US20200226878A1 - Fraudulence monitoring system of table game and fraudulence monitoring program of table game - Google Patents

Fraudulence monitoring system of table game and fraudulence monitoring program of table game Download PDF

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Publication number
US20200226878A1
US20200226878A1 US16/649,191 US201816649191A US2020226878A1 US 20200226878 A1 US20200226878 A1 US 20200226878A1 US 201816649191 A US201816649191 A US 201816649191A US 2020226878 A1 US2020226878 A1 US 2020226878A1
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United States
Prior art keywords
game
games
fraudulence
significant difference
control device
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US16/649,191
Inventor
Yasushi Shigeta
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Angel Group Co Ltd
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Angel Playing Cards Co Ltd
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Assigned to ANGEL PLAYING CARDS CO., LTD. reassignment ANGEL PLAYING CARDS CO., LTD. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: SHIGETA, YASUSHI
Assigned to Angel Group Co., Ltd. reassignment Angel Group Co., Ltd. CHANGE OF NAME (SEE DOCUMENT FOR DETAILS). Assignors: ANGEL PLAYING CARDS CO., LTD.
Abandoned legal-status Critical Current

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Classifications

    • GPHYSICS
    • G07CHECKING-DEVICES
    • G07FCOIN-FREED OR LIKE APPARATUS
    • G07F17/00Coin-freed apparatus for hiring articles; Coin-freed facilities or services
    • G07F17/32Coin-freed apparatus for hiring articles; Coin-freed facilities or services for games, toys, sports, or amusements
    • G07F17/3241Security aspects of a gaming system, e.g. detecting cheating, device integrity, surveillance
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63FCARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F5/00Roulette games
    • A63F5/0076Driving means
    • A63F5/0082Driving means electrical
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63FCARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F5/00Roulette games
    • A63F5/04Disc roulettes; Dial roulettes; Teetotums; Dice-tops
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/18Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/10Terrestrial scenes
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/50Context or environment of the image
    • G06V20/52Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • GPHYSICS
    • G07CHECKING-DEVICES
    • G07FCOIN-FREED OR LIKE APPARATUS
    • G07F17/00Coin-freed apparatus for hiring articles; Coin-freed facilities or services
    • G07F17/32Coin-freed apparatus for hiring articles; Coin-freed facilities or services for games, toys, sports, or amusements
    • G07F17/3202Hardware aspects of a gaming system, e.g. components, construction, architecture thereof
    • G07F17/3216Construction aspects of a gaming system, e.g. housing, seats, ergonomic aspects
    • G07F17/322Casino tables, e.g. tables having integrated screens, chip detection means
    • GPHYSICS
    • G07CHECKING-DEVICES
    • G07FCOIN-FREED OR LIKE APPARATUS
    • G07F17/00Coin-freed apparatus for hiring articles; Coin-freed facilities or services
    • G07F17/32Coin-freed apparatus for hiring articles; Coin-freed facilities or services for games, toys, sports, or amusements
    • G07F17/3225Data transfer within a gaming system, e.g. data sent between gaming machines and users
    • G07F17/3232Data transfer within a gaming system, e.g. data sent between gaming machines and users wherein the operator is informed
    • G07F17/3237Data transfer within a gaming system, e.g. data sent between gaming machines and users wherein the operator is informed about the players, e.g. profiling, responsible gaming, strategy/behavior of players, location of players
    • G07F17/3239Tracking of individual players
    • GPHYSICS
    • G07CHECKING-DEVICES
    • G07FCOIN-FREED OR LIKE APPARATUS
    • G07F17/00Coin-freed apparatus for hiring articles; Coin-freed facilities or services
    • G07F17/32Coin-freed apparatus for hiring articles; Coin-freed facilities or services for games, toys, sports, or amusements
    • G07F17/3244Payment aspects of a gaming system, e.g. payment schemes, setting payout ratio, bonus or consolation prizes
    • G07F17/3248Payment aspects of a gaming system, e.g. payment schemes, setting payout ratio, bonus or consolation prizes involving non-monetary media of fixed value, e.g. casino chips of fixed value
    • GPHYSICS
    • G07CHECKING-DEVICES
    • G07FCOIN-FREED OR LIKE APPARATUS
    • G07F17/00Coin-freed apparatus for hiring articles; Coin-freed facilities or services
    • G07F17/32Coin-freed apparatus for hiring articles; Coin-freed facilities or services for games, toys, sports, or amusements
    • G07F17/3286Type of games
    • G07F17/3293Card games, e.g. poker, canasta, black jack
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00Details of television systems
    • H04N5/76Television signal recording
    • H04N5/91Television signal processing therefor
    • H04N5/93Regeneration of the television signal or of selected parts thereof
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00Television systems
    • H04N7/18Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast

Definitions

  • the present disclosure relates to a fraudulence monitoring system of a table game in a game hall, and more particularly, to a technology for detecting a fraudulent act.
  • the game hall has surveillance cameras for monitoring fraudulent acts and prevents fraudulence by determining fraudulence during a game and fraudulence by collection or repayment of chips different from a win or lose result using images obtained from the surveillance cameras. Meanwhile, it is suggested to grasp an amount of chips by attaching an IC tag to each chip in order to grasp the number of betted chips and a total amount of betted chips.
  • PCT/JP2015/000171 discloses a card game monitoring system which determines whether chips placed on a game table are collected or repaid as a win or lose result by performing an image analysis on a movement of chips and monitors a fraudulent act.
  • the game table is recorded by the surveillance camera, and when the amount of money won at a time by a game participant is large, the recorded VTR is played to confirm whether or not there is a fraudulent act.
  • fraudulence such as sophisticated fraudulence acts in a game table and continuous winning of a small amount of money cannot be found by simply detecting that the game participant wins the large amount of money.
  • the related art does not sufficiently prevent a fraudulence act by collusion of a dealer and a player.
  • An object of the present disclosure is to prevent damage due to a fraudulent act by continuously monitoring an amount betted by a game participant and win or lose of a game, comparing data of a probability statistic calculation or past statistical data, and detecting a suspicious pattern suspected of being fraudulent.
  • a fraudulence monitoring system of a table game includes: a win and lose determination device which determines win and lose results for each game in a game table; a bet chip measuring device which grasps an amount of game tokens that a game participant bets on the game table in each game; and a management control device which stores the number of games performed on the game table and specifies positions and the amount of game tokens that the game participant places on the game table based on a measurement result by the bet chip measuring device in each game and stores the specified positions and amount of game tokens in each game participant or player positions of the game table, wherein the management control device includes a calculation function which compares results of an actual winning rate and a total return amount of the same person in each game participant or player position with figures obtained by a probability statistic calculation at the time of an end of a predetermined number of games, on the basis of a calculation on a total number of games in which the same person participates in each game participant or player position, a transition of bet chip amounts for each game,
  • the management control device may further include a function which specifies dealers in each game and include a function which specifies a dealer responsible for a series of games in which the significant difference occurs.
  • the management control device may include a calculation function which factorizes the total return amount in a series of games in which the significant difference occurs to specify whether an occurrence cause of the significant difference in the series of games in which the significant difference occurs is due to the winning rate or due to a magnitude of a betted amount of the bet chip.
  • the management control device may include a calculation function which stores the bet chip amounts for each game at the bet position having different return rates, and specifies whether the occurrence cause of the significant difference in a series of games in which the significant difference has occurred is associated with the bet position having different return rates.
  • the management control device may have a plurality of criteria which determine whether there is a significant difference and issue a different kind of warnings for each criterion.
  • the management control device may have different determination criteria of a different significant difference for the number of games divided by a predetermined rule or for each of the predetermined number of games and issue a different kind of warnings.
  • the management control device may determine whether there are significant differences for each game sequentially or every time the predetermined number of games is progressed in accordance with the progress of the plurality of games, and issue a warning when the determination criteria on the significant difference exceed.
  • the management control device may have a plurality of criteria which determine whether there is a significant difference and specify the game participant or the player position having the fraudulence possibility for each criterion to be able to display scores for each different criteria and display scores or ranks for warnings.
  • the management control device may obtain the figures obtained by the probability statistic calculation used to determine whether there is a significant difference based on a conditional probability calculation when a specific element is a fixed value.
  • the management control device may further include a function which sequentially grasps the spots from the playing cards or spots of dice from a series of games, and estimates the fraudulence cause in the case in which it is determined that there is a significant difference based on the data of the spots from a series of games and enumerates the fraudulence cause with the possibility.
