JP6910191B2 - Information processing equipment, systems and programs - Google Patents

Description

Embodiments of the present invention relate to information processing devices, systems and programs.

Conventionally, so-called in-car sales have been carried out in which products such as groceries are sold on trains such as trains. This in-vehicle sales is a sales method in which a sales person pushes a wagon loaded with products and moves through the aisle in the passenger vehicle while selling the products to passengers.

The person in charge travels around the passenger car and sells the products loaded on the wagon by a fixed route. The wagon is loaded with a wide variety of products to accommodate passengers of various attributes (age group, gender, etc.).

However, for example, if there are many passengers with a specific attribute tendency and a specific product sells more than expected, the product may be out of stock during the migration. In such a case, the person in charge needs to return to the office in the car where the out-of-stock product is stocked, which does not lead to improvement of sales and efficient sales.

An object to be solved by the present invention is to provide an information processing device, a system and a program capable of improving the sales amount and efficient sales in the in-vehicle sales.

The information processing apparatus of the embodiment, based on each vehicle of a vehicle in which a plurality of vehicles are connected to ride boasts a image taken, an attribute determining means for determining attributes tendency of the vehicle by a passenger, is determined and products predicting means for predicting a product sold in each vehicle based on the vehicle-basis attribute trends and demographic purchasing trend information, the vehicle-specific prediction information item predicted, the vehicle in which the image is transmitted It includes a predictive information transmitting means for transmitting to the provided information terminal device.

FIG. 1 is a schematic view showing a train in which a plurality of passenger cars are connected. FIG. 2 is a diagram showing a system according to an embodiment. FIG. 3 is a block diagram showing a hardware configuration of a handy terminal. FIG. 4 is a block diagram showing a hardware configuration of the POS server. FIG. 5 is a block diagram showing a hardware configuration of the seat server. FIG. 6 is a diagram showing a memory configuration of the seat DB. FIG. 7 is a block diagram showing the hardware configuration of the analysis server. FIG. 8 is a diagram showing a memory configuration of the analysis DB. FIG. 9 is a functional block diagram showing a functional configuration of the handy terminal. FIG. 10 is a flowchart showing the flow of control processing of the handy terminal. FIG. 11 is a flowchart showing the flow of control processing of the POS server. FIG. 12 is a flowchart showing the flow of control processing of the seat server. FIG. 13 is a functional block diagram showing a functional configuration of the analysis server. FIG. 14 is a flowchart showing the flow of control processing of the analysis server.

Hereinafter, the information processing apparatus, system, and program according to the embodiment will be described with reference to FIGS. 1 to 14. In the embodiment, the analysis server will be described as an example of the information processing device. Further, the handy terminal will be described as an example of the information terminal device. In addition, a train will be described as an example of a vehicle. Further, as an example of a vehicle, a train and a passenger car connected to the train will be described. The present invention is not limited to the embodiments described below.

FIG. 1 is a schematic diagram showing a train configuration. Train T is a train such as a train or a train that runs on rails. In the embodiment, as an example of the train T, a train in which six passenger cars (vehicles) from the first car T1 to the sixth car T6 are connected will be described. The passenger car of this train T is, for example, a reserved seat car in which the seats for the first car T1 and the second car T2 are predetermined. In addition, car No. 3 T3 and car No. 4 T4 are green cars (reserved seat cars) of special passenger cars. Further, the No. 5 car T5 and the No. 6 car T6 are unreserved seat cars in which the seats to be seated are not determined in advance. Reserved seats for cars 1 to 4 and T4 can be reserved in advance.

Cameras C are installed near the ceilings at both ends of each passenger car. The camera C11 is installed at one end of the first car T1, and the camera C12 is installed at the other end. The camera C21 is installed at one end of the second car T2, and the camera C22 is installed at the other end. The camera C31 is installed at one end of the No. 3 car T3, and the camera C32 is installed at the other end. A camera C41 is installed at one end of the No. 4 car T4, and a camera C42 is installed at the other end. The camera C51 is installed at one end of the No. 5 car T5, and the camera C52 is installed at the other end. The camera C61 is installed at one end of the No. 6 car T6, and the camera C62 is installed at the other end. These cameras are collectively referred to as camera C.

The camera C constantly captures the faces and clothes of the passengers in each passenger car. When the train T travels in the direction of the arrow Y1, the camera C11, the camera C21, the camera C31, the camera C41, the camera C51, and the camera C61 image the passengers in the passenger cars in which the respective cameras are installed. On the other hand, when the train T travels in the direction of arrow Y2, the camera C12, the camera C22, the camera C32, the camera C42, the camera C52, and the camera C62 image the passengers in the passenger cars in which the respective cameras are installed. do. It should be noted that all cameras C may simultaneously image the passengers of each train T. For example, the camera C11 and the camera C12 may simultaneously image the passengers on the No. 1 car T1. Further, instead of installing the cameras C at both ends of the passenger car, the inside of the passenger car may be imaged by an omnidirectional camera installed at the center of each passenger car. Further, the camera C may take an image of the inside of the passenger vehicle at predetermined time intervals (for example, once a minute). In short, it suffices if the camera C can capture an image to the extent that the attribute tendency of the passengers in the passenger car can be grasped. For example, it suffices if the car No. 1 T1 can be imaged to the extent that it can be determined that there are many male passengers in their 40s.

