Management apparatus for managing an automatic change machine and receipt printer, and method of managing the same

A management apparatus according to an embodiment includes an interface for communicating with an automatic change machine in a store. The automatic change machine receives money and provides withdrawal of money. A storage device stores first statistical information indicating a number of customers in the store during past time periods, and second statistical information indicating an amount of money stored in the automatic change machine during past time periods. A processor is programmed to perform a prediction processing including: predicting, based on the first statistical information and the second statistical information, at least one of an appropriate collection time period during a current day for collecting money from the automatic change machine and an appropriate refill time period for refilling money in the automatic change machine, and outputting information for displaying an image indicating the at least one of the predicted collection time period and the predicted refill time period.

CROSS-REFERENCE TO RELATED APPLICATION

This application is based upon and claims the benefit of priority from Japanese Patent Application No. 2017-162452, filed in Aug. 25, 2017, the entire contents of which are incorporated herein by reference.

FIELD

Embodiments described herein relate generally to a management apparatus for managing an automatic change machine and receipt printer, and a method of managing the same.

BACKGROUND

In the related art, a point of sales (POS) system is introduced in a store such as a supermarket or a convenience store to process sales of commodities purchased by customers and to manage sales data of the store.

The POS system includes one or a plurality of POS terminals and a server such as a store server. Each POS terminal performs sales registration and payment processing for commodities purchased by customers. The server receives and stores sales data from the one or the plurality of POS terminals and manages the sales data of the store.

A coin change machine and a bill change machine (hereinafter, collectively referred to as an “automatic change machine”) that are used for deposit and withdrawal of bills and coins (hereinafter, collectively referred to as “money”) are connected to each POS terminal. Money that is received from customers is deposited and stored in each automatic change machine. Change that is to be given to customers is withdrawn from each automatic change machine.

Each POS terminal issues receipts to be given to customers. Commodity information related to commodities purchased by customers, payment information related to payment, and the like are printed on the receipts. A roll of receipt paper is stored in each POS terminal, and the receipts are issued by printing the commodity information, the payment information, and the like on the receipt paper.

Money needs to be collected from each automatic change machine filled with money. Also, each automatic change machine having not enough money needs to be refilled with money. In addition, if the receipt paper becomes insufficient by issuing the receipts, the receipt paper needs to be replaced with new receipt paper.

If refill or collection of money in an automatic change machine or replacement of receipt paper is performed, operations with respect to the corresponding POS terminal or automatic change machine needs to be stopped. Thus, when the store is congested, refill or collection of money in each automatic change machine or replacement of receipt paper in each POS terminal causes customers performing payment to wait.

DETAILED DESCRIPTION

Embodiments provide a management apparatus and a method that enable prediction of an appropriate time period for money refill or an appropriate time period for money collection, or an appropriate time period for replacing receipt paper in which the number of customers is relatively small.

An automatic change machine management apparatus according to an embodiment includes an interface for communicating with an automatic change machine in a store. The automatic change machine receives money and provides withdrawal of money. A storage device stores first statistical information indicating a number of customers in the store during past time periods, and second statistical information indicating an amount of money stored in the automatic change machine during past time periods. A processor is programmed to perform a prediction processing including: predicting, based on the first statistical information and the second statistical information, at least one of an appropriate collection time period during a current day for collecting money from the automatic change machine and an appropriate refill time period for refilling money in the automatic change machine, and outputting information for displaying an image indicating the at least one of the predicted collection time period and the predicted refill time period.

Hereinafter, an embodiment will be described in detail with reference to the drawings. In the embodiment, a server will be described as one example of a management apparatus. The embodiment described below is not for limitation.

FIG. 1is a schematic diagram illustrating a POS system according to the embodiment. The POS system includes a server1, a plurality of POS terminals3, and an automatic change machine5connected to each POS terminal3in a store T. In this case, the automatic change machine5is indirectly connected to the server1.

Each POS terminal3is connected to the server1through a communication line N1such as a local area network (LAN). Thus, the server1and the POS terminal3can transmit and receive data and the like with each other.

The POS terminal3executes sales registration and payment processing for commodities that are sold in the store T. The sales registration refers to a process of acquiring a commodity code by capturing or optically reading a symbol or an image of a symbol such as a barcode assigned to a sold commodity, displaying commodity information (a commodity name, a price, and the like) related to the commodity read from a commodity master based on the acquired commodity code, and storing the commodity information in a RAM or the like. The payment processing refers to, for example, a process of displaying the total amount of money related to a transaction based on the commodity information stored in the RAM or the like during the sales registration, and calculating and displaying the amount of change based on money (cash) received from a customer.

The POS terminal3transmits information regarding the calculated amount of change to the automatic change machine5. The POS terminal3also outputs the commodity information and the payment information to a receipt issuing device. The receipt issuing device issues a receipt on which the input commodity information and payment information are printed. If the receipt issuing device is incorporated in the POS terminal3, the receipt issuing device functions as a printing device40(refer toFIG. 5) which will be described later. The receipt issuing device may be a printing device that is electrically connected to the POS terminal3. In the embodiment, the printing device40will be described as the receipt issuing device below. The POS terminal3also transmits the commodity information and the payment information to the server1through the communication line N1.

The server1tracks and manages sales data from the store T based on the commodity information and the payment information received from each POS terminal3. The server predicts a time period for refilling money in the automatic change machine5and a time period for collecting money from the automatic change machine5. The server1also predicts a time period for replacing a roll of receipt paper stored in the POS terminal3.

The automatic change machine5is electrically connected to the POS terminal3. Thus, the POS terminal3and the automatic change machine5can transmit and receive data and the like with each other. The automatic change machine5has the function of at least one of a coin change machine that is used for deposit and withdrawal of coins, and a bill change machine that is used for deposit and withdrawal of bills. The embodiment will be described using the automatic change machine5that has the function of both deposit and withdrawal of coins, and deposit and withdrawal of bills.

The automatic change machine5includes a coin deposit unit, a coin withdrawal unit, a bill deposit unit, and a bill withdrawal unit (none illustrated). The coin deposit unit is used for deposit of coins from the customer into the automatic change machine5. The coin withdrawal unit is used for withdrawal of coins included in money to be paid to the customer as change. The bill deposit unit is used for deposit of bills received from the customer into the automatic change machine5. The bill withdrawal unit is used for withdrawal of bills included in the money to be paid to the customer as change.

The automatic change machine5includes a storage unit in which coins deposited from the coin deposit unit and bills deposited from the bill deposit unit are stored by type. If change information is input from the POS terminal3, the automatic change machine5withdraws money corresponding to the amount of change from money stored in the storage unit. If the withdrawn money includes coins, the coins are withdrawn from the coin withdrawal unit. If the withdrawn money includes bills, the bills are withdrawn from the bill withdrawal unit.

The server1can communicate with a server7installed in a security company through a communication line N2such as an Internet line. Thus, the server1and the server7in the security company can transmit and receive data and the like with each other. The server1can also communicate with a server8installed in a bank through the communication line N2. Thus, the server1and the server8in the bank can transmit and receive data and the like with each other.

A company that operates the store T outsources, to the security company, work such as transporting money to be used for change to a safe in the store T from the bank, or transporting collected sales money to the bank. The money for change is prepared as change in the automatic change machine5. The store T communicates information related to money between the server1and the server7and the server in order to request the security company to prepare sufficient money for change or to transport collected money for deposit in the bank promptly.