  • the management control device may estimate the fraudulence cause determined that there is the significant difference using any one or both of big data on past games or past fraudulent data, and enumerate the cause with the fraudulence possibility.
  • a fraudulence monitoring system of a table game includes: an income and expenditure grasping device which grasps income and expenditure of a casino side for each game table in a plurality of game tables; and a management control device which stores the number of games performed on each game table and sequentially grasps and stores a transition of the income and expenditure of the casino side in each game, wherein the management control device includes a calculation function which compares results of the income or expenditure of the casino side with figures obtained by a probability statistic calculation at the time of an end of a predetermined number of games, on the basis of a calculation on a total number of games performed on each game table and the transition of the income and expenditure of the casino side in each game to determine whether there is a significant difference therebetween, and specifies any one of the game table or a room having the game table where the significant difference is occurring.
  • a fraudulence monitoring system of a table game includes: a win and lose determination device which determines win and lose results for each game in a game table; a bet chip measuring device which grasps an amount of game tokens that a game participant bets on the game table in each game; and a management control device which stores the number of games performed on the game table and specifies positions and the amount of game tokens that the game participant places on the game table using a measurement result by the bet chip measuring device in each game and stores the specified positions and amount of game tokens in each game participant or player positions of the game table, wherein the management control device includes artificial intelligence having past data of a fraudulent game taught as training data, and further includes a calculation function which determines whether a significant difference with fraudulence possibility occurs in any one of the game participant or player position, the game table, or a room having the game table at the time of an end of a predetermined number of games, on the basis of a calculation on
  • the management control device may further include a function which specifies dealers in each game and include a function which specifies the dealer responsible for a series of games in which the significant difference occurs.
  • the management control device may include a calculation function which factorizes the total return amount in a series of games in which the significant difference occurs to specify whether an occurrence cause of the significant difference in the series of games in which the significant difference occurs is due to the winning rate or due to a magnitude of a betted amount of a bet chip.
  • the management control device may include a calculation function which stores the bet chip amounts for each game at the bet position having different return rates, and specifies whether the occurrence cause of the significant difference in a series of games in which the significant difference has occurred is associated with the bet position having different return rates.
  • the management control device may have a plurality of criteria which determine whether there is a significant difference and issue a different kind of warnings for each criterion.
  • the management control device may have different criteria of a different significant difference for the number of games divided by a predetermined rule or for each of the predetermined number of games and issue a different kind of warnings.
  • the management control device may have a plurality of criteria which determine whether there is a significant difference and specify the game participant or the player position having the fraudulence possibility for each criterion to be able to display scores for each different criterion and display scores or ranks for warnings.
  • the management control device may further include a function which sequentially grasps the spots from playing cards or spots of dice from a series of games, and estimates the fraudulence cause in the case in which it is determined that there is a significant difference based on the data of the spots from a series of games and enumerates the fraudulence cause with the possibility.
  • the management control device may estimate the fraudulence cause in the case in which there is a significant difference using the big data about the past game as an additional item and enumerate the causes with the fraudulence possibility.
  • a fraudulence monitoring system of a table game includes: an income and expenditure grasping device which grasps income and expenditure of a casino side for each game table in a plurality of game tables; and a management control device which stores the number of games performed on each game table and sequentially grasps and stores a transition of the income and expenditure of the casino side in each game, wherein the management control device includes artificial intelligence having data of a past fraudulent game taught as training data, and further includes a calculation function which compares results of the income or expenditure of the casino side with figures obtained by a calculation of the artificial intelligence having the data of the past fraudulent game taught as the training data on the basis of a calculation on a total number of games performed on each game table and the transition of the income and expenditure of the casino side in each game to determine whether there is a significant difference therebetween, and determines a possibility that fraudulence occur in any one of the game table or a room having the game table where the significant difference is occurring.
  • a fraudulence monitoring program of a table game includes: a win and lose determining step of grasping win and lose results for each game in a game table; a bet chip grasping step of grasping an amount of game tokens that a game participant bets on the game table in each game; a game progressing, grasping, managing step of storing the number of games performed on the game table and specifying bet patterns of the game tokens that the game participant places on the game table using transition data of a bet chip in the bet chip grasping step in each game and storing the specified bet patterns in each game participant or player positions of the game table; and a step of verifying occurrence possibility of a fraudulence act, wherein the step of verifying the occurrence possibility of the fraudulence act includes a step of calculating an actual winning rate of the same person in each game participant or player position and a step of calculating a total return amount at the time of an end of a pre
  • the step of verifying the occurrence possibility of the fraudulence act may further include a step of specifying dealers in each game and has a step of specifying the dealer responsible for the series of games in which the significant difference occurs in the abnormal spot determining step.
  • the step of verifying the occurrence possibility of the fraudulence act may further include an artificial intelligence learning step that learns data of a past fraudulent game as training data.
  • the fraudulence monitoring system of a table game may further include: a device which specifies the game participant of the game table from the information on a face authentication system or the credit card or the like used.
  • FIG. 1 is a diagram schematically showing the whole fraudulence monitoring system in a game hall having a game table according to an embodiment of the present disclosure.
  • FIG. 2 is a perspective view of a chip showing an example of an overlapping state of grasped chips in the embodiment of the present disclosure.
  • FIG. 3 is a front cross-sectional view of a game token in the embodiment of the present disclosure.
  • FIG. 4 is a perspective view of a chip showing another example of the overlapping state of grasped chips in the embodiment of the present disclosure.
  • FIG. 5 is a schematic diagram of a casino system having a plurality of game tables according to the embodiment of the present disclosure.
  • FIG. 6 is a diagram showing an example of a graph showing a return amount for each game participant according to the embodiment of the present disclosure.
  • FIG. 7 is a graph showing a winning rate of a game participant according to the embodiment of the present disclosure.
  • FIG. 8 is another graph showing a winning rate of a game participant according to the embodiment of the present disclosure.
  • FIG. 9 is a diagram schematically showing a fraudulence monitoring system in a game table according to another embodiment of the present disclosure.
  • the table game includes various table games such as baccarat, blackjack, poker, bridge, roulette, and dice. Representatively, a baccarat game will be described below by way of example.
  • FIGS. 1 and 2 are diagrams showing the whole fraudulence monitoring system 10 .
  • the game table 4 is a table for baccarat, and is provided with each bet area 44 for seven game participants 6 .
  • Each bet area 44 for each game participant 6 includes each area for a player 441 , a banker 442 , a tie 443 , a player pair (P) 444 , and a banker pair (B) 445 .
  • Each game participant 6 places game tokens 9 representing a bet amount on each area corresponding to a target to be bet, thereby making a bet.
  • a win or lose determination device which determines win or lose results for each game in the game table 4 uses a card distribution device 3 .
  • the card distribution device 3 is a so-called electronic shoe already used by those skilled in the art, and is programmed with rules of a game in advance and has a structure to make it possible to determine a win or lose of a game by reading information on a playing card to be distributed. For example, in the baccarat game, the win of the banker, the win of the player, the tie (draw) and the pair (ranks of playing cards of a player or banker are the same) are basically determined by ranks of 2 and 3 cards, and the determination result (win or lose result) is displayed by a result display lamp 13 . In addition, the card distribution device 3 sends the win or lose result of the determined game to a management control device 50 .
  • a win or lose determination device may determine a win or lose by image recognition of a drawn playing card using a camera device 2 .
  • the camera device 2 is provided above the game table 4 to photograph the bet area 44 .
  • the game table 4 according to the present embodiment is provided with seven player positions 45 (“1”, “2”, “3”, “5”, “6”, “7”, and “8” in FIG. 1 ), and seven game participants 6 can participate in the game.
  • the camera device 2 photographs the bet areas 44 of all the player positions 45 .
  • One camera device 2 does not necessary photograph the bet areas 44 of all the player positions 45 , but a plurality of camera devices 2 may photograph all the bet areas 44 in a shared manner.
  • the game token 9 has a mark, a pattern and/or a color (may also have both of them) which can specify a type (value) of game token 9 on a surface and/or a side of the game token 9 , and a bet chip measuring device 19 specifies positions (to be betted), types, and the number of game tokens 9 placed on the bet areas 44 from colors of edges of side surfaces of the game tokens 9 based on the image photographed by the camera device 2 .