The camera C transmits the captured image to the analysis server 1 (see FIG. 2) described later. For example, the image captured by the camera C is transmitted to the analysis server 1 via the handy terminal 3 (see FIG. 2) which is an information terminal device. Further, for example, the image captured by the camera C is transmitted to the analysis server 1 via an information terminal device (not shown) different from the handy terminal 3 such as a PC (Personal Computer) installed on the train T. You may.

In-car sales are carried out on the train T. In-car sales is a mechanism in which a person in charge travels around a wagon loaded with goods in the train T, for example, and sells the goods to passengers.

Next, the system according to the embodiment will be described. FIG. 2 is a diagram showing a system according to an embodiment. The system includes a handy terminal 3, a POS server 5, a seat server 7, an analysis server 1, and a camera C. The handy terminal 3 is connected to the POS server 5 directly or via an information terminal device (not shown above) via a wireless line M2. Further, the handy terminal 3 is connected to the analysis server 1 by a wireless line M1. Further, the POS server 5 is connected to the analysis server 1 by the communication line L1. Further, the seat server 7 is connected to the analysis server 1 by a communication line L2. Further, the analysis server 1 is connected to the camera C directly or via an information terminal device (not shown above) via a wireless line M3.

The handy terminal 3 is carried by a person in charge of in-vehicle sales. The handy terminal 3 executes sales registration processing and settlement processing of products sold in the vehicle. The sales registration process is a handy terminal that provides product information such as the product name and price of the product corresponding to the product code that identifies the product associated with the product based on the symbol attached to the product purchased by the passenger. Including the process of displaying in 3 and storing the product information. The settlement process includes a process of displaying the total amount of transactions with customers and the amount of change on a handy terminal based on the product information of the product for which sales registration processing has been performed.

The person in charge optically reads a symbol such as a barcode attached to the product purchased by the passenger using the handy terminal 3. Then, the handy terminal 3 executes the sales registration process for the product based on the read symbol. When the passengers have finished purchasing the product, the person in charge operates the payment button provided on the handy terminal 3. Then, the handy terminal 3 displays the total amount of money related to the transaction with the passenger. If there is change in the deposit received from the customer, the handy terminal 3 displays the change amount. The handy terminal 3 transmits the product information and the payment information of the product for which the sales registration has been processed to the POS server 5 together with the number of the passenger car for which the sales registration has been processed and the sales time information.

Further, the handy terminal 3 receives the prediction information from the analysis server 1. The forecast information includes the following information.
1. 1. Information on products that passengers are likely to purchase based on the attribute tendency of the passengers of each passenger car on this train T (hereinafter referred to as "sales product information").
2. In this train T, the quantity of products related to sales product information based on reserved seat information.
3. 3. Product information for sale between specific stations (specific sections) based on the running position information of train T.
4. Product information for sale by reserved seat passenger car, green car, and non-reserved seat passenger car.
5. Information on passenger car sales and congestion based on weather information and statistical number of passengers at each station.

Then, the handy terminal 3 displays the type and amount of products to be loaded in the cart based on the prediction information received from the analysis server 1. First, at the first train station, the handy terminal 3 displays information on products for sale that passengers are likely to purchase based on the forecast information. In addition, when traveling around the reserved seat passenger cars (cars 1 and 2), the load capacity of the products for sale is displayed according to the number of passengers in the reserved seats. In addition, when traveling around the reserved seat passenger car, the information on the products sold in the reserved seat passenger car is displayed. In addition, when traveling around the green car, information on products sold in the green car is displayed. In addition, when traveling around a non-reserved passenger car, information on products sold by the non-reserved passenger car is displayed. Next, while the train T is traveling between the specific stations, the information on the products sold between the specific stations is displayed. The handy terminal 3 may weight the prediction information received from the analysis server 1 and preferentially display the prediction information having a higher weighting priority.

The person in charge determines the type and amount of products to be loaded on the wagon by looking at the display on the handy terminal 3. The person in charge may determine the type and amount of products to be loaded on the wagon in consideration of the weighting of the prediction information displayed on the handy terminal 3.

The POS server 5 is installed, for example, at the headquarters of a company that executes in-vehicle sales. The POS server 5 receives and stores product information and payment information transmitted from a plurality of handy terminals 3 together with sales time information and passenger car number information. In this way, the POS server 5 manages the sales of the products that have been settled by the handy terminal 3. Further, the POS server 5 transmits the accumulated information to the analysis server 1 at a predetermined timing (for example, once a day).

The seat server 7 is installed, for example, at the headquarters of a company that executes in-vehicle sales. Reservation information for reserved seats on train T and reserved seats in the Green Car (hereinafter referred to as "reserved seat information") is stored for each train and each passenger car. Reserved seat information is received from the server of the train T operating company. The seat server 7 transmits reserved seat information to the analysis server 1 at a predetermined timing (for example, once an hour).

The analysis server 1 is installed, for example, at the headquarters of a company that executes in-vehicle sales. The analysis server 1 receives from the POS server 5 the information of the product whose sales registration processing and settlement processing have been processed by the handy terminal 3 together with the sales time information and the passenger car number information. Further, the analysis server 1 receives reserved seat information for each train and each passenger car from the seat server 7. Further, the analysis server 1 receives the image of each passenger car captured by the camera C. The analysis server 1 will be described later with reference to FIGS. 7 and 8.