The server1can also communicate with a server9installed in a weather forecasting company through the communication line N2. Thus, the server1and the server9in the weather forecasting company can transmit and receive data and the like with each other. The server1continuously or periodically receives meteorological information such as weather, temperature, and humidity from the server9.

The server1estimates the number of customers visiting the store T based on the acquired meteorological information and statistical information (hereinafter referred to as “first statistical information”) which will be described later. The server1predicts the time period for refiling money in the automatic change machine5or the time period for collecting money from the automatic change machine5based on the first statistical information and statistical information (hereinafter referred to as “second statistical information”) related to the amount of money stored in the automatic change machine5.

Hereinafter, hardware configurations of the server1and the POS terminal3will be described. First, a hardware configuration of the server1will be described.FIG. 2is a block diagram illustrating a hardware configuration of the server1. As illustrated inFIG. 2, the server1includes a central processing unit (CPU)11, a read-only memory (ROM)12, a random access memory (RAM)13, a memory unit14, and the like. The CPU11is a main controller. The ROM12stores various programs. Programs and various types of data are loaded into the RAM13. The memory unit14stores various programs. The CPU11, the ROM12, the RAM13, and the memory unit14are connected to each other through a bus15. The CPU11, the ROM12, and the RAM13constitute a control unit100. That is, the control unit100executes a control, described later, related to the server1by operating the CPU11in accordance with a control program that is stored in the ROM12or the memory unit14and loaded into the RAM13.

The memory unit14is a non-volatile memory device such as a hard disc drive (HDD) or a flash memory that retains stored information even if power is off. The memory unit14includes a control program141, a sales management unit142, a statistics section143, a change management unit144, and a receipt management unit145. The control program141is used for controlling the server1. The sales management unit142stores and manages sales information that is acquired by counting the commodity information and the payment information which are related to commodities purchased by customers and received from each POS terminal3.

The statistics section143stores the first statistical information, the second statistical information, and third statistical information related to the amount of use of the receipt paper. Details of the statistics section143will be described later in connection withFIG. 3. For each automatic change machine5(that is, for each POS terminal3), the change management unit144stores information related to each type of money stored in the automatic change machine5and received from the POS terminal3.

For each POS terminal3, the receipt management unit145stores information related to the actual amount of use of the receipt paper and received from the POS terminal3. The amount of use of the receipt paper is calculated based on data such as the number of issued receipts handed to customers, the amount of printing of commercial messages or logos on the receipt paper, the number of issued receipts including sales promotion information, the number of issued receipt copies, the ratio of electronic receipts (i.e., the ratio of receipts not issued as paper receipts compared to total receipts issued), and the number of non-transaction receipts issued (reports and the like at the time of inspection and settlement). The amount of use of the receipt paper can be estimated based on statistical data of the average amount of use of the receipt paper in one instance of issuing the receipt, and the number of sheets of issued receipt paper. The amount of use of the receipt paper can also be estimated by, for example, measuring a distance in which the receipt paper is transported. The distance in which the receipt paper is transported can be measured based on the number of rotations of a transport roller that transports the receipt paper.

The control unit100is connected to an operation unit and a display device18through the bus15and a controller16. The operation unit17is a keyboard. The display device18displays information to an operating person who operates the server1.

The control unit100is also connected to a communication interface (I/F)19through the bus15. The communication interface19is communicably connected to the plurality of POS terminals3through the communication line N1. The control unit100is also connected to a communication interface (I/F)20through the bus15. The communication interface20is communicably connected to the security company server7, the bank server8, and the weather forecasting company server9outside the store T through the communication line N2.

Next, the statistics section143will be described.FIG. 3is a diagram illustrating a memory configuration of the statistics section143corresponding to one automatic change machine5. The statistics section143stores, in a base data section1431, statistical data (first statistical information) that represents the number of customers visiting the store T. The statistics section143stores, in a stored money statistics section1432, statistical data (second statistical information) that represents the number of pieces of each type of money stored in the automatic change machine5. The statistics section143stores, in a used receipt amount statistics section1433, statistical data (third statistical information) that represents the amount of use of the receipt paper stored in the POS terminal3during one day.

The base data section1431includes a daily transaction number statistics section14311, a day-of-week specific transaction number statistics section14312, a weather specific transaction number statistics section14313, a special sale day specific transaction number statistics section14314, an event specific transaction number statistics section14315, a daily transaction item number statistics section14316, a day-of-week specific transaction item number statistics section14317, a weather specific transaction item number statistics section14318, a special sale day specific transaction item number statistics section14319, and an event specific transaction item number statistics section14320.

The daily transaction number statistics section14311stores statistical data that represents a daily number of transactions at each time (for example, the number of transactions per hour). With this statistical data, a time range in which the number of transactions is large, and a time range in which the number of transactions is small during one day can be found. In addition, the number of transactions at each time can be found for each day in a predetermined period (for example, the first to the thirtieth (or the thirty-first) of each month). In addition, characteristics (differences) of a daily change in the number of transactions can be found.

The day-of-week specific transaction number statistics section14312stores statistical data that represents the number of transactions at each time (for example, the number of transactions per hour) for each day (Sunday to Saturday). With this statistical data, a time range in which the number of transactions is large, and a time range in which the number of transactions is small during one day can be found for each day of the week. In addition, the number of transactions at each time can be found for each day of the week. In addition, differences in the number of transactions can be found for each day of the week compared to other days.

The weather specific transaction number statistics section14313stores statistical data that represents the number of transactions at each time (for example, the number of transactions per hour) for each type of weather (sunny, cloudy, rainy, snowy, a day of strong wind, a day of light wind, a day of high humidity, a day of low humidity, and the like). With this statistical data, a time range in which the number of transactions is large, and a time range in which the number of transactions is small during one day can be found for each type of weather. In addition, the number of transactions at each time can be found for each type of weather. In addition, differences in the number of transactions can be found for each type of weather compared to other types of weather.

The special sale day specific transaction number statistics section14314stores statistical data that represents the number of transactions at each time (for example, the number of transactions per hour) if the day is a special sale day when a special sale is held. With this statistical data, a time range in which the number of transactions is large, and a time range in which the number of transactions is small during one special sale day can be found. In addition, the number of transactions at each time on a special sale day can be found. In addition, differences in the number of transactions on a special sale day compared to an ordinary day which is not a special sale day can be found.

The event specific transaction number statistics section14315stores statistical data that represents the number of transactions at each time (for example, the number of transactions per hour) in the case of holding an event (for example, a morning fair or a limited-time sale) and the case of not holding an event. With this statistical data, a time range in which the number of transactions is large, and a time range in which the number of transactions is small during one day in the case of holding an event and the case of not holding an event can be found. In addition, the number of transactions at each time in the case of holding an event and the case of not holding an event can be found. In addition, differences in the number of transactions in the case of holding an event and the case of not holding an event can be found.

The daily transaction item number statistics section14316stores statistical data that represents the number of items in transactions at each time (for example, the number of items in transactions per hour). With this statistical data, a time range in which the number of items in transactions is large, and a time range in which the number of items in transactions is small during one day can be found. In addition, the number of items in transactions at each time can be found for each day in a predetermined period (for example, the first to the thirtieth (or the thirty-first) of each month). In addition, differences in the number of items in transactions for each time compared to other times can be found.