  • the bet chip measuring device 19 may be configured to recognize hiding (when a part of one chip is hidden, or when the entire chip is hidden) or the like due to dead spots of the game token 9 using a self-learning function or the like based on the existing artificial intelligence-based computer or control system and a deep learning (structure) technology, thereby accurately grasping the positions and number of game tokens.
  • the game token 9 may be configured to have a plurality of plastic layers which have different colors and are stacked, a colored layer 121 which is at least disposed in the middle of the plurality of plastic layers, and white layers or light color layers 120 which have the colored layer 121 sandwiched therebetween and are stacked on both sides of the game token 9 to form a stripe pattern on the side surface of the game token 9 in a stacked direction, such that the colored layer can specify a type of game tokens 9 .
  • types (10 points, 20 points, 100 points, 1000 points, or the like) of game tokens 9 by changing colors (red, green, yellow, blue, or the like) of the colored layer 121 .
  • the game token has a multilayered structure stacked as shown in FIG. 4 (compared with the existing chip shown in FIG. 2 ) and has the striped pattern distinctly formed on the side surface thereof in the stacked direction, such that the bet chip measuring device 19 can easily measure accurately the types and number of game tokens 9 .
  • the structure which detects the position 8 and the type of game token 9 in the bet area 44 is not limited thereto, and for example, as shown in FIG. 3 , the game token 9 may be configured to have an RFID 125 embedded in the game token 9 , with the RFID 125 storing information which can specify the type of game tokens 9 and an RFID antenna (not shown) which is provided on the game table 4 and reads ID to specify and detect the positions (to be betted), the type, and the number of game tokens 9 placed in the bet area 44 .
  • a game token tray 17 for a dealer 5 to accommodate the game token 9 is provided in front of the dealer 5 of the game table 4 . At least a part of the game token tray 17 is embedded in the game table 4 .
  • the bet chip measuring device 19 analyzes and measures the game token 9 stacked in a horizontal direction, thereby determining the type and the number of game tokens 9 .
  • the bet chip measuring device 19 may specify the positions (to be betted), the type, and the number of game tokens 9 accommodated in the game token tray 17 from the color or the like of the edge of the side surface of the game token 9 and the like, based on the image photographed by the camera device 2 , and for example, as shown in FIG.
  • the game token 9 may be configured to have the RFID 125 embedded in the game token 9 , with the RFID 125 storing the information which can specify at least the type of game tokens 9 and the RFID antenna (not shown) which is provided on the game table 4 and reads the ID to specify and detect the positions (to be betted), the type, and the number of game tokens 9 accommodated in the game token tray 17 .
  • the management control device 50 serves to grasp the positions, the type, and the number of game tokens 9 on the game table 4 which are obtained by the bet chip measuring device 19 , perform a balance calculation on the casino side in the game table 4 using the win or lose result obtained from the card distribution device 3 as the win or lose determination device, stores the number of games performed on the game table 4 , and specifies a position and an amount of game token 9 that the game participant 6 places on the game table 4 based on the measurement result of the bet chip measuring device 19 in each game and stores the specified position and amount of game token 9 in each game participant 6 or player positions 45 of the game table 4 .
  • the management control device 50 has a calculation function which calculates settlement amounts for each game (balance calculation on the casino side in the game table 4 ) for each game, and is configured to settle a total amount of game tokens 9 in the game token tray 17 of the dealer 5 of the game table 4 with the betted game token 9 of the game participant 6 after each game and then be able to compare and calculate whether an increase and decrease in the game token corresponding to the settlement is correct.
  • the management control device 50 can verify the total amount of game tokens 9 of the game token tray 17 at all times (or a predetermined time interval).
  • the management control device 50 stores the total number of games in which the same person for each game participant 6 or player position 45 participates, a transition of bet chip amounts for each game, and a return amount obtained in each game.
  • the return amount is an amount of money obtained by betting of the game participant 6 .
  • the management control device 50 calculates a winning rate at the time of the end of each game as shown in FIG. 7 on the basis of the calculation on the total number of games, the transition of the bet amounts for each game, and the return amounts obtained in each game, aggregates the return amount obtained in each game, and obtains results of an actual wining rate and a total return amount of the same person for each game participant 6 or player position 45 .
  • the management control device 50 compares the obtained actual winning rate and total return amount with figures obtained by a probability statistic calculation to determine whether there is a significant difference therebetween and specifies any one of the game participant 6 or the player position 45 , the game table 4 , or a room having the game table 4 where the significant difference is occurring.
  • the management control device 50 may determine that there is a significant difference when the ratio of the winning rate to the total number of games is higher than a predetermined threshold value as compared with the number on the probability statistical calculation, may determine that there is a significant difference when the ratio of the total return amount to the total number of games is higher than a predetermined threshold value as compared with the number on the probability statistical calculation, may determine that there is a significant difference when the ratio of the winning rate to the total return amount is higher than a predetermined threshold value as compared with the number on the probability statistical calculation, may determine that there is a significant difference when the total return amount obtained by one participant is higher than a predetermined threshold value as compared with the number on the probability statistical calculation, or may determine there is a significant difference according to other criteria.
  • FIG. 5 shows an overall view of a room having a plurality of game tables 4 .
  • the management control device 50 stores the total number of games, the transition of the bet amounts for each game, the return amounts obtained in each game for each same person for each game participant 6 or player position 45 in each of the plurality of game tables 4 , and obtains the winning rate and the total return amount.
  • the management control device 50 may store the total number of games, the transition of the bet amounts for each game, the return amounts obtained in each game for each game table 4 and each room, and may obtain the winning rate and the total return amount. By doing so, it is possible to detect cooperative fraudulent acts in the entire game table or the entire room.
  • the management control device 50 may further have a function which specifies the dealers 5 in each game and may have a function which specifies the dealer 5 responsible for the series of games in which the significant difference occurs.
  • the management control device 50 stores the total number of games for each dealer 5 , the transition of the bet chip amounts for each game, the return amounts obtained in each game and obtains the winning rate and the total return amount, thereby detecting a dealer 5 that is highly likely to lead a fraudulent act.
  • FIG. 6 is a diagram showing the transition of the total return amounts for each game participant 6 over time, in which it is possible to detect the game participant 6 who is highly likely to do a fraudulent act by comparing the data obtained by the probability calculation or the past statistical data with the total return amounts or by comparing the total return amounts with each other among the game participants 6 .
  • the management control device 50 includes a calculation function which factorizes the total return amount in a series of games in which the significant difference has occurred to specify whether the occurrence cause of the significant difference in a series of games in which the significant difference has occurred is due to the winning rate or due to a magnitude of a betted amount of a bet chip. That is, it is possible to determine whether although the same amount of money is betted upon winning and losing, since the probability of winning is merely high, the total return amount is large or although the probability of winning is not so high, since a large amount of money is betted upon winning and a small amount of money is betted upon losing, the total return amount is large.
  • the management control device 50 includes a calculation function which stores the bet chip amounts for each game at the bet position having different return rates, and specifies whether the occurrence cause of the significant difference in a series of games in which the significant difference has occurred is associated with the bet position having different return rates.
  • the return rate is twice in the case of the player/banker, 8 times in the case of the tie, and 11 times in the case of the pair. Therefore, it is possible to detect a betting method to win only in a betting side where the possibility of fraudulent act is high and the return rate like the tie or the pair is high.
  • the tie is established if 10 or continuous picture cards J, Q, and K are in the game, and therefore is famous for a fraudulent act.
  • the management control device 50 has a plurality of criteria for determining whether there is the significant difference, and issues a different kind of warning for each criterion. For example, if the detected significant difference is a significant difference which can occur at a frequency of about once every three days, a warning of a first stage is issued, if the detected significant difference is a significant difference which can occur at a frequency of about once a week, a warning of a second stage is issued, and if the detected significant difference is a significant difference which can occur at a frequency of about once a month, a warning of a third stage is issued.
  • abnormality display lamps 16 provided on the win or lose determination device 3 or both sides of the game table 4 are turned on, and the detection of the fraudulence is output to a casino management department or the like in a wireless or wired manner.
  • a monitor or a lamp which performs a warning or a display in response to the determination result may further be provided in another place.
  • it may be configured to be able to play the VTR recorded in the camera device 2 when receiving a warning.
  • FIG. 7 is a graph showing a change in the number of games of a winning rate of a game participant 6 .