Next, the hardware configuration of the handy terminal 3 will be described. FIG. 3 is a block diagram showing a hardware configuration of the handy terminal 3. As shown in FIG. 3, the handy terminal 3 includes a CPU (Central Processing Unit) 31, a ROM (Read Only Memory) 32, a RAM (Random Access Memory) 33, a memory unit 34, and the like. The CPU 31 is the control body. The ROM 32 stores various programs. The RAM 33 develops various data. The memory unit 34 stores various programs. The CPU 31, ROM 32, RAM 33, and memory unit 34 are connected to each other via the data bus 35. The CPU 31, ROM 32, and RAM 33 constitute the control unit 300. That is, the control unit 300 executes the control process described later by operating the CPU 31 according to the control program stored in the ROM 32 or the memory unit 34 and expanded in the RAM 33.

The RAM 33 includes a product information unit 331 and a display information unit 332. The product information unit 331 stores the product information of the product for which the handy terminal 3 has processed the sales registration. The display information unit 332 stores the prediction information received from the analysis server 1.

The memory unit 34 includes a control program unit 341 and a product master 342. The control program unit 341 stores a program for controlling and processing the handy terminal 3. The product master 342 stores product information (product name, price, etc.) of the product in association with a product code that identifies the product acquired based on the symbol read by the symbol reading unit 39, which will be described later.

Further, the control unit 300 is connected to the clock unit 41. The clock unit 41 measures the current time. Further, the control unit 300 is connected to the display unit 37, the operation unit 38, and the symbol reading unit 39 via the data bus 35 and the controller 36. The display unit 37 is, for example, a liquid crystal display unit. The display unit 37 displays the product information of the product for which the symbol reading unit 39 has read the symbol. In addition, the display unit 37 displays the total price of the products purchased by the passengers when the sale of the products to one passenger is terminated. In addition, the display unit 37 displays the sales product information based on the prediction information received from the analysis server 1.

The operation unit 38 is a keyboard for operating the handy terminal 3. The operation unit 38 includes a payment button 381. The payment button 381 is operated by the person in charge when the sale of the product to one passenger is terminated.

The symbol reading unit 39 is a device that optically reads a symbol such as a bar code or a two-dimensional code attached to a product. The symbol reading unit 39 reads the symbol by injecting the reflected light of the symbol of the light emitted by itself or the reflected light of the symbol of natural light. The symbol reading unit 39 may have a structure that reads the symbol based on the image obtained by capturing the symbol.

Further, the control unit 300 connects to the communication I / F 40 via the data bus 35. The communication I / F 40 transmits / receives information to / from the analysis server 1 via the wireless line M1. For example, the communication I / F 40 receives the prediction information from the analysis server 1 via the wireless line M1. Further, the communication I / F 40 transmits / receives information to / from the POS server 5 via the wireless line M2. For example, the communication I / F40 transmits product information and payment information to the POS server 5 via the wireless line M2.

Next, the hardware configuration of the POS server 5 will be described. FIG. 4 is a block diagram showing a hardware configuration of the POS server 5. As shown in FIG. 4, the POS server 5 includes a CPU 51, a ROM 52, a RAM 53, a memory unit 54, and the like. The CPU 51 is the control body. The ROM 52 stores various programs. The RAM 53 develops various data. The memory unit 54 stores various programs. The CPU 51, ROM 52, RAM 53, and memory unit 54 are connected to each other via the data bus 55. The CPU 51, ROM 52, and RAM 53 constitute the control unit 500. That is, the control unit 500 executes the control process described later by operating the CPU 51 according to the control program stored in the ROM 52 or the memory unit 54 and expanded in the RAM 53.

The memory unit 54 includes a control program unit 541, a product master 542, and a product aggregation unit 543. The control program unit 541 stores a program for controlling and processing the POS server 5. The product master 542 stores the product information of the product in association with the product code that identifies the product. The product master 542 has the same contents as the product master 342. The control unit 500 transmits the contents of the product master 542 to the handy terminal 3 at a predetermined timing (for example, once a day). The control unit 300 of the handy terminal 3 stores the content received from the POS server 5 as the product master 342. The product totaling unit 543 cumulatively stores the product information and the payment information received from each handy terminal 3. That is, the product aggregation unit 543 comprehensively collects and manages sales information about the products whose sales are registered and settled by each handy terminal 3 (that is, the products sold by the handy terminal 3).

Further, the control unit 500 connects to the display unit 57 and the operation unit 58 via the data bus 55 and the controller 56. The display unit 57 is, for example, a liquid crystal display unit. The operation unit 58 is a keyboard for operating the handy terminal 3.

Further, the control unit 500 connects to the communication I / F 59 via the data bus 55. The communication I / F 59 transmits / receives information to / from the handy terminal 3 via the wireless line M2. For example, the communication I / F 59 receives product information and payment information from the handy terminal 3 via the wireless line M2. Further, the communication I / F 60 transmits / receives information to / from the analysis server 1 via the communication line L1. For example, the communication I / F 60 transmits product information and payment information to the analysis server 1 via the communication line L1.