The day-of-week specific transaction item number statistics section14317stores statistical data that represents the number of items in transactions at each time (for example, the number of items in transactions per hour) for each day (Sunday to Saturday). With this statistical data, a time range in which the number of items in transactions is large, and a time range in which the number of items in transactions is small during one day can be found for each day of the week. In addition, the number of items in transactions at each time can be found for each day of the week. In addition, differences in the number of items in transactions can be found for each day of the week compared to other days of the week.

The weather specific transaction item number statistics section14318stores statistical data that represents the number of items in transactions at each time (for example, the number of items in transactions per hour) for each type of weather (sunny, cloudy, rainy, snowy, strong wind, light wind, high humidity, low humidity, and the like). With this statistical data, a time range in which the number of items in transactions is large, and a time range in which the number of items in transactions is small during one day can be found for each type of weather. In addition, the number of items in transactions at each time can be found for each type of weather. In addition, differences in the number of items in transactions can be found for each type of weather compared to other types of weather.

The special sale day specific transaction item number statistics section14319stores statistical data that represents the number of items in transactions at each time (for example, the number of items in transactions per hour) if the day is a special sale day when a special sale is held. With this statistical data, a time range in which the number of items in transactions is large, and a time range in which the number of items in transactions is small during one special sale day can be found. In addition, the number of items in transactions at each time on a special sale day can be found. In addition, differences in the number of items in transactions on a special sale day compared to an ordinary day which is not a special sale day can be found.

The event specific transaction item number statistics section14320stores statistical data that represents the number of items in transactions at each time (for example, the number of items in transactions per hour) in the case of holding an event (for example, a morning fair or a limited-time sale) and the case of not holding an event. With this statistical data, a time range in which the number of items in transactions is large, and a time range in which the number of items in transactions is small during one day in the case of holding an event and the case of not holding an event can be found. In addition, the number of items in transactions at each time in the case of holding an event and the case of not holding an event can be found. In addition, differences in the number of items in transactions in the case of holding an event and the case of not holding an event can be found.

The server1estimates a change in the number of customers visiting the store T on the current day based on the number of transactions, the number of items in transactions, the year, the month, the date, and the day of the week (for example, the current day) when the number of customers is estimated, the presence of a special sale or an event, and the meteorological information acquired from the weather forecasting company, which are stored in the base data section1431.

Next, the stored money statistics section1432will be described. The stored money statistics section1432includes a daily money storage statistics section14321, a day-of-week specific money storage statistics section14322, a weather specific money storage statistics section14323, a special sale day specific money storage statistics section14324, and an event specific money storage statistics section14325.

The daily money storage statistics section14321stores statistical data that represents the number of pieces of each type of money (for example, the number of pieces of each type of money per hour) stored in the automatic change machine5at each time. With this statistical data, a time range in which the amount of each type of stored money is large, and a time range in which the amount of each type of stored money is small in the automatic change machine5during one day can be found. In addition, the amount of each type of money stored in the automatic change machine5at each time can be found for each day in a predetermined period (for example, the first to the thirtieth (or the thirty-first) of each month). In addition, differences in each type of stored money for each time compared to other times can be found.

The day-of-week specific money storage statistics section14322stores statistical data that represents the number of pieces of each type of money at each time (for example, the number of pieces of each type of money per hour) stored in the automatic change machine5for each day of the week. With this statistical data, a time range in which the amount of each type of stored money is large, and a time range in which the amount of each type of stored money is small in the automatic change machine5during one day can be found for each day of the week. In addition, the amount of each type of money stored in the automatic change machine5at each time can be found for each day of the week. In addition, differences in each type of stored money can be found for each day of the week compared to other days of the week.

The weather specific money storage statistics section14323stores statistical data that represents the number of pieces of each type of money at each time (for example, the number of pieces of each type of money per hour) stored in the automatic change machine5for each type of weather. With this statistical data, a time range in which the amount of each type of stored money is large, and a time range in which the amount of each type of stored money is small in the automatic change machine5during one day can be found for each type of weather. In addition, each type of money stored in the automatic change machine5at each time can be found for each type of weather. In addition, differences in each type of stored money can be found for each type of weather compared to other types of weather.

The special sale day specific money storage statistics section14324stores statistical data that represents the number of pieces of each type of money at each time (for example, the number of pieces of each type of money per hour) stored in the automatic change machine5on a special sale day. With this statistical data, a time range in which the amount of each type of stored money is large, and a time range in which the amount of each type of stored money is small in the automatic change machine5during one special sale day can be found. In addition, each type of money stored in the automatic change machine5at each time on a special sale day can be found. In addition, differences in each type of stored money on a special sale day compared to an ordinary day which is not a special sale day can be found.

The event specific money storage statistics section14325stores statistical data that represents the number of pieces of each type of money at each time (for example, the number of pieces of each type of money per hour) stored in the automatic change machine5on a day when an event is held. With this statistical data, a time range in which the amount of each type of stored money is large, and a time range in which the amount of each type of stored money is small in the automatic change machine5during one day when an event is held can be found. In addition, each type of money stored in the automatic change machine5at each time on a day when an event is held can be found. In addition, differences in each type of stored money on a day when an event is held compared an ordinary day when an event is not held can be found.

The server1predicts the time period for refilling money and the time period for collecting money in the automatic change machine5by estimating the number of customers visiting the store T based on the statistical number of transactions and the statistical number of items in transactions stored in the base data section1431, and also using the statistical number of pieces of each type of money stored in the automatic change machine5, which is stored in the stored money statistics section1432.

Specifically, statistical data that represents the number of transactions on the same day as the current day is extracted from the daily transaction number statistics section14311. Statistical data that represents the number of transactions on the same day of the week as the current day is extracted from the day-of-week specific transaction number statistics section14312. Statistical data that represents the number of transactions on a day having the same type of weather as the weather forecast of the current day is extracted from the weather specific transaction number statistics section14313based on the meteorological information received from the server9installed in the weather forecasting company. If the current day is a special sale day, statistical data that represents the number of transactions on a special sale day is extracted from the special sale day specific transaction number statistics section14314. If the current day is not a special sale day, statistical data that represents the number of transactions on an ordinary day which is not a special sale day is extracted from the special sale day specific transaction number statistics section14314. If the current day is a day when an event is held, statistical data that represents the number of transactions on a day when an event is held is extracted from the event specific transaction number statistics section14315. If the current day is not a day when an event is held, statistical data that represents the number of transactions on a day other than a day when an event is held is extracted from the event specific transaction number statistics section14315.

Statistical data that represents the number of items in transactions on the same day as the current day is extracted from the daily transaction item number statistics section14316. Statistical data that represents the number of items in transactions on the same day of the week as the current day is extracted from the day-of-week specific transaction item number statistics section14317. Statistical data that represents the number of items in transactions on a day having the same type of weather as the weather forecast of the current day is extracted from the weather specific transaction item number statistics section14318based on the meteorological information received from the server9. If the current day is a special sale day, statistical data that represents the number of items in transactions on a special sale day is extracted from the special sale day specific transaction item number statistics section14319. If the current day is not a special sale day, statistical data that represents the number of items in transactions on a day other than a special sale day is extracted from the special sale day specific transaction item number statistics section14319. If the current day is a day when an event is held, statistical data that represents the number of items in transactions on a day when an event is held is extracted from the event specific transaction item number statistics section14320. If the current day is not a day when an event is held, statistical data that represents the number of items in transactions on a day other than a day when an event is held is extracted from the event specific transaction item number statistics section14320.