  • a winning rate is high in the range of 100th to 200th games, but if the number of games is small, the warning of the first stage is issued because the winning rate is in the range which may occur by the probability calculation. Thereafter, since the wining rate is lowered, the warning disappears once, but the winning rate increases again at a 1000th game. In this case, the winning rate is high regardless of the large number of games, which is an event that rarely occurs by the probability calculation. As a result, the warning of the third stage is issued.
  • the management control device 50 has determination criteria having different significant differences for the number of games divided by a predetermined rule or for each of the predetermined number of games and thus issues a different kind of warnings.
  • the shuffle playing card in which playing cards corresponding to 8 to 10 decks are shuffled and are accommodated in a box is set in the card distribution device 3 to perform a game.
  • FIG. 8 shows a graph in which data of winning rates divided (of shoe 1 S, shoe 2 S, and shoe 3 S) by box (this is referred to as shoe) of the shuffle playing card used in the game are aggregated.
  • the management control device 50 determines whether there are significant differences for each game sequentially or every time the predetermined number of games is progressed in accordance with the progress of the plurality of games, and issues a warning when the determination criteria on the significant difference exceed. For example, it is difficult to determine that there is a significant difference even if the winning rate is 70% in the case in which 50 games are performed, but if the winning rate is 70% after 500 games are performed, it is determined that there is a significant difference and the suspicion of the fraudulent act is increased.
  • the management control device 50 may calculate an occurrence probability for each game unit and determine whether there is a significant difference or not. If each game unit consists of, for example, 75 games, the management control device 50 calculates the probability of obtaining the actual results of the 1st to the 75th games, then calculates the probability of obtaining the actual result of the 2nd to the 76th games, and calculates the probability for each game unit in the same way, and outputs a warning when the occurrence probability exceeds the judgment criterion of the significant difference.
  • the game unit is not limited to one consisting of 75 games, but may consists of 100 games, 300 games or the like. Further, the management control device 50 may calculate the occurrence probability for each bet type or each box number.
  • the management control device 50 has a plurality of criteria which determine whether there is a significant difference and specifies the game participant 6 or the player position 45 having the fraudulence possibility for each criterion to be able to display scores for each different criteria and display scores or ranks for warnings.
  • the management control device 50 can obtain the figures obtained by the probability statistic calculation used to determine whether there is a significant difference based on a conditional probability calculation when a specific element is a fixed value.
  • the calculation may be performed by fixing the number of games and using the conditional probability calculation.
  • the management control device 50 further has a function which sequentially grasps the playing cards or the spots of the dice from a series of games, and can estimate the fraudulence cause in the case in which it is determined that there is a significant difference based on the data of the spots from a series of games and enumerate the fraudulence cause with the possibility. For example, if a winner of a game is recognized based on the data of the spots from a series of games when a figure of the playing card first drawn is 9, it can be estimated that knowing the position of the playing card of 9 is the fraudulence cause.
  • the management control device 50 may estimate the fraudulence cause determined that there is the significant difference using any one or both of big data on past games or past fraudulent data, and enumerate the cause with the fraudulence possibility.
  • the management control device 50 may include a calculation function which compares results of the income or expenditure of the casino side with figures obtained by a probability statistic calculation at the time of an end of a predetermined number of games, on the basis of a calculation on a total number of games performed on the respective game tables 4 and the transition of the income and expenditure of the casino side in each game to determine whether there is a significant difference therebetween, and specifies any one of the game tables 4 or a room having the game tables 4 where the significant difference is occurring. In this case, it is unnecessary to grasp the bet amounts for each game participant 6 , and it is necessary to grasp only the balance of the game token tray.
  • the fraudulence monitoring system of the table game may further include a device which specifies the game participant 6 of the game table 4 from information on a face authentication system or an ID card, credit card or the like used.
  • the face authentication system may acquire an image of a face by feature point extraction or the like, and allocate an identity number (ID or the like) to specify the image of the face.
  • ID identity number
  • the face authentication system includes a warning function which informs the another game table of the existence of the specific player. Specifically, it is possible to warn a pit manager managing each game table 4 or a manager of each table.
  • the management control device 50 stores the total number of games in which the same person for each game participant 6 or player position 45 participates, a transition of bet chip amounts for each game, and a return amount obtained in each game.
  • the return amount is an amount of money obtained by betting of the game participant 6 .
  • the management control device 50 includes artificial intelligence having data of past fraudulent games taught as training data, and further includes a calculation function which determines whether a significant difference with fraudulence possibility occurs in any one of the game participant 6 or player position 45 , the game tables 4 , or a room having the game tables 4 at the time of an end of a predetermined number of games, on the basis of a calculation on a total number of games, a transition of bet chip amounts for each game, and a return amount obtained in each game
  • the management control device 50 is a control device of intelligent type, and is an artificial intelligence type or a deep learning structure which grasps the position (the betted position on the player, the banker, or the pair) and the amount (type and number) of the betted game token 9 on the game table 4 and compares the win or lose history and the obtained amount of chips (winning amount) of each game participant 6 from the win or lose results of each game with the statistical data of a large number (big data) of past games to be able to be extracted as a unique situation (set by the casino).
  • the management control device 50 having the artificial intelligence type or a deep learning structure compares the situation with the statistical data (big data or the like) of past games to be able to be extracted as a unique situation. In addition, the management control device 50 can compare the statistical data of the past game to determine what the cause of the fraudulent act is.
  • the management control device 50 Since the management control device 50 has the artificial intelligence having data of past fraudulent games taught as training data, it is possible to detect the fraudulent act of the type which is newly detected by the artificial intelligence.
  • the management control device 50 may estimate the fraudulence cause in the case in which there is a significant difference using the big data about the past game as an additional item and enumerate the causes with the fraudulence possibility.
  • the management control device 50 includes artificial intelligence having data of past fraudulent games taught as training data, and further includes a calculation function which determines whether a significant difference with fraudulence possibility occurs in any one of the game participant 6 or player position 45 , the game tables 4 , or a room having the game tables 4 at the time of an end of a predetermined number of games, on the basis of a calculation on a total number of games in which the same person participates in each game participant 6 or player position 45 , a transition of bet chip amounts for each game, a win or lose for each game, and a return amount obtained in each game.
  • a fraudulence monitoring program of a table game including: a win or lose determining step of grasping win or lose results for each game in a game table 4 ; a bet chip grasping step of grasping an amount of game tokens 9 that a game participant 6 bets on the game table 4 in each game; a game progressing, grasping, managing step of storing the number of games performed on the game table 4 and specifying bet patterns of the game tokens 9 that the game participant 6 places on the game table 4 using transition data of a bet chip in the bet chip grasping step in each game and storing the specified bet patterns in each game participant 6 or player positions 45 of the game table 4 ; and a step of verifying occurrence possibility of a fraudulence act, wherein the step of verifying the occurrence possibility of the fraudulence act includes a step of calculating an actual winning rate of the same person in each game participant or player position and a step of calculating a total return amount at the time of the end of a
  • the step of verifying the occurrence possibility of the fraudulence act further includes a step of specifying the dealers 5 in each game and has a step of specifying the dealer 5 responsible for the series of games in which the significant difference occurs in the abnormal spot determining step.
  • the step of verifying the occurrence possibility of the fraudulence act further includes the artificial intelligence learning step that learns the data of the past fraudulent games as the training data.
  • the fraudulence monitoring system of the table game further includes a device which specifies the game participant 6 of the game table 4 from the information on the face authentication system or the credit card or the like used.
  • the table game may also be the roulette as shown in FIG. 9 .
  • a kind of game token 9 having different colors is used for each player, and each game participant 6 performs betting by placing the game tokens 9 having different colors in each of the bet areas 54 .
  • the camera device 2 grasps the number and the amount of game tokens 9 betted in the bet area 54 , and recognizes the colors of the game tokens 9 to grasp the game participants 6 in which the game tokens 9 are placed.
  • the win or lose determination in the roulette is performed by allowing the camera device 2 to recognize a pocket 58 in which a ball 59 enters a wheel 57 .
  • the win or lose determination device which is performed by the manual input of the dealer 5 may be provided.

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Abstract

A detection system of the present disclosure stores positions and the amount of game tokens that a game participant places on a game table based on a measurement result by a bet chip measuring device in the same persons for each game participant or player positions of the game table. A management control device compares an actual winning rate and a total return amount with figures obtained by a probability statistic calculation at the time of an end of the number of games to determine whether there is a significant difference therebetween and specifies any one of the game participant or the player position, the game table, or a room having the game table where the significant difference is occurring.

