3 acquires information about the detected area (step S23). Note that the order of steps S23 and S24 may be reversed.

[0042] Next, the determination unit 34 of the server 3 acquires an image from a camera placed in the detected area, analyzes the acquired image, and determines whether a predetermined situation has occurred in the area (step S24).

[0043] Next, the prediction unit 35 of the server 3 predicts demand based on the information about the area and the determination result by the determination unit 34 (step S35). The notification unit 36 ​​of the server 3 may notify taxis of the predicted demand for rides.

[0044] At least some of the functions of the server 3 may be executed on the camera 2 side. That is, a processor, storage device, and memory may be stored inside the camera 2, and all or some of the processing of each means of the server 3 may be executed by these components. For example, the processing of the acquisition unit 33 and the determination unit 34 may be executed on the camera 2 side.

[0045] Like the demand forecasting system 1, the demand forecasting system 10 can also reduce the processing load when forecasting demand in multiple areas.

[0046] FIG. 5 is a block diagram showing an example of the hardware configuration of a demand forecasting system 1 and a server 3 (hereinafter referred to as the demand forecasting system 1, etc.). Referring to FIG. 5, the demand forecasting system 1, etc. includes a network interface 1001, a processor 1002, and a memory 1003. The network interface 1001 is used to communicate with other network node devices constituting a communication system. The network interface 1001 may be used for wireless communication. For example, the network interface 1001 may be used for wireless LAN communication defined in the IEEE 802.11 series or mobile communication defined in 3GPP (3rd Generation Partnership Project). Alternatively, the network interface 1001 may include a network interface card (NIC) conforming to the IEEE 802.3 series.

[0047] The processor 1002 reads and executes software (computer programs) from the memory 1003 to perform the processes of steps S11 to S14 in Fig. 2 and steps S21 to S25 in Fig. 4. The processor 1002 may be, for example, a microprocessor, an MPU, or a CPU. The processor 1002 may include multiple processors.

[0048] The memory 1003 is configured by a combination of volatile memory and non-volatile memory. The memory 1003 may include storage located remotely from the processor 1002. In this case, the processor 1002 may access the memory 1003 via an I / O (Input / Output) interface (not shown).

[0049] 5, the memory 1003 is used to store a group of software modules. The processor 1002 can perform the processes of steps S11 to S14 and steps S21 to S25 by reading and executing the group of software modules from the memory 1003.

[0050] As explained using Figure 5, each of the processors possessed by the demand forecasting system 1 in the above-mentioned embodiment executes one or more programs including a group of instructions for causing a computer to perform the algorithm explained using the drawings.

[0051] In the above examples, the program includes instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more functions described in the embodiments. The program may be stored on a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, computer-readable medium or tangible storage medium includes random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technology, CD-ROM, digital versatile disc (DVD), Blu-ray® disc or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may also be transmitted on a transitory computer-readable medium or communication medium. By way of example and not limitation, transitory computer-readable medium or communication medium includes electrical, optical, acoustic, or other forms of propagated signals.

[0052] The technical ideas of the present disclosure are not limited to the above-described embodiments, and can be modified as appropriate within the scope of the invention.

[0053] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0054] Each drawing is merely an example for describing one or more embodiments. Each drawing may relate not only to one particular embodiment, but also to one or more other embodiments. As will be understood by those skilled in the art, various features or steps described with reference to any one drawing can be combined with features or steps shown in one or more other drawings to create, for example, an embodiment not explicitly shown or described. Not all features or steps shown in any one drawing are necessary to describe an exemplary embodiment, and some features or steps may be omitted. The order of steps described in any drawing may be changed as appropriate.

[0055] A part or all of the above-described embodiments can be described as, but not limited to, the following supplementary notes.

[0056] Some or all of the elements (e.g., configurations and functions) described in Supplementary Notes 2 to 8 that are dependent on Supplementary Note 1 may also be dependent on Supplementary Notes 9 and 10 in the same dependency relationship as Supplementary Notes 2 to 8. Some or all of the elements described in any Supplementary Note may be applied to various hardware, software, recording means for recording software, systems, and methods.