A quiet time period and a crowded time period of the current day for customers in the store T are estimated based on the extracted statistical data. Specifically, for example, the number of customers visiting on the current day is estimated as the average value of the extracted statistical data. In addition, for example, priorities are assigned to the statistical data, and the number of customers visiting on the current day is estimated as the average value of the statistical data that is weighted in order of priority. The quiet time period and the crowded time period of the current day for customers in the store T are estimated based on the estimated number of customers visiting on the current day. The quiet time period is estimated as a time period when the number of customers visiting the store is the smallest. The crowded time period is estimated as a time period when the number of customers visiting the store is the largest.

Next, a time period of a state where the storage unit is almost filled to capacity with money (hereinafter, referred to as “near full,” i.e., a state where the storage unit is not filled yet but will be filled soon), and a time period of a state where the storage unit in which money is stored is almost empty (hereinafter, referred to as “near empty,” i.e., a state where the storage unit is not empty yet but will become empty soon) are estimated for each type of money based on the statistical number of pieces of each type of money stored in the automatic change machine5.

Specifically, statistical data that represents a statistical number of pieces of each type of money stored in the automatic change machine5on the same day as the current day is extracted from the daily money storage statistics section14321. Statistical data that represents a statistical number of pieces of each type of money stored in the automatic change machine5on the same day of the week as the current day is extracted from the day-of-week specific money storage statistics section14322. Statistical data that represents a statistical number of pieces of each type of money stored in the automatic change machine5on a day having the same type of weather as the weather forecast of the current day is extracted from the weather specific money storage statistics section14323based on the meteorological information received from the server9. If the current day is a special sale day, statistical data that represents a statistical number of pieces of each type of money stored in the automatic change machine5on a special sale day is extracted from the special sale day specific money storage statistics section14324. If the current day is not a special sale day, statistical data that represents a statistical number of pieces of each type of money stored in the automatic change machine5on a day other than a special sale day is extracted from the special sale day specific money storage statistics section14324. If the current day is a day when an event is held, statistical data that represents a statistical number of pieces of each type of money stored in the automatic change machine5on a day when an event is held is extracted from the event specific money storage statistics section14325. If the current day is not a day when an event is held, statistical data that represents a statistical number of pieces of each type of money stored in the automatic change machine5on a day other than a day when an event is held is extracted from the event specific money storage statistics section14325.

The near full time period and the near empty time period of the current day for the storage unit of the automatic change machine5are estimated based on the extracted statistical data. Specifically, for example, the near full time period and the near empty time period for the automatic change machine5are estimated based on the average value of the extracted statistical data. In addition, for example, priorities are assigned to the statistical data, and the near full time period and the near empty time period for the automatic change machine5are estimated based on the average value of the statistical data that is weighted in order of priority.

The “near full” is desirably a state slightly before the storage unit actually becomes full. That is, the near full time period is desirably a time period slightly before the storage unit is at maximum capacity. The “near empty” is desirably a state slightly before the storage unit actually becomes empty. That is, the near empty time period is desirably a time period slightly before the storage unit is empty. An appropriate refill time period for refilling money and an appropriate collection time period for collecting money are predicted based on the estimated quiet time period and the near full or near empty time period.

For example, if the estimated quiet time period and the near full time period approximately match each other, the matching time period is predicted as the collection time period for money. If the estimated quiet time period and the near empty time period approximately match each other, the matching time period is predicted as the refill time period for money. If the estimated quiet time period and the near full time period or the near empty time period do not match each other, a time period included in the quiet time period, or a time period that is between both time periods and is close to the quiet time period is predicted as the collection time period or the refill time period.

The server1predicts an appropriate refill time period or an appropriate collection time period in which the number of customers is relatively small, and transmits information in a displayable manner such that the POS terminal3can display the time period. The POS terminal3displays the appropriate refill time period or the appropriate collection time period based on the received information. By doing so, refill or collection of money in the automatic change machine5can be performed in an appropriate time period when the number of customers visiting the store T is relatively small.

The server1corrects the near empty or near full time period based on the statistical number of pieces of each type of money and the actual number of pieces of each type of money stored in the change management unit144. For example, the server1compares the statistical number of pieces of each type of money with the actual number of pieces of each type of money stored in the change management unit144. Consequently, if the statistical number of pieces of each type of money is larger than the actual number of pieces of each type of money, the server1corrects the near empty or near full time period to be later than the current estimated time period. The server1corrects the refill time period or the collection time period to be later than the current predicted time period. If the actual number of pieces of each type of money is larger than the statistical number of pieces of each type of money, the server1corrects the near empty or near full time period to be sooner than the current estimated time period. The server1corrects the refill time period or the collection time period to be sooner than the current predicted time period.

The refill time period or the collection time period may also be corrected by estimating the number of visiting customers through comparison of the statistical number of visiting customers with the actual number of visiting customers.

Next, the used receipt amount statistics section1433will be described. The used receipt amount statistics section1433includes a daily used receipt amount statistics section14331, a day-of-week specific used receipt amount statistics section14332, a weather specific used receipt amount statistics section14333, a special sale day specific used receipt amount statistics section14334, and an event specific used receipt amount statistics section14335.

The daily used receipt amount statistics section14331stores statistical data that represents the amount of use of the receipt paper at each time (for example, the amount of use of the receipt paper per hour). With this statistical data, a time range in which the amount of use of the receipt paper is large, and a time range in which the amount of use of the receipt paper is small in the POS terminal3during one day can be found. In addition, the amount of use of the receipt paper at each time in a predetermined period (for example, the first to the thirtieth (or the thirty-first) of each month) can be found. In addition, differences in the amount of use of the receipt paper for each time compared to other times can be found.

The day-of-week specific used receipt amount statistics section14332stores statistical data that represents the amount of use of the receipt paper at each time (for example, the amount of use of the receipt paper per hour) for each day of the week. With this statistical data, a time range in which the amount of use of the receipt paper is large, and a time range in which the amount of use of the receipt paper is small in the POS terminal3during one day can be found for each day of the week. In addition, the amount of use of the receipt paper at each time can be found for each day of the week. In addition, differences in the amount of use of the receipt paper can be found for each day of the week compared to other days of the week.

The weather specific used receipt amount statistics section14333stores statistical data that represents the amount of use of the receipt paper at each time (for example, the amount of use of the receipt paper per hour) for each type of weather. With this statistical data, a time range in which the amount of use of the receipt paper is large, and a time range in which the amount of use of the receipt paper is small in the POS terminal3during one day can be found for each type of weather. In addition, the amount of use of the receipt paper at each time can be found for each type of weather. In addition, differences in the amount of use of the receipt paper can be found for each type of weather compared to other types of weather.

The special sale day specific used receipt amount statistics section14334stores statistical data that represents the amount of use of the receipt paper at each time (for example, the amount of use of the receipt paper per hour) on a special sale day. With this statistical data, a time range in which the amount of use of the receipt paper is large, and a time range in which the amount of use of the receipt paper is small in the POS terminal3on a special sale day can be found. In addition, the amount of use of the receipt paper at each time on a special sale day can be found. In addition, differences in the amount of use of the receipt paper on a special sale day compared an ordinary day which is not a special sale day can be found.