Description

    TECHNICAL FIELD
  • The present disclosure relates to a fraudulence monitoring system of a table game in a game hall, and more particularly, to a technology for detecting a fraudulent act.
  • BACKGROUND
  • Attempts are being made to prevent various fraudulent acts in a game hall such as a casino. The game hall has surveillance cameras for monitoring fraudulent acts and prevents fraudulence by determining fraudulence during a game and fraudulence by collection or repayment of chips different from a win or lose result using images obtained from the surveillance cameras. Meanwhile, it is suggested to grasp an amount of chips by attaching an IC tag to each chip in order to grasp the number of betted chips and a total amount of betted chips.
  • PCT/JP2015/000171 discloses a card game monitoring system which determines whether chips placed on a game table are collected or repaid as a win or lose result by performing an image analysis on a movement of chips and monitors a fraudulent act.
  • In the game hall such as the casino, the game table is recorded by the surveillance camera, and when the amount of money won at a time by a game participant is large, the recorded VTR is played to confirm whether or not there is a fraudulent act. However, there is a problem that fraudulence such as sophisticated fraudulence acts in a game table and continuous winning of a small amount of money cannot be found by simply detecting that the game participant wins the large amount of money. In addition, the related art does not sufficiently prevent a fraudulence act by collusion of a dealer and a player.
  • SUMMARY OF THE INVENTION
  • An object of the present disclosure is to prevent damage due to a fraudulent act by continuously monitoring an amount betted by a game participant and win or lose of a game, comparing data of a probability statistic calculation or past statistical data, and detecting a suspicious pattern suspected of being fraudulent.
  • To solve the conventional problem, a fraudulence monitoring system of a table game includes: a win and lose determination device which determines win and lose results for each game in a game table; a bet chip measuring device which grasps an amount of game tokens that a game participant bets on the game table in each game; and a management control device which stores the number of games performed on the game table and specifies positions and the amount of game tokens that the game participant places on the game table based on a measurement result by the bet chip measuring device in each game and stores the specified positions and amount of game tokens in each game participant or player positions of the game table, wherein the management control device includes a calculation function which compares results of an actual winning rate and a total return amount of the same person in each game participant or player position with figures obtained by a probability statistic calculation at the time of an end of a predetermined number of games, on the basis of a calculation on a total number of games in which the same person participates in each game participant or player position, a transition of bet chip amounts for each game, a win and lose for each game, and a return amount obtained in each game to determine whether there is a significant difference therebetween, and specifies any one of the game participant or player position, the game table, or a room having the game table where the significant difference is occurring.
  • The management control device may further include a function which specifies dealers in each game and include a function which specifies a dealer responsible for a series of games in which the significant difference occurs.
  • The management control device may include a calculation function which factorizes the total return amount in a series of games in which the significant difference occurs to specify whether an occurrence cause of the significant difference in the series of games in which the significant difference occurs is due to the winning rate or due to a magnitude of a betted amount of the bet chip.
  • The management control device may include a calculation function which stores the bet chip amounts for each game at the bet position having different return rates, and specifies whether the occurrence cause of the significant difference in a series of games in which the significant difference has occurred is associated with the bet position having different return rates.
  • The management control device may have a plurality of criteria which determine whether there is a significant difference and issue a different kind of warnings for each criterion.
  • The management control device may have different determination criteria of a different significant difference for the number of games divided by a predetermined rule or for each of the predetermined number of games and issue a different kind of warnings.
  • The management control device may determine whether there are significant differences for each game sequentially or every time the predetermined number of games is progressed in accordance with the progress of the plurality of games, and issue a warning when the determination criteria on the significant difference exceed.
  • The management control device may have a plurality of criteria which determine whether there is a significant difference and specify the game participant or the player position having the fraudulence possibility for each criterion to be able to display scores for each different criteria and display scores or ranks for warnings.
  • The management control device may obtain the figures obtained by the probability statistic calculation used to determine whether there is a significant difference based on a conditional probability calculation when a specific element is a fixed value.
  • The management control device may further include a function which sequentially grasps the spots from the playing cards or spots of dice from a series of games, and estimates the fraudulence cause in the case in which it is determined that there is a significant difference based on the data of the spots from a series of games and enumerates the fraudulence cause with the possibility.
  • The management control device may estimate the fraudulence cause determined that there is the significant difference using any one or both of big data on past games or past fraudulent data, and enumerate the cause with the fraudulence possibility.
  • To solve the conventional problem, the fraudulence monitoring system of the present invention may adopt the following form. A fraudulence monitoring system of a table game, includes: an income and expenditure grasping device which grasps income and expenditure of a casino side for each game table in a plurality of game tables; and a management control device which stores the number of games performed on each game table and sequentially grasps and stores a transition of the income and expenditure of the casino side in each game, wherein the management control device includes a calculation function which compares results of the income or expenditure of the casino side with figures obtained by a probability statistic calculation at the time of an end of a predetermined number of games, on the basis of a calculation on a total number of games performed on each game table and the transition of the income and expenditure of the casino side in each game to determine whether there is a significant difference therebetween, and specifies any one of the game table or a room having the game table where the significant difference is occurring.
  • To solve the conventional problem, the fraudulence monitoring system of the present invention may adopt the following form. A fraudulence monitoring system of a table game, includes: a win and lose determination device which determines win and lose results for each game in a game table; a bet chip measuring device which grasps an amount of game tokens that a game participant bets on the game table in each game; and a management control device which stores the number of games performed on the game table and specifies positions and the amount of game tokens that the game participant places on the game table using a measurement result by the bet chip measuring device in each game and stores the specified positions and amount of game tokens in each game participant or player positions of the game table, wherein the management control device includes artificial intelligence having past data of a fraudulent game taught as training data, and further includes a calculation function which determines whether a significant difference with fraudulence possibility occurs in any one of the game participant or player position, the game table, or a room having the game table at the time of an end of a predetermined number of games, on the basis of a calculation on a total number of games in which the same person participates in each game participant or player position, a transition of bet chip amounts for each game, a win and lose for each game, and a return amount obtained in each game.
  • The management control device may further include a function which specifies dealers in each game and include a function which specifies the dealer responsible for a series of games in which the significant difference occurs.
  • The management control device may include a calculation function which factorizes the total return amount in a series of games in which the significant difference occurs to specify whether an occurrence cause of the significant difference in the series of games in which the significant difference occurs is due to the winning rate or due to a magnitude of a betted amount of a bet chip.
  • The management control device may include a calculation function which stores the bet chip amounts for each game at the bet position having different return rates, and specifies whether the occurrence cause of the significant difference in a series of games in which the significant difference has occurred is associated with the bet position having different return rates.
  • The management control device may have a plurality of criteria which determine whether there is a significant difference and issue a different kind of warnings for each criterion.
  • The management control device may have different criteria of a different significant difference for the number of games divided by a predetermined rule or for each of the predetermined number of games and issue a different kind of warnings.
  • The management control device may have a plurality of criteria which determine whether there is a significant difference and specify the game participant or the player position having the fraudulence possibility for each criterion to be able to display scores for each different criterion and display scores or ranks for warnings.
  • The management control device may further include a function which sequentially grasps the spots from playing cards or spots of dice from a series of games, and estimates the fraudulence cause in the case in which it is determined that there is a significant difference based on the data of the spots from a series of games and enumerates the fraudulence cause with the possibility.
  • The management control device may estimate the fraudulence cause in the case in which there is a significant difference using the big data about the past game as an additional item and enumerate the causes with the fraudulence possibility.
  • To solve the conventional problem, the fraudulence monitoring system of the present invention may adopt the following form. A fraudulence monitoring system of a table game, includes: an income and expenditure grasping device which grasps income and expenditure of a casino side for each game table in a plurality of game tables; and a management control device which stores the number of games performed on each game table and sequentially grasps and stores a transition of the income and expenditure of the casino side in each game, wherein the management control device includes artificial intelligence having data of a past fraudulent game taught as training data, and further includes a calculation function which compares results of the income or expenditure of the casino side with figures obtained by a calculation of the artificial intelligence having the data of the past fraudulent game taught as the training data on the basis of a calculation on a total number of games performed on each game table and the transition of the income and expenditure of the casino side in each game to determine whether there is a significant difference therebetween, and determines a possibility that fraudulence occur in any one of the game table or a room having the game table where the significant difference is occurring.