Next, the hardware of the seat server 7 will be described. FIG. 5 is a block diagram showing a hardware configuration of the seat server 7. As shown in FIG. 5, the seat server 7 includes a CPU 71, a ROM 72, a RAM 73, a memory unit 74, and the like. The CPU 71 is the control subject. The ROM 72 stores various programs. The RAM 73 develops various data. The memory unit 74 stores various programs. The CPU 71, ROM 72, RAM 73, and memory unit 74 are connected to each other via the data bus 75. The CPU 71, ROM 72, and RAM 73 constitute the control unit 700. That is, the control unit 700 executes the control process described later by operating the CPU 71 according to the control program stored in the ROM 72 or the memory unit 74 and expanded in the RAM 73.

The memory unit 74 includes a control program unit 741 and a seat DB (database) 742. The control program unit 741 stores a program for controlling and processing the seat server 7. The seat DB 742 stores reservation information (reserved seat information) of reserved seats and green cars for each train and each passenger car. This reserved seat information indicates which seat is reserved for which section. In the embodiment, the memory unit 74 is provided with the seat DB 742, but the seat DB 742 may be provided separately from the memory unit 74. Further, the seat DB 742 may be a server different from the seat server 7. The seat DB742 will be described later in FIG.

Further, the control unit 700 connects to the display unit 77 and the operation unit 78 via the data bus 75 and the controller 76. The display unit 77 is, for example, a liquid crystal display unit. The operation unit 78 is a keyboard for operating the seat server 7.

Further, the control unit 700 connects to the communication I / F 79 via the data bus 75. The communication I / F 79 transmits / receives information to / from the analysis server 1 via the communication line L2. For example, the communication I / F 79 transmits reserved seat information to the analysis server 1 via the communication line L2.

Next, the seat DB 742 will be described. FIG. 6 is a diagram showing a memory configuration of the seat DB 742. As shown in FIG. 6, the seat DB 742 stores reserved seat information for each passenger car for each train T. In addition, the seat DB 742 stores reserved seat information for each station. For example, in the case of FIG. 6, the seat DB 742 stores reserved seat information for each passenger car in the section between the A station and the B station. That is, the seat DB 742 stores the reserved seat information of the first car in the reserved seat information unit 742AB1 in the section between the A station and the B station. Further, in the same section, the reserved seat information of the second car is stored in the reserved seat information unit 742AB2. Similarly, the reserved seat information of the third car is stored in the reserved seat information unit 742AB3. The reserved seat information of the No. 4 car is stored in the reserved seat information unit 742AB4.

Further, the seat DB 742 stores reserved seat information for each passenger car in the section between the B station and the C station. That is, the seat DB 742 stores the reserved seat information of the first car in the reserved seat information unit 742BC1 in the section between the B station and the C station. Further, in the same section, the reserved seat information of the second car is stored in the reserved seat information unit 742BC2. Similarly, the reserved seat information of the third car is stored in the reserved seat information unit 742BC3. The reserved seat information of the No. 4 car is stored in the reserved seat information unit 742BC4. The seat DB 742 similarly stores reserved seat information for each train and each passenger car for sections of other stations.

Next, the hardware of the analysis server 1 will be described. FIG. 7 is a block diagram showing a hardware configuration of the analysis server 1. As shown in FIG. 7, the analysis server 1 includes a CPU 11, a ROM 12, a RAM 13, a memory unit 14, and the like. The CPU 11 is the control subject. The ROM 12 stores various programs. The RAM 13 develops various data. The memory unit 14 stores various programs. The CPU 11, ROM 12, RAM 13, and memory unit 14 are connected to each other via the data bus 15. The CPU 11, ROM 12, and RAM 13 constitute the control unit 100. That is, the control unit 100 executes the control process described later by operating the CPU 11 according to the control program stored in the ROM 12 or the memory unit 14 and expanded in the RAM 13.

The memory unit 14 includes a control program unit 141 and an analysis DB 142. The control program unit 141 stores a program for controlling and processing the analysis server 1. The analysis DB 142 stores various information for determining the product to be loaded on the wagon. In the embodiment, the memory unit 14 is provided with the analysis DB 142, but the analysis DB 142 may be provided separately from the memory unit 14. Further, the analysis DB 142 may be a server different from the analysis server 1. The analysis DB 142 will be described later with reference to FIG.

Further, the control unit 100 connects to the display unit 17 and the operation unit 18 via the data bus 15 and the controller 16. The display unit 17 is, for example, a liquid crystal display unit. The operation unit 18 is a keyboard for operating the analysis server 1.

Further, the control unit 100 connects to the communication I / F 19 via the data bus 15. The communication I / F 19 transmits / receives information to / from the handy terminal 3 via the wireless line M1. For example, the communication I / F 19 transmits the prediction information to the handy terminal 3 via the wireless line M1. Further, the communication I / F 19 transmits / receives information to / from the camera C via the wireless line M3. For example, the communication I / F 19 receives the image of the passenger car captured by the camera C via the wireless line M3.

Further, the control unit 100 connects to the communication I / F 20 via the data bus 15. The communication I / F 20 transmits / receives information to / from the POS server 5 via the communication line L1. For example, the communication I / F 20 receives product information, payment information, payment time information, passenger car number information, and the like from the POS server 5 via the communication line L1. Further, the communication I / F 20 transmits / receives information to / from the seat server 7 via the communication line L2. For example, the communication I / F 20 receives reserved seat information via the communication line L2.