The event specific used receipt amount statistics section14335stores statistical data that represents the amount of use of the receipt paper at each time (for example, the amount of use of the receipt paper per hour) on a day when an event is held. With this statistical data, a time range in which the amount of use of the receipt paper is large, and a time range in which the amount of use of the receipt paper is small in the POS terminal3on a day when an event is held can be found. In addition, the amount of use of the receipt paper at each time on a day when an event is held can be found. In addition, differences in the amount of use of the receipt paper on a day when an event is held compared an ordinary day when an event is not held can be found.

The server1predicts the replacement time period for the receipt paper stored in the receipt issuing device by estimating the number of customers visiting the store T based on the statistical number of transactions and the statistical number of items in transactions stored in the base data section1431, and also using the statistical amount of use of the receipt paper in the POS terminal3, which is stored in the used receipt amount statistics section1433.

Specifically, statistical data that represents a statistical amount of use of the receipt paper on the same day as the current day is extracted from the daily used receipt amount statistics section14331. Statistical data that represents a statistical amount of use of the receipt paper on the same day of the week as the current day is extracted from the day-of-week specific used receipt amount statistics section14332. Statistical data that represents a statistical amount of use of the receipt paper on a day having the same type of weather as the weather forecast of the current day is extracted from the weather specific used receipt amount statistics section14333based on the meteorological information received from the server9. If the current day is a special sale day, statistical data that represents the amount of use of the receipt paper on a special sale day is extracted from the special sale day specific used receipt amount statistics section14334. If the current day is a day other than a special sale day, statistical data that represents the amount of use of the receipt paper on a day other than a special sale day is extracted from the special sale day specific used receipt amount statistics section14334. If the current day is a day when an event is held, statistical data that represents the amount of use of the receipt paper on a day when an event is held is extracted from the event specific used receipt amount statistics section14335. If the current day is a day other than a day when an event is held, statistical data that represents the amount of use of the receipt paper on a day other than a day when an event is held is extracted from the event specific used receipt amount statistics section14335.

A time period of a state where the receipt paper stored in the receipt issuing device will be used up soon (hereinafter, referred to as “near end” (i.e., a state where the receipt paper is not used up yet but will be used up soon)”) is estimated based on the statistical change in the amount of use of the receipt paper. Specifically, for example, the near end time period of the current day for the receipt paper is estimated based on the average value of the extracted statistical data. In addition, for example, priorities are assigned to the statistical data, and the near end time period of the current day for the receipt paper is estimated based on the average value of the statistical data that is weighted in order of priority.

The “near end” is desirably a state slightly before an end of the receipt paper where a red band-shaped line is printed at both ends is reached. That is, the near end time period (time range) is desirably a time period slightly before the end of the receipt paper is reached. An appropriate replacement time period for replacing the receipt paper is predicted based on the estimated quiet time period and the near end time period.

For example, if the estimated quiet time period and the near end time period match approximately, the matching time period is predicted as the replacement time period. If the estimated quiet time period and the near end time period do not match, a time period included in the quiet time period, or a time period that is between both time periods and is close to the quiet time period is predicted as the replacement time period.

The server1predicts an appropriate replacement time period in which the number of customers is relatively small, and transmits information in a displayable manner such that the POS terminal3can display the time period. The POS terminal3displays) the optimal replacement time period based on the received information. By doing so, the receipt paper in the POS terminal3can be replaced in a time period when the number of customers visiting the store T is relatively small.

The server1corrects the near end time period for the receipt paper based on the statistical amount of use of the receipt paper and the actual amount of use of the receipt paper stored in the receipt management unit145. Specifically, the server1compares the statistical c amount of use of the receipt paper with the actual amount of use of the receipt paper stored in the receipt management unit145. Consequently, if the statistical amount of use of the receipt paper is larger than the actual amount of use of the receipt paper, the server1corrects the near end time period to be later than the current estimated time period. The server1corrects the replacement time period to be later than the current predicted time period. If the actual amount of use of the receipt paper is larger than the statistical amount of use of the receipt paper, the server1corrects the near end time period to be sooner than the current estimated time period. The server1corrects the replacement time period to be sooner than the current predicted time period.

The replacement time period may also be corrected by estimating the number of visiting customers through comparison of the statistical number of visiting customers with the actual number of visiting customers.

Hereinafter, the POS terminal3will be described.FIG. 4is a perspective view illustrating the POS terminal. InFIG. 4, the POS terminal3includes a main body46and a combination keyboard45. An operator-use display device38, the printing device40as the receipt issuing device, a code reader42, and the like are disposed in the main body46. In addition, the main body46includes a control unit300, a customer-use display device39(refer toFIG. 5), and the like. The operator-use display device38displays information to an operator. The customer-use display device39displays information to customers. For example, the printing device40is equipped with a thermal head and issues receipts by printing information using the thermal head on the receipt paper that is thermal paper. The code reader42reads symbols assigned to commodities. The POS terminal3acquires the commodity code specifying each commodity based on the read symbols. The code reader42may specify commodities using a general object recognition technology based on captured images of commodities.

The combination keyboard45can be detached from the main body46. The combination keyboard45includes an operation unit37, a subdisplay device44, and a card reader41. The operation unit37is a keyboard that includes a payment key371. The payment key371is operated at the time of announcing the payment in a transaction with a customer. The subdisplay device44displays information to the operator. The subdisplay device44displays supplementary information, communication information regarding the store, and the like that are not displayed on the operator-use display device38. The subdisplay device44displays the collection time period or the refill time period for collecting or refilling money, or the replacement time period for replacing the receipt paper as a message to the operator.

Next, a hardware configuration of the POS terminal3will be described.FIG. 5is a block diagram illustrating a hardware configuration of the POS terminal3. As illustrated inFIG. 5, the POS terminal3includes a CPU31, a ROM32, a RAM33, a memory unit34, and the like. The CPU31is a main unit of control. The ROM32stores various programs. Programs and various types of data are loaded into the RAM33. The memory unit34stores various programs. The CPU31, the ROM32, the RAM33, and the memory unit34are connected to each other through a bus35. The CPU31, the ROM32, and the RAM33constitute the control unit300. That is, the control unit300executes a control, described later, related to the POS terminal3by operating the CPU31in accordance with a control program that is stored in the ROM32or the memory unit34and loaded into the RAM33.

The RAM33includes a commodity information section331. The commodity information section331stores the commodity information (a commodity name, a price of a commodity, and the like) related to commodities that are subjected to the sales registration based on the commodity code acquired from symbols read by the code reader42.

The memory unit34is a non-volatile memory device such as an HDD or a flash memory that retains stored information even if power is off. The memory unit34includes a control program341, a commodity master342, and the like. The control program section341is the control program that is used for controlling the POS terminal3. For each commodity code specifying a commodity, the commodity master342stores the commodity information related to the commodity.

The control unit300is connected to the operation unit37, the operator-use display device38, the customer-use display section39, the subdisplay device44, the printing device40, the card reader41, and the code reader42through the bus35and a controller36.

The control unit300is also connected to a communication interface (I/F)43through the bus35. The communication interface43is communicably connected to the server1and the other POS terminals3through the communication line N1.

Hereinafter, control of the server1and the POS terminal3will be described. First, control of the server1will be described.FIG. 6is a function block diagram illustrating a functional configuration of the server1. In accordance with the control program stored in the ROM12or the control program141stored in the memory unit14, the control unit100functions as a prediction unit101, a first output unit102, a first correction unit103, a replacement prediction unit104, a second output unit105, and a second correction unit106.