  • To solve the conventional problem, the fraudulence monitoring system of the present invention may adopt the following form. A fraudulence monitoring program of a table game, includes: a win and lose determining step of grasping win and lose results for each game in a game table; a bet chip grasping step of grasping an amount of game tokens that a game participant bets on the game table in each game; a game progressing, grasping, managing step of storing the number of games performed on the game table and specifying bet patterns of the game tokens that the game participant places on the game table using transition data of a bet chip in the bet chip grasping step in each game and storing the specified bet patterns in each game participant or player positions of the game table; and a step of verifying occurrence possibility of a fraudulence act, wherein the step of verifying the occurrence possibility of the fraudulence act includes a step of calculating an actual winning rate of the same person in each game participant or player position and a step of calculating a total return amount at the time of an end of a predetermined number of games end, on the basis of grasping and calculating a total number of games in which the same person participates in each game participant or player position, a transition of a bet chip amount, and a return amount for each game, a significant different determining step of comparing the obtained winning rate and total return amount with a winning rate and a total return amount based on a probability statistic calculation or past data to determine whether there is a significant difference therebetween in the predetermined number of games, and an abnormal spot determining step of specifying any one of the game participant or player position, the game table, or a room having the game table where the significant difference is occurring.
  • The step of verifying the occurrence possibility of the fraudulence act may further include a step of specifying dealers in each game and has a step of specifying the dealer responsible for the series of games in which the significant difference occurs in the abnormal spot determining step.
  • The step of verifying the occurrence possibility of the fraudulence act may further include an artificial intelligence learning step that learns data of a past fraudulent game as training data.
  • The fraudulence monitoring system of a table game may further include: a device which specifies the game participant of the game table from the information on a face authentication system or the credit card or the like used.
  • According to the above configuration, it is possible to prevent damage due to a fraudulent act by continuously monitoring an amount betted by a game participant and win or lose of a game, comparing data obtained by a probability statistic calculation or past statistical data, and detecting a suspicious pattern suspected of being fraudulent.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • FIG. 1 is a diagram schematically showing the whole fraudulence monitoring system in a game hall having a game table according to an embodiment of the present disclosure.
  • FIG. 2 is a perspective view of a chip showing an example of an overlapping state of grasped chips in the embodiment of the present disclosure.
  • FIG. 3 is a front cross-sectional view of a game token in the embodiment of the present disclosure.
  • FIG. 4 is a perspective view of a chip showing another example of the overlapping state of grasped chips in the embodiment of the present disclosure.
  • FIG. 5 is a schematic diagram of a casino system having a plurality of game tables according to the embodiment of the present disclosure.
  • FIG. 6 is a diagram showing an example of a graph showing a return amount for each game participant according to the embodiment of the present disclosure.
  • FIG. 7 is a graph showing a winning rate of a game participant according to the embodiment of the present disclosure.
  • FIG. 8 is another graph showing a winning rate of a game participant according to the embodiment of the present disclosure.
  • FIG. 9 is a diagram schematically showing a fraudulence monitoring system in a game table according to another embodiment of the present disclosure.
  • DESCRIPTION OF EMBODIMENTS
  • An outline of a fraudulence monitoring system 10 of a game table in a game hall will be described below with reference to the accompanying drawings. Here, the table game includes various table games such as baccarat, blackjack, poker, bridge, roulette, and dice. Representatively, a baccarat game will be described below by way of example.
  • FIGS. 1 and 2 are diagrams showing the whole fraudulence monitoring system 10. The game table 4 is a table for baccarat, and is provided with each bet area 44 for seven game participants 6. Each bet area 44 for each game participant 6 includes each area for a player 441, a banker 442, a tie 443, a player pair (P) 444, and a banker pair (B) 445. Each game participant 6 places game tokens 9 representing a bet amount on each area corresponding to a target to be bet, thereby making a bet.
  • A win or lose determination device which determines win or lose results for each game in the game table 4 uses a card distribution device 3. The card distribution device 3 is a so-called electronic shoe already used by those skilled in the art, and is programmed with rules of a game in advance and has a structure to make it possible to determine a win or lose of a game by reading information on a playing card to be distributed. For example, in the baccarat game, the win of the banker, the win of the player, the tie (draw) and the pair (ranks of playing cards of a player or banker are the same) are basically determined by ranks of 2 and 3 cards, and the determination result (win or lose result) is displayed by a result display lamp 13. In addition, the card distribution device 3 sends the win or lose result of the determined game to a management control device 50.
  • However, according to another embodiment, instead of the card distribution device 3, a win or lose determination device may determine a win or lose by image recognition of a drawn playing card using a camera device 2.
  • The camera device 2 is provided above the game table 4 to photograph the bet area 44. The game table 4 according to the present embodiment is provided with seven player positions 45 (“1”, “2”, “3”, “5”, “6”, “7”, and “8” in FIG. 1), and seven game participants 6 can participate in the game. The camera device 2 photographs the bet areas 44 of all the player positions 45. One camera device 2 does not necessary photograph the bet areas 44 of all the player positions 45, but a plurality of camera devices 2 may photograph all the bet areas 44 in a shared manner.
  • The game token 9 has a mark, a pattern and/or a color (may also have both of them) which can specify a type (value) of game token 9 on a surface and/or a side of the game token 9, and a bet chip measuring device 19 specifies positions (to be betted), types, and the number of game tokens 9 placed on the bet areas 44 from colors of edges of side surfaces of the game tokens 9 based on the image photographed by the camera device 2. In this case, the bet chip measuring device 19 may be configured to recognize hiding (when a part of one chip is hidden, or when the entire chip is hidden) or the like due to dead spots of the game token 9 using a self-learning function or the like based on the existing artificial intelligence-based computer or control system and a deep learning (structure) technology, thereby accurately grasping the positions and number of game tokens.
  • In addition, as shown in FIG. 4, the game token 9 may be configured to have a plurality of plastic layers which have different colors and are stacked, a colored layer 121 which is at least disposed in the middle of the plurality of plastic layers, and white layers or light color layers 120 which have the colored layer 121 sandwiched therebetween and are stacked on both sides of the game token 9 to form a stripe pattern on the side surface of the game token 9 in a stacked direction, such that the colored layer can specify a type of game tokens 9. In this case, it is possible to specify types (10 points, 20 points, 100 points, 1000 points, or the like) of game tokens 9 by changing colors (red, green, yellow, blue, or the like) of the colored layer 121.
  • In such a case, the game token has a multilayered structure stacked as shown in FIG. 4 (compared with the existing chip shown in FIG. 2) and has the striped pattern distinctly formed on the side surface thereof in the stacked direction, such that the bet chip measuring device 19 can easily measure accurately the types and number of game tokens 9.
  • Alternatively, the structure which detects the position 8 and the type of game token 9 in the bet area 44 is not limited thereto, and for example, as shown in FIG. 3, the game token 9 may be configured to have an RFID 125 embedded in the game token 9, with the RFID 125 storing information which can specify the type of game tokens 9 and an RFID antenna (not shown) which is provided on the game table 4 and reads ID to specify and detect the positions (to be betted), the type, and the number of game tokens 9 placed in the bet area 44.
  • A game token tray 17 for a dealer 5 to accommodate the game token 9 is provided in front of the dealer 5 of the game table 4. At least a part of the game token tray 17 is embedded in the game table 4. In the game token tray 17, the bet chip measuring device 19 analyzes and measures the game token 9 stacked in a horizontal direction, thereby determining the type and the number of game tokens 9. In this case, the bet chip measuring device 19 may specify the positions (to be betted), the type, and the number of game tokens 9 accommodated in the game token tray 17 from the color or the like of the edge of the side surface of the game token 9 and the like, based on the image photographed by the camera device 2, and for example, as shown in FIG. 3, the game token 9 may be configured to have the RFID 125 embedded in the game token 9, with the RFID 125 storing the information which can specify at least the type of game tokens 9 and the RFID antenna (not shown) which is provided on the game table 4 and reads the ID to specify and detect the positions (to be betted), the type, and the number of game tokens 9 accommodated in the game token tray 17.