Next, the analysis DB 142 will be described. FIG. 8 is a diagram showing a memory configuration of the analysis DB 142. As shown in FIG. 8, the analysis DB 142 includes reserved seat information unit 1421 for each passenger vehicle, passenger information unit 1422 for each passenger vehicle, hot selling information unit 1423 for each passenger car, hot selling information unit 1424 for each station, and hot selling information unit 1425 for each time zone. It includes a hot selling information unit 1426 by weather, a hot selling information unit 1427 by boarding station, a purchasing tendency information unit 1428 by attribute, and an attribute information unit 1429 by passenger vehicle.

The reserved seat information unit 1421 for each passenger car stores the reserved seat information for each train and each passenger car received from the seat server 7. The passenger / passenger information unit 1422 for each passenger car stores the number of passengers for each train and each passenger car between each station. This information is statistical information on the number of passengers in each passenger car based on the number of passengers in the past at each station. The best-selling information unit 1423 for each passenger car stores the best-selling information for each type of passenger car. For example, the best-selling information in the reserved seat car, the best-selling information in the green car, the best-selling information in the non-reserved seat car, and the like are stored. This information is statistical information based on the accumulated information of sold products by type of passenger cars in the past. The best-selling information unit 1424 for each station stores the best-selling information for each station. For example, the best-selling information between A station and B station and the best-selling information between B station and C station are stored. This information is statistical information based on the accumulated information of products sold between stations in the past. The best-selling information unit 1425 for each time zone stores the best-selling information for each time zone. For example, the best-selling information for each time zone such as morning time zone, morning time zone, daytime time zone, afternoon time zone, evening time zone, night time zone, midnight time zone, etc. is stored. This information is statistical information based on the accumulated information of the products sold by the past time zone. The weather-specific hot-selling information unit 1426 stores the hot-selling information according to the weather. For example, it stores hot-selling information by weather such as sunny, cloudy, rainy, and snowy. In addition, the weather-specific hot-selling information unit 1426 also stores hot-selling information by season, temperature, and the like. This information is statistical information based on accumulated information of products sold according to past weather. The boarding station selling information unit 1427 stores the selling information for each boarding station. For example, it stores the best-selling information of passengers who boarded from station A. This information is statistical information based on the accumulated information of products sold by each boarding station in the past.

The attribute-based purchasing tendency information unit 1428 stores the best-selling information by attribute (age group and gender). For example, it stores the best-selling information by age group such as teens and 20s, and the best-selling information by gender of men and women. This information is statistical information based on the accumulated information of products sold by past attributes. The passenger car-specific attribute information unit 1429 stores the attribute tendency information for each train and each passenger car based on the image captured by the camera C and received from the camera C. The control unit 100 determines the attributes of each passenger based on the passenger's face and clothes in the image received from the camera C. Then, the control unit 100 stores the determined most attribute as the attribute tendency of the passenger car. For example, a passenger car with the largest number of men in their thirties has a male in their thirties as the attribute tendency of the passenger car.

The passenger attributes are determined based on, for example, the passenger face parts information stored for each attribute. Face part information is data showing each part or feature for each attribute, which classifies a person's face according to the part or feature. For example, it refers to data representing the characteristics of parts such as human eyes, nose, mouth, ears, and chin, and facial deformation characteristics such as smile, serious face, closed eyes, and open eyes. The face part information stored for each attribute is information representing the characteristics of the attribute, which is different from other attributes. For example, the face parts information of a teenager (male) stores information on eyes, nose, mouth, ears, and chin that show the characteristics of a male in his teens, and information on a smile and a serious face that show the characteristics of a male in his teens. Has been done. The face part information for each attribute is information that is created based on a large amount of statistical data and that remarkably represents the attribute.

From here, the control process of the handy terminal 3 according to the embodiment will be described. FIG. 9 is a functional block diagram showing a functional configuration of the handy terminal 3. The control unit 300 functions as the receiving means 301 and the sales product information notification means 302 by following the control program stored in the ROM 32 or the memory unit 34 and expanded in the RAM 33.

The receiving means 301 has a function of receiving the prediction information transmitted from the analysis server 1.

The sales product information notification means 302 has a function of notifying the sales product information of the product based on the prediction information received from the analysis server 1.

FIG. 10 is a flowchart showing the flow of control processing of the handy terminal 3. As shown in FIG. 10, the control unit 300 determines whether or not the symbol reading unit 39 has read the symbol attached to the product (S11). When it is determined that the symbol has been read (Yes in S11), the control unit 300 acquires the current time from the clock unit 41 (S12). Then, the control unit 300 acquires the product information of the product from the product master 342 for the product (S13). Then, the control unit 300 executes the sales registration process for the product (S14). The product information processed for sales registration is stored in the product information unit 331. At this time, the control unit 300 stores in the product information unit 331 the time acquired in S12 and the number information of the passenger car for which the sales registration processing has been performed, together with the product information of the product for which the sales registration processing has been performed. The passenger car number information may be automatically input by the person in charge or by registering it in the handy terminal 3 in advance. Each time the person in charge enters each passenger car, the number information can be automatically input by registering the number information in the handy terminal 3. Then, the control unit 300 returns to S11.