The prediction unit101has a function of predicting at least one of an appropriate collection time period for collecting money stored in the automatic change machine5or an appropriate refill time period for refilling money in the automatic change machine5based on the first statistical information (i.e., the statistical information related to the number of customers visiting the store T at the time, which is stored in the base data section1431), and the second statistical information (i.e., the statistical information related to the amount of money stored in the automatic change machine5at the time, which is stored in the stored money statistics section1432).

The first output unit102has a function of transmitting at least one of the predicted collection time period or the predicted refill time period to the POS terminal3in a displayable manner.

The first correction unit103has a function of correcting at least one of the collection time period for money or the refill time period predicted by the prediction unit101based on the actual number of pieces of each type of money stored in the automatic change machine5.

The replacement prediction unit104has a function of predicting an appropriate replacement time period for replacing the stored receipt paper based on the first statistical information (i.e., the statistical change in the number of customers visiting the store T at the time, which is stored in the base data section1431), and the third statistical information (i.e., the statistical change in the amount of use of the receipt paper at the time, which is stored in the used receipt amount statistics section1433).

The second output unit105has a function of transmitting information related to the predicted replacement time period to the POS terminal3in a displayable manner.

The second correction unit106has a function of correcting the replacement time period predicted by the replacement prediction unit104based on the actual amount of use of the stored receipt paper.

Next, a control processing performed by the server1for predicting the refill time period and the collection time period will be described.FIG. 7is a flowchart illustrating the flow of the processing performed by the server1for predicting the refill time period and the collection time period in the automatic change machine5. InFIG. 7, the control unit100determines whether or not a predetermined timing is reached (Act11). The determination of whether the predetermined timing is reached in Act11is performed at, for example, a time slightly before the opening of the store T. At this timing, the collection time period and the refill time period of the current day in the automatic change machine5are predicted. If the control unit100determines that the predetermined timing is reached (Yes in Act11), the control unit100executes prediction (Act12). The control unit100returns to Act11.

FIG. 8is a flowchart illustrating the prediction processing performed by the control unit100in Act12. InFIG. 8, the control unit100acquires base data related to the statistical number of transactions and number of items in transactions from the base data section1431of the statistics section143based on the year, the month, the date, and the day of the week of the current day, the presence of a special sale, the presence of an event, the meteorological information, and the like (Act31). The control unit100finds the number of transactions on the current day and the number of items in transactions on the current day from the acquired base data. The control unit100estimates the number of customers visiting the store T on the current day from the found number of transactions and number of items in transactions. The control unit100estimates the quiet time period and the crowded time period of the current day based on the estimated number of visiting customers (Act32). Next, the control unit100acquires the statistical information related to money stored in the automatic change machine5from the stored money statistics section1432based on the year, the month, the date, and the day of the week of the current day, the presence of a special sale, the presence of an event, the meteorological information, and the like (Act33). The control unit100finds the number of pieces of money stored in the automatic change machine5from the acquired information. The control unit100estimates the near empty time period and the near full time period for the automatic change machine5based on the estimated number of pieces of money (Act34). The control unit100(prediction unit101) predicts the refill time period and the collection time period for the automatic change machine5based on the estimated quiet time period and the estimated near empty time period and the near full time period (Act35).

Next, the control unit100creates image data of a graph that visualizes information related to the estimated change in the number of customers and the predicted refill time period and the predicted collection time period (Act36). The control unit100(first output unit102) transmits the created image data of the graph to the POS terminal3(Act37).

Returning toFIG. 7again, if the control unit100in Act11determines that the predetermined timing is not reached (No in Act11), the control unit100determines whether or not a predetermined time period (for example, one hour) elapses from the predetermined timing in Act11(or the opening time of the store) (Act13). If the control unit100determines that the predetermined time period elapses (Yes in Act13), the control unit100executes a correction processing (Act14). The control unit100then returns to Act11.

FIG. 9is a flowchart illustrating the correction processing performed by the control unit100in Act14. InFIG. 9, the control unit100acquires correction data (Act41). The correction data is information that is stored in the change management unit144and related to each type of money actually stored in the automatic change machine5. Next, the control unit100compares the statistical number of pieces of each type of money with the actual number of pieces of each type of money stored in the change management unit144. The control unit100determines whether or not the refill time period and the collection time period for money need to be corrected based on the result of comparison (Act43). If there is no difference between the statistical number of pieces of each type of money and the actual number of pieces of each type of money stored in the change management unit144, the control unit100determines that the refill time period and the collection time period do not need to be corrected. If there is a difference between the statistical number of pieces of each type of money and the actual number of pieces of each type of money stored in the change management unit144, the control unit100determines that the refill time period and the collection time period need to be corrected.

If the control unit100determines that the refill time period and the collection time period need to be corrected (Yes in Act43), the control unit100estimates the near empty time period and the near full time period for the automatic change machine5again based on the difference. The control unit100(first correction unit103) corrects the refill time period and the collection time period predicted in Act35for money in the automatic change machine5based on the estimated near empty time period and the near full time period, and information related to the number of visiting customers (Act44).

Next, the control unit100corrects the image data of the graph created in Act36based on the corrected refill time period and collection time period (Act45). The control unit100transmits the corrected image data of the graph to the POS terminal3(Act46). If the control unit100determines that the refill time period and the collection time period do not need to be corrected (No in Act43), the control unit100returns to Act11without processing Act44to Act46.

Returning toFIG. 7again, if the control unit100in Act13determines that the predetermined time period does not elapse (No in Act13), the control unit100determines whether or not the predicted time period for refill or collection predicted in Act35or the predicted time period corrected in Act44is reached (Act15). If the control unit100determines that the predicted time period is reached (Yes in Act15), the control unit100transmits message data representing a message to the POS terminal3(Act16). If the predicted time period is for refilling money, the control unit100transmits message data indicating a message that prompts refilling money. If the predicted time period is for collecting money, the control unit100transmits message data indicating a message that prompts collecting money. The control unit100returns to Act11.

If the control unit100determines that the predicted time period for refill or collection of money is not reached (No in Act15), the control unit100determines whether or not a signal indicating that refill or collection of money is performed is received from the POS terminal3(Act17). If the control unit100determines that the signal is received (Yes in Act17), the control unit100stores the amount and the number of pieces of refilled or collected money in the RAM13(Act18). The control unit100returns to Act11.

If the control unit100determines that the signal indicating that refill or collection of money is performed is not received (No in Act17), the control unit100determines whether or not a predetermined time that is set in advance is reached (Act20). If the control unit100determines that the predetermined time is reached (Yes in Act20), the control unit100transmits amount information stored in the RAM13to the server7in the security company (Act21). The control unit100returns to Act11. If the control unit100determines that the predetermined time is not reached (No in Act20), the control unit100returns to Act11.

If money for change and the like are needed again, the security company that receives the amount information withdraws money from the bank and transports the money to the store T. If there is money to be collected from the store T, the security company visits the store T to collect the money.

Next, control of the POS terminal3will be described.FIG. 10is a flowchart illustrating the flow of the processing performed by the POS terminal. InFIG. 10, the control unit300determines whether or not the commodity code is acquired based on the symbols read by the code reader42(Act51). If the control unit300determines that the commodity code is acquired (Yes in Act51), the control unit300searches the commodity master342based on the commodity code, acquires the commodity information related to the commodity specified by the commodity code, and stores the commodity information in the commodity information section331(Act52). The control unit300returns to Act51.