  • The management control device 50 serves to grasp the positions, the type, and the number of game tokens 9 on the game table 4 which are obtained by the bet chip measuring device 19, perform a balance calculation on the casino side in the game table 4 using the win or lose result obtained from the card distribution device 3 as the win or lose determination device, stores the number of games performed on the game table 4, and specifies a position and an amount of game token 9 that the game participant 6 places on the game table 4 based on the measurement result of the bet chip measuring device 19 in each game and stores the specified position and amount of game token 9 in each game participant 6 or player positions 45 of the game table 4.
  • In addition, the management control device 50 has a calculation function which calculates settlement amounts for each game (balance calculation on the casino side in the game table 4) for each game, and is configured to settle a total amount of game tokens 9 in the game token tray 17 of the dealer 5 of the game table 4 with the betted game token 9 of the game participant 6 after each game and then be able to compare and calculate whether an increase and decrease in the game token corresponding to the settlement is correct. The management control device 50 can verify the total amount of game tokens 9 of the game token tray 17 at all times (or a predetermined time interval).
  • The management control device 50 stores the total number of games in which the same person for each game participant 6 or player position 45 participates, a transition of bet chip amounts for each game, and a return amount obtained in each game. The return amount is an amount of money obtained by betting of the game participant 6. The management control device 50 calculates a winning rate at the time of the end of each game as shown in FIG. 7 on the basis of the calculation on the total number of games, the transition of the bet amounts for each game, and the return amounts obtained in each game, aggregates the return amount obtained in each game, and obtains results of an actual wining rate and a total return amount of the same person for each game participant 6 or player position 45. The management control device 50 compares the obtained actual winning rate and total return amount with figures obtained by a probability statistic calculation to determine whether there is a significant difference therebetween and specifies any one of the game participant 6 or the player position 45, the game table 4, or a room having the game table 4 where the significant difference is occurring.
  • Specifically, for example, the management control device 50 may determine that there is a significant difference when the ratio of the winning rate to the total number of games is higher than a predetermined threshold value as compared with the number on the probability statistical calculation, may determine that there is a significant difference when the ratio of the total return amount to the total number of games is higher than a predetermined threshold value as compared with the number on the probability statistical calculation, may determine that there is a significant difference when the ratio of the winning rate to the total return amount is higher than a predetermined threshold value as compared with the number on the probability statistical calculation, may determine that there is a significant difference when the total return amount obtained by one participant is higher than a predetermined threshold value as compared with the number on the probability statistical calculation, or may determine there is a significant difference according to other criteria.
  • FIG. 5 shows an overall view of a room having a plurality of game tables 4. The management control device 50 stores the total number of games, the transition of the bet amounts for each game, the return amounts obtained in each game for each same person for each game participant 6 or player position 45 in each of the plurality of game tables 4, and obtains the winning rate and the total return amount. In addition, the management control device 50 may store the total number of games, the transition of the bet amounts for each game, the return amounts obtained in each game for each game table 4 and each room, and may obtain the winning rate and the total return amount. By doing so, it is possible to detect cooperative fraudulent acts in the entire game table or the entire room.
  • The management control device 50 may further have a function which specifies the dealers 5 in each game and may have a function which specifies the dealer 5 responsible for the series of games in which the significant difference occurs. In addition, the management control device 50 stores the total number of games for each dealer 5, the transition of the bet chip amounts for each game, the return amounts obtained in each game and obtains the winning rate and the total return amount, thereby detecting a dealer 5 that is highly likely to lead a fraudulent act.
  • FIG. 6 is a diagram showing the transition of the total return amounts for each game participant 6 over time, in which it is possible to detect the game participant 6 who is highly likely to do a fraudulent act by comparing the data obtained by the probability calculation or the past statistical data with the total return amounts or by comparing the total return amounts with each other among the game participants 6.
  • The management control device 50 includes a calculation function which factorizes the total return amount in a series of games in which the significant difference has occurred to specify whether the occurrence cause of the significant difference in a series of games in which the significant difference has occurred is due to the winning rate or due to a magnitude of a betted amount of a bet chip. That is, it is possible to determine whether although the same amount of money is betted upon winning and losing, since the probability of winning is merely high, the total return amount is large or although the probability of winning is not so high, since a large amount of money is betted upon winning and a small amount of money is betted upon losing, the total return amount is large.
  • In addition, the management control device 50 includes a calculation function which stores the bet chip amounts for each game at the bet position having different return rates, and specifies whether the occurrence cause of the significant difference in a series of games in which the significant difference has occurred is associated with the bet position having different return rates. For example, in the baccarat game, the return rate is twice in the case of the player/banker, 8 times in the case of the tie, and 11 times in the case of the pair. Therefore, it is possible to detect a betting method to win only in a betting side where the possibility of fraudulent act is high and the return rate like the tie or the pair is high. In particular, the tie is established if 10 or continuous picture cards J, Q, and K are in the game, and therefore is famous for a fraudulent act.
  • Further, the management control device 50 has a plurality of criteria for determining whether there is the significant difference, and issues a different kind of warning for each criterion. For example, if the detected significant difference is a significant difference which can occur at a frequency of about once every three days, a warning of a first stage is issued, if the detected significant difference is a significant difference which can occur at a frequency of about once a week, a warning of a second stage is issued, and if the detected significant difference is a significant difference which can occur at a frequency of about once a month, a warning of a third stage is issued. Upon the detection of the fraudulence, abnormality display lamps 16 provided on the win or lose determination device 3 or both sides of the game table 4 are turned on, and the detection of the fraudulence is output to a casino management department or the like in a wireless or wired manner. A monitor or a lamp which performs a warning or a display in response to the determination result may further be provided in another place. In addition, it may be configured to be able to play the VTR recorded in the camera device 2 when receiving a warning.
  • FIG. 7 is a graph showing a change in the number of games of a winning rate of a game participant 6. In this case, for example, a winning rate is high in the range of 100th to 200th games, but if the number of games is small, the warning of the first stage is issued because the winning rate is in the range which may occur by the probability calculation. Thereafter, since the wining rate is lowered, the warning disappears once, but the winning rate increases again at a 1000th game. In this case, the winning rate is high regardless of the large number of games, which is an event that rarely occurs by the probability calculation. As a result, the warning of the third stage is issued.
  • In addition, the management control device 50 has determination criteria having different significant differences for the number of games divided by a predetermined rule or for each of the predetermined number of games and thus issues a different kind of warnings. For example, in the table game using a shuffle playing card like the baccarat, the shuffle playing card in which playing cards corresponding to 8 to 10 decks are shuffled and are accommodated in a box is set in the card distribution device 3 to perform a game. FIG. 8 shows a graph in which data of winning rates divided (of shoe 1S, shoe 2S, and shoe 3S) by box (this is referred to as shoe) of the shuffle playing card used in the game are aggregated. By doing so, it is possible to detect a fraudulent act such as knowing the arrangement order of specific shuffle playing cards in the box that cannot be detected only by monitoring the overall winning rate. In the graph of the upper part of FIG. 8 showing the overall winning rate continuously monitored, it seems that the winning rate is high first and there is no feature later. However, looking at the graphs divided by shoe in the lower part of FIG. 8, in the shoe 3S, it is possible to detect that the winning rate is high and the possibility of the fraudulent act is high. In addition, it possible to detect that the shoe 15 and the shoe 3S become the graph of the same winning rate and the possibility of the fraudulent act is high.
  • In addition, the management control device 50 determines whether there are significant differences for each game sequentially or every time the predetermined number of games is progressed in accordance with the progress of the plurality of games, and issues a warning when the determination criteria on the significant difference exceed. For example, it is difficult to determine that there is a significant difference even if the winning rate is 70% in the case in which 50 games are performed, but if the winning rate is 70% after 500 games are performed, it is determined that there is a significant difference and the suspicion of the fraudulent act is increased.
  • In addition, the management control device 50 may calculate an occurrence probability for each game unit and determine whether there is a significant difference or not. If each game unit consists of, for example, 75 games, the management control device 50 calculates the probability of obtaining the actual results of the 1st to the 75th games, then calculates the probability of obtaining the actual result of the 2nd to the 76th games, and calculates the probability for each game unit in the same way, and outputs a warning when the occurrence probability exceeds the judgment criterion of the significant difference. The game unit is not limited to one consisting of 75 games, but may consists of 100 games, 300 games or the like. Further, the management control device 50 may calculate the occurrence probability for each bet type or each box number.
  • In addition, the management control device 50 has a plurality of criteria which determine whether there is a significant difference and specifies the game participant 6 or the player position 45 having the fraudulence possibility for each criterion to be able to display scores for each different criteria and display scores or ranks for warnings.