If the symbol reading unit 39 determines that the symbol attached to the product has not been read (No in S11), the control unit 300 determines whether or not the payment button 381 has been operated (S15). When it is determined that the settlement button 381 has been operated (Yes in S15), the control unit 300 executes the settlement process for the product for which the sales registration process has been performed (S16). That is, the control unit 300 displays the total amount of the products for which sales registration processing has been performed on the display unit 37. Then, the control unit 300 transmits the product information, the payment information, the time information, and the number information of the product for which the sales registration process has been performed to the POS server 5 together with the train number information for identifying the train T (S17). Then, the control unit 300 returns to S11.

When it is determined that the payment button 381 is not operated (No in S15), the following description will be given after the explanation of the control process of the analysis server 1.

Next, the control process of the POS server 5 will be described. FIG. 11 is a flowchart showing the flow of control processing of the POS server 5. As shown in FIG. 11, the control unit 500 of the POS server 5 determines whether or not the product information, payment information, time information, telephone number information, and vehicle number information have been received from the handy terminal 3 (S31). When it is determined that the product information, payment information, time information, number information, and vehicle number information have been received (Yes in S31), the control unit 500 cumulatively stores these information in the product totaling unit 543 (S32). ). Then, the control unit 500 returns to S31.

If it is determined that the product information, payment information, time information, telephone number information, and vehicle number information have not been received from the handy terminal 3 (No in S31), the control unit 500 has a predetermined transmission time. Whether or not it is determined (S33). When it is determined that the predetermined transmission time is reached (Yes in S33), the control unit 500 transmits the information cumulatively stored in the product totaling unit 543 to the analysis server 1 (S34). Then, the control unit 500 returns to S31. If it is determined that the transmission time is not the predetermined time (No in S33), the control unit 500 returns to S31.

Next, the control process of the seat server 7 will be described. FIG. 12 is a flowchart showing the flow of control processing of the seat server 7. As shown in FIG. 12, the control unit 700 of the seat server 7 determines whether or not the timing is predetermined (S41). Waiting until a predetermined timing is reached (No in S41), and when it is determined that the timing is predetermined (Yes in S41), the control unit 700 analyzes the reserved seat information stored in the seat DB 742 in the analysis server 1. (S42). Then, the control unit 700 returns to S41.

From here, the control of the analysis server 1 will be described. FIG. 13 is a functional block diagram showing a functional configuration of the analysis server 1. The control unit 100 functions as an attribute determination unit 101, a product prediction unit 102, a prediction information transmission unit 103, and a reservation status determination unit 104 by following a control program stored in the ROM 12 or the memory unit 14 and expanded in the RAM 13.

The attribute determination means 101 has a function of determining the attribute tendency of passengers for each passenger vehicle based on an image of each passenger vehicle of the train T in which a plurality of passenger vehicles are connected.

The product prediction means 102 has a function of predicting a product to be sold in each passenger car based on the determined attribute tendency and purchase tendency information for each attribute.

The prediction information transmitting means 103 has a function of transmitting the predicted prediction information for each passenger car to the information terminal device provided in the train T to which the image is transmitted.

The reservation status determination means 104 has a function of determining the reservation status of reserved seats based on the reserved seat information indicating the seats reserved in advance.

FIG. 14 is a flowchart showing the flow of control processing of the analysis server 1. The control unit 100 of the analysis server 1 receives the information and the like transmitted by the POS server 5 in S34, and constructs the information to be stored in the analysis DB 142. That is, the control unit 100 determines which product was sold by which passenger car of which train T and at what time based on the product information, payment information, time information, number information, and vehicle number information received from the POS server 5. Is accumulated for each product. In addition, from the sales time, it is determined between which stations the product was sold and accumulated. Based on these accumulated information and the separately acquired weather information, the information of the hot selling information unit 1423 by passenger car, the information of the hot selling information unit 1424 by station, the information of the selling information unit 1425 by time zone, and the selling information unit 1426 by weather. Information, information of boarding station hot selling information department 1427, is updated.

First, the control unit 100 determines whether or not the image information captured by the camera C has been received from the camera C (S51). When it is determined that the image information has been received (Yes in S51), the control unit 100 (attribute determination means 101) determines the attribute tendency of the passenger for each passenger vehicle based on the received image information (S52). Next, the control unit 100 stores the determined attribute tendency of the passenger for each passenger car in the attribute information unit 1429 for each passenger car (S53). Each time the control unit 100 receives the image information from the camera C, the control unit 100 updates the attribute tendency information stored in the passenger car-specific attribute information unit 1429 to the latest information. Then, the control unit 100 returns to S51.

If it is determined that the image information has not been received (No in S51), the control unit 100 determines whether or not the reserved seat information has been received from the seat server 7 (S61). When it is determined that the reserved seat information has been received (Yes in S61), the control unit 100 stores the reserved seat information for each passenger car (S62). The control unit 100 receives reserved seat information from the seat server 7 at predetermined timings and updates it with the latest information. Then, the control unit 100 returns to S51.