If the control unit300determines that the commodity code is not acquired (No in Act51), the control unit300determines whether or not the payment key371is operated (Act53). If the control unit300determines that the payment key371is operated (Yes in Act53), the control unit300executes the payment processing for the transaction based on the commodity information stored in the commodity information section331and money received from the customer (Act54). Next, the control unit300transmits the change information to the automatic change machine5. The control unit300receives data of the current inventory of each type of money (reflecting deposits and withdrawals) from the automatic change machine (Act55). The current inventory is information related to money stored in the automatic change machine5. The current inventory is a numerical value as data and is calculated based on the amount of preparatory money for change, the amount of deposited money, and the amount of withdrawn money. The current inventory data is stored in the automatic change machine5and includes the number of pieces and the amount of each type of money. Each time there is a deposit or a withdrawal of money, the automatic change machine5updates the current inventory data to up-to-date data. Next, the control unit300transmits the commodity information and the payment information related to the payment, and the current inventory data received from the automatic change machine5to the server1(Act56). The control unit300returns to Act51.

If the control unit300in Act53determines that the payment key371is not operated (No in Act53), the control unit300determines whether or not the image data of the graph transmitted by the server1in the process of Act37or the process of Act46is received (Act61). If the control unit300determines that the image data of the graph is received (Yes in Act61), the control unit300displays an image graph based on the image data of the graph on the subdisplay device44(Act62). The control unit300returns to Act51. The control unit300may display the graph image on the operator-use display device38instead of the subdisplay device44.

FIG. 11is one example of a graph image G displayed in Act62. As illustrated inFIG. 11, the graph image G includes a horizontal axis as a time axis from the opening to the closing of the store T, and a vertical axis as the number of visiting customers. A line G1illustrated in the graph image G represents a change in the number of visiting customers at each time during one day. In the example inFIG. 11, the number of customers continues increasing from the opening time of the store and reaches a first peak (position of G7) at around 12:00. In the afternoon, the number of customers starts to decrease and reaches a bottom (position of G9) at around 15:00. Then, until the evening, the number of customers is increased again and reaches a second peak (position of G8) at around 18:00. Then, the number of customers is decreased until the closing time of the store and reaches a second bottom (position of G10) at a time immediately before the closing of the store. That is, the store T has the crowded time period near times G7and G8, and has the quiet time period near times G9and G10.

The time range of an event on the current day is also illustrated inFIG. 11. In the example inFIG. 11, a morning fair G2is held in a time range of 09:00 to 10:00, and a limited-time sale G3is held in a time range of 17:00 to 18:00.

In the example inFIG. 11, a time range G11that includes a quiet time period G9is predicted as a refill time period G4. A time range G12that includes a quiet time period G10is predicted as a collection time period G5. The operator or a person in charge can view the graph image G and confirm the refill time period G4and the collection time period G5. By performing refill and collection of money during the confirmed time period in which the number of customers is relatively small, influence on the customers can be minimized.

Returning toFIG. 10again, if the control unit300in Act61determines that the image data of the graph is not received (No in Act61), the control unit300determines whether or not the message data transmitted by the server1in Act16is received (Act63). If the control unit300determines that the message data is received (Yes in Act63), the control unit300displays the message indicated by the message data on the subdisplay device44(Act64). The control unit300returns to Act51.

As illustrated inFIG. 11, the control unit300displays the message displayed in the process of Act64in a lower part G6of the graph image G. The operator or the person who performs refill or collection of money can view and remember to comply with the message. In addition, the operator or the person who forgets to perform refill or collection of money can view the message and recall that refill or collection of money is to be performed.

Returning toFIG. 10again, if the control unit300in Act63determines that the message data is not received (No in Act63), the control unit300determines whether or not refill or collection of money from the automatic change machine5is executed (Act65). If the control unit300determines that refill or collection of money is executed (Yes in Act65), the control unit300removes the message displayed in the lower part G6of the graph image G (Act66). The control unit300transmits the amount and the number of pieces of money refilled or collected to the server1(Act67). The control unit300returns to Act51. If the control unit300determines that the signal indicating that refill or collection of money is executed is not received (No in Act65), the control unit300returns to Act51.

According to the embodiment, the server1can predict an appropriate refill time period or a collection time period for the automatic change machine5and transmit the refill time period or the collection time period to the POS terminal3.

Hereinafter, a processing performed by the server1for predicting the replacement time period for replacing the receipt paper stored in the POS terminal3will be described usingFIG. 12toFIG. 14. InFIG. 12toFIG. 14, descriptions of parts corresponding to the description ofFIG. 7toFIG. 9will not be repeated or will be simplified. The printing device40which is the receipt issuing device is indirectly connected to the server1.FIG. 12is a flowchart illustrating the flow of processing performed by the server1for predicting the replacement time period for replacing the receipt paper. As illustrated inFIG. 12, the control unit100determines whether or not a predetermined timing is reached (Act71). The predetermined timing in Act71is, for example, a time slightly before the opening of the store T. At this timing, the replacement time period for replacing the receipt paper is predicted. If the control unit100determines that the predetermined timing is reached (Yes in Act71), the control unit100executes prediction (Act72). The control unit100returns to Act71.

FIG. 13is a flowchart illustrating the prediction processing by the control unit100in Act72. InFIG. 13, the control unit100processes Act91and Act92. Since these processes are the same as Act31and Act32, such descriptions will not be repeated. Next, the control unit100acquires the statistical information related to the amount of use of the receipt paper from the used receipt amount statistics section1433based on the year, the month, the date, and the day of the week of the current day, the presence of a special sale, the presence of an event, the meteorological information, and the like (Act93). The control unit100finds the amount of use of the receipt paper from the acquired information. The control unit100estimates the near end time period for the receipt paper based on the found amount of use of the receipt paper (Act94). The control unit100(replacement prediction unit104) predicts the replacement time period for replacing the receipt paper based on the estimated quiet time period and the estimated near end time period (Act95).

Next, the control unit100creates image data of a graph that visualizes information related to the estimated number of customers and the predicted replacement time period for replacing the receipt paper (Act96). The control unit100(second output unit105) transmits the created image data of the graph to the POS terminal3(Act97).

Returning toFIG. 12again, if the control unit100in Act71determines that the predetermined timing is not reached (No in Act71), the control unit100determines whether or not a predetermined time period (for example, one hour) elapses from the predetermined timing in Act71(or the opening time of the store) (Act73). If the control unit100determines that the predetermined time period elapses (Yes in Act73), the control unit100executes correction (Act74). The control unit100returns to Act71.

FIG. 14is a flowchart illustrating the correction processed by the control unit100in Act74. InFIG. 14, the control unit100acquires correction data (Act101). The correction data is information related to the actual amount of use of the receipt paper stored in the receipt management unit145. Next, the control unit100compares the statistical amount of use of the receipt paper with the actual amount of use of the receipt paper stored in the receipt management unit145. The control unit100determines whether or not the replacement time period needs to be corrected based on the result of comparison (Act103). If there is no difference between the statistical amount of use of the receipt paper and the actual amount of use of the receipt paper stored in the receipt management unit145, the control unit100determines that the replacement time period for the receipt paper does not need to be corrected. If there is a difference between the statistical amount of use of the receipt paper and the actual amount of use of the receipt paper stored in the receipt management unit145, the control unit100determines that the replacement time period for the receipt paper needs to be corrected.