[0057] (Appendix 1) a monitoring means for monitoring the usage status of wireless communication; a detection means for detecting an area where wireless communication is frequently used among a plurality of areas in which cameras are installed; a determination means for performing image analysis on an image acquired from a camera disposed in the detected area and determining whether a predetermined situation is occurring in the area; a prediction means for predicting demand according to a determination result as to whether or not the predetermined situation has occurred; A demand forecasting system equipped with: (Appendix 2) further comprising an acquisition means for acquiring information about the detected area; The prediction means predicts the demand further depending on information about the area. Demand forecasting system according to claim 1. (Appendix 3) The prediction means predicts demand for taxi rides. 3. The demand forecasting system of claim 1 or 2. (Appendix 4) The prediction means predicts delivery demand, The system further includes a notification means for notifying the delivery vehicle or an electronic device used by the delivery company of the predicted delivery demand. 3. The demand forecasting system of claim 1 or 2. (Appendix 5) The prediction means predicts the demand to be high when it is determined that the predetermined situation has occurred and the information about the area indicates an event that will lead to an increase in the demand. 4. The demand forecasting system of claim 2 or 3. (Appendix 6) The information about the area includes weather information about the area; The predetermined situation includes a situation where many people do not have rain gear. Demand forecasting system according to claim 5. (Appendix 7) The determination means determines the weather in the area by analyzing the image captured by the thermal camera, and determines whether the predetermined situation has occurred based on the weather. 3. The demand forecasting system of claim 1 or 2. (Appendix 8) The monitoring means monitors at least one of the number of communication terminals in each area, the amount of communication, and the usage status of radio waves in the communication frequency band. 3. The demand forecasting system of claim 1 or 2. (Appendix 9) Monitor wireless communication usage, Among multiple areas where cameras are installed, the system detects areas with high wireless communication usage, performing image analysis on images acquired from cameras arranged in the detected area to determine whether a predetermined situation has occurred in the area; Demand is predicted according to the result of determining whether the predetermined situation has occurred. Demand forecasting methods. (Appendix 10) a process for monitoring wireless communication usage; A process of detecting areas with high wireless communication usage among multiple areas where cameras are installed; a process of performing image analysis on video captured by a camera disposed in the detected area and determining whether a predetermined situation is occurring in the area; a process of predicting demand according to a result of determining whether or not the predetermined situation has occurred; A program that causes a computer to execute the following. [Explanation of symbols]

[0058] 1, 10 Demand forecasting system 11, 31 Monitoring Department 12, 32 Detector 13, 34 Judgment section 14, 35 Prediction Section 2 Cameras 33 Acquisition Department 36 Notification Department 1001 Network Interface 1002 processor 1003 memory N Network

Claims

1. a monitoring means for monitoring the usage status of wireless communication; a detection means for detecting an area where wireless communication is frequently used among a plurality of areas in which cameras are installed; a determination means for performing image analysis on an image acquired from a camera disposed in the detected area and determining whether a predetermined situation is occurring in the area; a prediction means for predicting demand according to a determination result as to whether or not the predetermined situation has occurred; A demand forecasting system equipped with:

2. further comprising an acquisition means for acquiring area information, which is information about the detected area; The prediction means predicts the demand further depending on information about the area. The demand forecasting system according to claim 1 .

3. The prediction means predicts demand for taxi rides. The demand forecasting system according to claim 1 or 2.

4. The prediction means predicts delivery demand, The system further includes a notification means for notifying the delivery vehicle or an electronic device used by the delivery company of the predicted delivery demand. The demand forecasting system according to claim 1 or 2.

5. The prediction means predicts the demand to be high when it is determined that the predetermined situation has occurred and the information about the area indicates an event that will lead to an increase in the demand. The demand forecasting system according to claim 2 .

6. The information about the area includes weather information about the area; The predetermined situation includes a situation where many people do not have rain gear. The demand forecasting system according to claim 5 .

7. The determining means determines the weather in the area by analyzing the image captured by the thermal camera, and determines whether the predetermined situation has occurred based on the weather. The demand forecasting system according to claim 1 or 2.

8. The monitoring means monitors at least one of the number of communication terminals in each area, the amount of communication, and the usage status of radio waves in the communication frequency band. The demand forecasting system according to claim 1 or 2.

9. Monitor wireless communication usage, Among multiple areas where cameras are installed, the system detects areas with high wireless communication usage, performing image analysis on video captured by a camera disposed in the detected area to determine whether a predetermined situation has occurred in the area; Demand is predicted according to the result of determining whether the predetermined situation has occurred. Demand forecasting methods.

10. a process for monitoring wireless communication usage; A process of detecting areas with high wireless communication usage among multiple areas where cameras are installed; a process of performing image analysis on video captured by a camera disposed in the detected area and determining whether a predetermined situation is occurring in the area; a process of predicting demand according to a result of determining whether the predetermined situation has occurred; A program that causes a computer to execute the following.

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