If it is determined that the reserved seat information has not been received from the seat server 7 (No in S61), the control unit 100 determines whether or not it is the departure time of the first station of the train T (S71). .. The analysis server 1 stores the departure times at the starting station and the intermediate station for all the trains T under its jurisdiction. Based on this information, the control unit 100 determines whether or not it is the departure time of the first train station for the train T. When it is determined that it is the departure time of the first train station of the train T (Yes in S71), the control unit 100 (product prediction means 102) loads the product on the wagon of the train T and sells it (hereinafter, "sales"). "Product") is predicted (S72). That is, the control unit 100 is based on the attribute tendency information stored in the attribute information unit 1429 for each passenger vehicle and the purchase tendency information corresponding to the attribute tendency stored in the purchase tendency information unit 1428 for each passenger vehicle. , Predict the products for sale in passenger cars. Further, the control unit 100 (reservation status determination means 104) has a reservation status of reserved seats for each passenger car (whether there are many or few reserved seats) based on the reserved seat information stored in the reserved seat information unit 1421 for each passenger car. Is it?). Based on the determined reservation status, the control unit 100 predicts the amount of products for sale to be loaded on the wagon that wanders around the reserved seat vehicle. Further, the control unit 100 predicts the degree of congestion of the train T between each station and the products to be sold for each passenger car based on the passenger number information at each station stored in the passenger car-specific passenger information unit 1422. Further, the control unit 100 predicts the products to be sold in the reserved seat car, the green car, and the non-reserved seat car based on the hot selling information for each type of the passenger car stored in the hot selling information unit 1423 for each passenger car. Further, the control unit 100 predicts the selling products for each time zone based on the selling information for each time zone stored in the selling information unit 1425 for each time zone. In addition, the control unit 100 predicts the products to be sold by weather based on the hot selling information by weather stored in the hot selling information unit 1426 by weather.

Next, the control unit 100 (prediction information transmitting means 103) transfers the predicted information including the predicted sales product information and the congestion condition information to all the handy terminals 3 used to sell the product on the train T. Transmit (S73). Then, the control unit 100 returns to S51.

If it is determined that it is not the departure time of the first train station of the train T (No in S71), the control unit 100 determines whether or not the train departs from the first station and then departs from the intermediate station (S81). The control unit 100 determines whether or not the train has departed from the intermediate station based on the stored departure time of the intermediate station. If it is determined that the train has departed on the way (Yes in S81), the control unit 100 predicts the products to be sold between the departure station and the next station. That is, the control unit 100 predicts the products to be sold based on the sales information stored in the sales information unit 1424 for each station. Further, the control unit 100 predicts the products to be sold to the passengers who boarded at the departure station based on the selling information for each boarding station stored in the boarding station selling information unit 1427.

Next, the control unit 100 transmits the prediction information including the sales product information of the predicted sales product to all the handy terminals 3 used for selling the product on the train T (S83). Then, the control unit 100 returns to S51. Further, when the train departs from the station on the way and is determined to be in the residence (No in S81), the control unit 100 returns to S51.

From here, the control process of the handy terminal 3 after the case where it is determined that the payment button 381 in FIG. 10 is not operated (No in S15) will be described.

When it is determined that the settlement button 381 is not operated (No in S15), the control unit 300 (reception means 301) determines whether or not the prediction information has been received from the analysis server 1 (S21). When it is determined that the prediction information has been received (Yes in S21), the control unit 300 stores the sales product information included in the prediction information in the display information unit 332. Then, the control unit 300 (sales product information notification means 302) displays (notifies) the sales product information stored in the display information unit 332 on the display unit 37 (S22). The handy terminal 3 may sequentially display the received sales product information. Further, the handy terminal 3 may weight the received sales product information to display the sales product information having high importance. For example, the sales product information predicted based on the attribute tendency may be weighted higher, and the sales product information predicted based on the weather may be weighted lower. Further, the handy terminal 3 may display mainly the sales product information having a high total value of the importance of the received sales product information. If it is determined that the prediction information has not been received (No in S21), the control unit 300 returns to S11.

The forecast information transmitted by the analysis server 1 in the processing of S73 and received in S21 includes sales product information based on the weather of the day, information on the congestion condition of reserved seats on the day, reserved seats, green cars, and unreserved seat sales products. Information, information on products sold by attribute tendency by passenger car at the first train station, information on products sold by time zone at the departure time, etc. are included. In addition, the prediction information received when the train T departs from the first station includes congestion information by time zone and by passenger car.

Further, the prediction information transmitted by the analysis server 1 in the process of S81 and received in S21 includes sales product information between stations and sales product information for passengers who boarded at the departure station.

The person in charge of operating the wagon loads the product to be sold to the passengers on the wagon with reference to the product information for sale displayed on the handy terminal 3. That is, a large amount of products that the passengers of the train T are likely to purchase are loaded. Therefore, the wagon can be loaded with the products sold in the train T in just proportion. Therefore, it is possible to prevent the product from being out of stock during the in-car sales. In addition, the person in charge predicts which passenger car will be congested in which time zone based on the congestion information for each time zone. Then, the person in charge carries out in-car sales in the passenger car while avoiding the busy time zone. By doing so, it is possible to efficiently carry out in-vehicle sales even in passenger cars that are expected to be congested.

According to such an embodiment, the analysis server 1 determines the attribute tendency of the passenger and the corresponding purchasing tendency for each passenger car, predicts the sales product for each passenger car based on the determined purchasing tendency, and transmits the product to the handy terminal 3. do. The handy terminal 3 displays the predicted sales product information. The person in charge loads a lot of sales products that passengers are likely to purchase on the wagon by referring to the displayed sales product information. Therefore, it is possible to sell products that passengers are likely to desire without running out of stock, which makes it possible to improve the sales amount and lead to efficient sales.