If the control unit100determines that the replacement time period for the receipt paper needs to be corrected (Yes in Act103), the control unit100estimates the near end time period for the receipt paper again based on the difference. The control unit100(second correction unit106) corrects the replacement time period predicted in Act95based on the near end time period estimated again and information related to the number of visiting customers (Act104).

Next, the control unit100corrects the image data of the graph created in Act96based on the corrected replacement time period (Act105). The control unit100transmits the corrected image data of the graph to the POS terminal3(Act106). If the control unit100determines that the replacement time period does not need to be corrected (No in Act103), the control unit100returns to Act71without processing Act104to Act106.

Returning toFIG. 12again, if the control unit100in Act73determines that the predetermined time period does not elapse (No in Act73), the control unit100determines whether or not the predicted time period for replacement of the receipt paper predicted in Act95or the predicted time period corrected in Act104is reached (Act75). If the control unit100determines that the predicted time period is reached (Yes in Act75), the control unit100transmits message data representing a message to the POS terminal3(Act76). In this case, the control unit100transmits message data indicating a message that prompts replacement of the receipt paper. The control unit100returns to Act71.

If the control unit100determines that the predicted time period for replacement of the receipt paper is not reached (No in Act75), the control unit100determines whether or not a signal indicating that the receipt paper is replaced is received from the POS terminal3(Act77). If the control unit100determines that the signal is received (Yes in Act77), the control unit100stores the fact that the receipt paper is replaced in the RAM13(Act78). The RAM13cumulatively stores the number of times the receipt paper is replaced. The control unit100returns to Act71.

If the control unit100determines that the signal indicating that the receipt paper is replaced is not received (No in Act77), the control unit100determines whether or not the number of sheets or rolls of the receipt paper stored in the store T is less than a predetermined number, and refill of the receipt paper is needed (Act80). If the control unit100determines that refill of the receipt paper is needed (Yes in Act80), the control unit100orders receipt paper from a supplier (Act81). The control unit100returns to Act71. If the control unit100determines that refill of the receipt paper is not needed (No in Act80), the control unit100returns to Act71.

Next, control of the POS terminal3will be described.FIG. 15is a flowchart illustrating the processing performed by the POS terminal. InFIG. 15, descriptions of parts corresponding to the description ofFIG. 10will not be repeated or will be simplified. InFIG. 15, the control unit300processes Act111to Act114. Since Act111to Act114are the same as Act51to Act54, such descriptions will not be repeated. Next, the control unit300acquires the amount of receipt paper issued (Act115). For example, if payment is made in cash, one sheet of the receipt paper is issued. If payment is made by credit card, two sheets of the receipt paper, including one sheet to be given to the customer and one store copy, are issued. The amount of receipt paper issued may be increased by issuing coupons using the receipt paper. Next, the control unit300transmits the commodity information and the payment information related to the payment, and data of the amount of receipt paper issued to the server1(Act116). The control unit300returns to Act111.

While a detailed description is not provided, the amount of receipt paper issued is acquired as needed if the receipt paper is issued at a time other than a transaction with a customer such as issuing an inspection or settlement report.

If the control unit300in Act113determines that the payment key371is not operated (No in Act113), the control unit300processes Act121to Act124. Since Act121to Act124are the same as Act61to Act64, such descriptions will not be repeated.

If the control unit300in Act123determines that the message data is not received (No in Act123), the control unit300determines whether or not the receipt paper is replaced from the POS terminal3(Act125). If the control unit300determines that the receipt paper is replaced (Yes in Act125), the control unit300removes the message that is displayed in the lower part G6of the graph image G and prompts replacement of the receipt paper (Act126). The control unit300transmits a signal indicating the fact that the receipt paper is replaced to the server1(Act127). The control unit300returns to Act111. If the control unit300determines that the receipt paper is not replaced (No in Act125), the control unit300returns to Act111.

In the description of the embodiment, the server1predicts the refill time period for refilling money, the collection time period for collecting money, and the replacement time period for replacing the receipt paper for one connected POS terminal3for simplification of description. However, in actuality, the server1executes the same prediction for the plurality of connected POS terminals3.

For example, in the embodiment, the crowded time period and the quiet time period are estimated based on the number of customers visiting the store. Instead, the crowded time period and the quiet time period may be estimated using the number of deployed POS terminals3and the number of customers visiting the store.

In the embodiment, the refill time period and the collection time period are predicted based on the base data and the actual number of pieces of money stored in the automatic change machine5, which is stored in the change management unit144. Instead, for example, the refill time period and the collection time period may be predicted based on the ratio of payment in cash to the number of payments. The ratio of payment in cash to the number of payments tends to be proportional to the number of pieces of money stored in the automatic change machine5. For example, if the ratio of payment in cash is higher than statistical data, the number of pieces of money stored in the automatic change machine5tends to be increased. Thus, if the ratio of payment in cash is high, the refill time period for money is corrected to be slightly sooner.

In the embodiment, the process of refill or collection of money and the process of replacement of the receipt paper are described using different flowcharts. Instead, the process of refill or collection of money may be performed at the same time as the process of replacement of the receipt paper.

In the embodiment, the server1is described as one example of the prediction and management apparatus. Alternatively, the POS terminal3may be the prediction and management apparatus. In this case, the first output unit and the second output unit output information to the subdisplay device44in a reportable manner. In a self-checkout POS terminal where customers perform the sales registration and the payment, the first output unit and the second output unit controlled by the POS terminal may output information to an attendant PC and the like managing the self-checkout POS terminal in a reportable manner. If the POS terminal3is the prediction and management apparatus, the automatic change machine5and the printing device40are directly connected to the POS terminal3. Even if the receipt issuing device is a printing device that is electrically connected to the POS terminal3, the printing device is directly connected to the POS terminal3.

In the embodiment, the server1creates the image data of the graph that visualizes the predicted refill time period, the predicted collection time period, and the predicted replacement time period, and transmits the image data of the graph to the POS terminal3. Alternatively, the refill time period and the collection time period for money and the replacement time period for the receipt paper may be transmitted to the POS terminal3using a method other than the image of the graph.

In the embodiment, the first output unit102has a function of outputting information related to at least one of the predicted collection time period for collecting money or the predicted refill time period for refilling money to the POS terminal3in a displayable manner, and the second output unit105has a function of outputting information related to the predicted replacement time period for replacing the receipt paper to the POS terminal3in a displayable manner. However, one output unit that provides output to the POS terminal3from the server1may have the function of outputting information related to at least one of the predicted collection time period for collecting money or the predicted refill time period for refilling money to the POS terminal3in a displayable manner, and the function of outputting information related to the predicted replacement time period for replacing the receipt paper to the POS terminal3in a displayable manner. In this case, this one output unit functions as the first output unit102and also functions as the second output unit105.

The program executed in the server1of the embodiment is provided as a recording of an installable or executable file on a computer-readable recording medium such as a CD-ROM, a flexible disk (FD), a CD-R, or a digital versatile disk (DVD).

The program executed in the server1of the embodiment may be configured to be stored in a computer that is connected to a network such as the Internet, and provided as a download through the network. The program executed in the server1of the embodiment may be configured to be provided or distributed through a network such as the Internet.

The program executed in the server1of the embodiment may be configured to be provided by embedding the program in a ROM or the like.