Although not described in the embodiment, the analysis server 1 considers the best-selling information based on the attribute tendency of each train (for example, the characteristics of "Nozomi", "Hikari", and "Kodama" of the Shinkansen). , The product information for sale may be predicted. In addition, the sales product information may be predicted for each passenger car in consideration of the best-selling information based on the statistical information indicating the passenger cars that are crowded by the passenger cars and the passenger cars that are relatively vacant. For example, if passenger cars near the stairs of the platform tend to be crowded at each station, a large number of products for sale may be loaded on the wagons sold in the car for the passenger cars.

Although the embodiments of the present invention have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other embodiments, and various omissions, replacements, changes, and combinations can be made without departing from the gist of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are also included in the scope of the invention described in the claims and the equivalent scope thereof.

For example, in the embodiment, the analysis server 1 transmits the prediction information to the handy terminal 3 when departing from the starting station. However, for example, the prediction information may be transmitted at a predetermined timing (for example, in the morning) before the train T departs.

Further, in the embodiment, the analysis server 1 transmits the prediction information between stations to the handy terminal 3 at the timing of departure from a specific station. However, the prediction information between stations may be transmitted to the handy terminal 3 at the same time as the prediction information when departing from the first station. Further, the prediction information may be transmitted at a specific timing (for example, in the morning) before the train T departs.

Further, in the embodiment, since the handy terminal 3 is used as the information terminal device, the product information for sale of the product is displayed on the handy terminal 3. However, for example, when the above-mentioned PC or the like is used as an information terminal device, the information terminal device displays the product sales information on the PC or prints the product sales product information under the control of the PC. It may be notified.

Further, in the embodiment, a train in which a plurality of passenger cars (vehicles) are connected has been described as an example of a vehicle. However, the vehicle may be any vehicle as long as it has a vehicle, and may be, for example, a bus in which a plurality of vehicles are connected. Further, the vehicle may be, for example, a bus or an airplane composed of one vehicle provided with a space for passengers to ride. In this case, the space on which the passenger gets on the bus or airplane is the vehicle. In-car sales also include selling products on airplanes.

In addition, by adopting this embodiment, the product will not be out of stock and it is not necessary to return to the office in the car where the product is stocked. Therefore, the person in charge of selling in the car is not necessarily a human being. It doesn't have to be. For example, the robot may be the person in charge.

The program executed by the analysis server 1 of the embodiment is a file in an installable format or an executable format, and is a computer such as a CD-ROM, a flexible disc (FD), a CD-R, or a DVD (Digital Versatile Disc). It is recorded and provided on a readable recording medium.

Further, the program executed by the analysis server 1 of the embodiment may be stored on a computer connected to a network such as the Internet and provided by downloading via the network. Further, the program executed by the analysis server 1 of the embodiment may be configured to be provided or distributed via a network such as the Internet.

Further, the program executed by the analysis server 1 of the embodiment may be configured to be provided by incorporating it into a ROM or the like in advance.

1 Analysis server 3 Handy terminal 5 POS server 7 Seat server 100 Control unit 101 Attribute judgment means 102 Product prediction means 103 Prediction information transmission means 104 Reservation status judgment means 142 Analysis DB
300 Control unit 301 Receiving means 302 Sales product information notification means 500 Control unit 700 Control unit 742 Seat DB

Japanese Unexamined Patent Publication No. 2004-064493

Claims (5)

Customers on the basis of the image of the captured each vehicle rides a plurality of vehicles are connected to ride, an attribute determining means for determining attributes tendency of the vehicle by a passenger,
And products predicting means for predicting a product sold in each vehicle based on the determined another attribute trends and demographic purchasing trend information vehicle,
Prediction information transmitting means for transmitting the predicted information of the predicted product for each vehicle to the information terminal device provided in the vehicle to which the image is transmitted, and
Information processing device equipped with. Further provided with a reservation status determination means for determining the reservation status of the reserved seat based on the reserved seat information indicating the reserved seat in advance.
The product prediction means further predicts the amount of products to be sold in the reserved seat vehicle based on the reserved seat information.
The information processing device according to claim 1. The product prediction means predicts the type of product to be sold in each vehicle of a vehicle traveling in a specific section.
The information processing device according to claim 1 or 2. A system equipped with an information processing device and an information terminal device provided in a vehicle.
The information processing device
Customers on the basis of the image of the captured each vehicle rides a plurality of vehicles are connected to ride, an attribute determining means for determining attributes tendency of the vehicle by a passenger,
And products predicting means for predicting a product sold in each vehicle based on the determined another attribute trends and demographic purchasing trend information vehicle,
Prediction information transmitting means for transmitting the predicted information of the predicted product for each vehicle to the information terminal device provided in the vehicle to which the image is transmitted, and
With
The information terminal device is
A receiving means for receiving the transmitted prediction information, and
Sales product information notification means for notifying sales product information of products based on the received forecast information, and
System with. A computer as an information processing device
Customers on the basis of the image of the captured each vehicle rides a plurality of vehicles are connected to ride, an attribute determining means for determining attributes tendency of the vehicle by a passenger,
And products predicting means for predicting a product sold in each vehicle based on the determined another attribute trends and demographic purchasing trend information vehicle,
Prediction information transmitting means for transmitting the predicted information of the predicted product for each vehicle to the information terminal device provided in the vehicle to which the image is transmitted, and
A program to make it work.

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