  • In addition, the management control device 50 can obtain the figures obtained by the probability statistic calculation used to determine whether there is a significant difference based on a conditional probability calculation when a specific element is a fixed value. For example, the calculation may be performed by fixing the number of games and using the conditional probability calculation.
  • The management control device 50 further has a function which sequentially grasps the playing cards or the spots of the dice from a series of games, and can estimate the fraudulence cause in the case in which it is determined that there is a significant difference based on the data of the spots from a series of games and enumerate the fraudulence cause with the possibility. For example, if a winner of a game is recognized based on the data of the spots from a series of games when a figure of the playing card first drawn is 9, it can be estimated that knowing the position of the playing card of 9 is the fraudulence cause.
  • In addition, the management control device 50 may estimate the fraudulence cause determined that there is the significant difference using any one or both of big data on past games or past fraudulent data, and enumerate the cause with the fraudulence possibility.
  • In addition, the management control device 50 may include a calculation function which compares results of the income or expenditure of the casino side with figures obtained by a probability statistic calculation at the time of an end of a predetermined number of games, on the basis of a calculation on a total number of games performed on the respective game tables 4 and the transition of the income and expenditure of the casino side in each game to determine whether there is a significant difference therebetween, and specifies any one of the game tables 4 or a room having the game tables 4 where the significant difference is occurring. In this case, it is unnecessary to grasp the bet amounts for each game participant 6, and it is necessary to grasp only the balance of the game token tray.
  • Further, the fraudulence monitoring system of the table game may further include a device which specifies the game participant 6 of the game table 4 from information on a face authentication system or an ID card, credit card or the like used.
  • The face authentication system may acquire an image of a face by feature point extraction or the like, and allocate an identity number (ID or the like) to specify the image of the face. When the specified game participant 6 leaves his/her seat and sits on another game table, the face authentication system includes a warning function which informs the another game table of the existence of the specific player. Specifically, it is possible to warn a pit manager managing each game table 4 or a manager of each table.
  • According to another embodiment of the present invention, the management control device 50 stores the total number of games in which the same person for each game participant 6 or player position 45 participates, a transition of bet chip amounts for each game, and a return amount obtained in each game. The return amount is an amount of money obtained by betting of the game participant 6. The management control device 50 includes artificial intelligence having data of past fraudulent games taught as training data, and further includes a calculation function which determines whether a significant difference with fraudulence possibility occurs in any one of the game participant 6 or player position 45, the game tables 4, or a room having the game tables 4 at the time of an end of a predetermined number of games, on the basis of a calculation on a total number of games, a transition of bet chip amounts for each game, and a return amount obtained in each game
  • For example, the management control device 50 is a control device of intelligent type, and is an artificial intelligence type or a deep learning structure which grasps the position (the betted position on the player, the banker, or the pair) and the amount (type and number) of the betted game token 9 on the game table 4 and compares the win or lose history and the obtained amount of chips (winning amount) of each game participant 6 from the win or lose results of each game with the statistical data of a large number (big data) of past games to be able to be extracted as a unique situation (set by the casino). Typically, in the situation in which a winning amount equal to or more than any amount of money (a million dollar) is generated or in the situation in which the state in which a bet chip amount betted on a losing side is small and a bet chip amount on a winning side is large is continued in several games at the play position 7 of the game table 4, the management control device 50 having the artificial intelligence type or a deep learning structure compares the situation with the statistical data (big data or the like) of past games to be able to be extracted as a unique situation. In addition, the management control device 50 can compare the statistical data of the past game to determine what the cause of the fraudulent act is.
  • Since the management control device 50 has the artificial intelligence having data of past fraudulent games taught as training data, it is possible to detect the fraudulent act of the type which is newly detected by the artificial intelligence.
  • The management control device 50 may estimate the fraudulence cause in the case in which there is a significant difference using the big data about the past game as an additional item and enumerate the causes with the fraudulence possibility.
  • In addition, in the fraudulence monitoring system according to another embodiment of the present invention, the management control device 50 includes artificial intelligence having data of past fraudulent games taught as training data, and further includes a calculation function which determines whether a significant difference with fraudulence possibility occurs in any one of the game participant 6 or player position 45, the game tables 4, or a room having the game tables 4 at the time of an end of a predetermined number of games, on the basis of a calculation on a total number of games in which the same person participates in each game participant 6 or player position 45, a transition of bet chip amounts for each game, a win or lose for each game, and a return amount obtained in each game.
  • According to another embodiment of the present disclosure, a fraudulence monitoring program of a table game, including: a win or lose determining step of grasping win or lose results for each game in a game table 4; a bet chip grasping step of grasping an amount of game tokens 9 that a game participant 6 bets on the game table 4 in each game; a game progressing, grasping, managing step of storing the number of games performed on the game table 4 and specifying bet patterns of the game tokens 9 that the game participant 6 places on the game table 4 using transition data of a bet chip in the bet chip grasping step in each game and storing the specified bet patterns in each game participant 6 or player positions 45 of the game table 4; and a step of verifying occurrence possibility of a fraudulence act, wherein the step of verifying the occurrence possibility of the fraudulence act includes a step of calculating an actual winning rate of the same person in each game participant or player position and a step of calculating a total return amount at the time of the end of a predetermined number of games, on the basis of grasping and calculating a total number of games in which the same person participates in each game participant 6 or player position 45, a transition of a bet chip amount, and a return amount for each game, a significant different determining step of comparing the obtained winning rate and total return amount with a winning rate and a total return amount based on a probability statistic calculation or past data to determine whether there is a significant difference therebetween in the predetermined number of games, and an abnormal spot determining step of specifying any one of the game participant or player position, the game table, or a room having the game table where the significant difference is occurring.
  • The step of verifying the occurrence possibility of the fraudulence act further includes a step of specifying the dealers 5 in each game and has a step of specifying the dealer 5 responsible for the series of games in which the significant difference occurs in the abnormal spot determining step.
  • The step of verifying the occurrence possibility of the fraudulence act further includes the artificial intelligence learning step that learns the data of the past fraudulent games as the training data.
  • The fraudulence monitoring system of the table game further includes a device which specifies the game participant 6 of the game table 4 from the information on the face authentication system or the credit card or the like used.
  • The example of the baccarat is described above, but the table game may also be the roulette as shown in FIG. 9. In the roulette, a kind of game token 9 having different colors is used for each player, and each game participant 6 performs betting by placing the game tokens 9 having different colors in each of the bet areas 54. The camera device 2 grasps the number and the amount of game tokens 9 betted in the bet area 54, and recognizes the colors of the game tokens 9 to grasp the game participants 6 in which the game tokens 9 are placed. The win or lose determination in the roulette is performed by allowing the camera device 2 to recognize a pocket 58 in which a ball 59 enters a wheel 57. Alternatively, the win or lose determination device which is performed by the manual input of the dealer 5 may be provided.
  • In addition, although not described in detail, the present disclosure may be applied to various table games such as blackjack, poker, bridge, and dice.
  • EXPLANATION OF REFERENCES
      • 1, Playing card
      • 2, Camera, Surveillance camera
      • 3, Card distribution device
      • 4, Game table
      • 5, Dealer
      • 6, Game participant
      • 9, Chip (Game token)
      • 44, Bet area
      • 441, Player area
      • 442, Banker area
      • 443, Tie area
      • 444, Player pair area
      • 445, Banker pair area
      • 121, Colored layer
      • 122, White layer or light color layer
      • 125, RFID

Claims (26)

What is claimed is:
1. A fraudulence monitoring system of a table game, comprising:
a win or lose determination device which determines win or lose results for each game in a game table;
a bet chip measuring device which grasps an amount of game tokens that a game participant bets on the game table in each game; and
a management control device which stores the number of games performed on the game table and specifies positions and the amount of game tokens that the game participant places on the game table based on a measurement result by the bet chip measuring device in each game and stores the specified positions and amount of game tokens in each game participant or player positions of the game table,
wherein the management control device includes a function which refers to a total number of games, a transition of bet chip amounts for each game, a win or lose result of each game, and a return amount obtained in each game for each game participant or player position as calculation basis and compares results of an actual winning rate and a total return amount in each game participant or player position at the time of an end of a predetermined number of games with figures obtained by a probability statistic calculation to determine whether there is a significant difference therebetween or not.
2. The fraudulence monitoring system of a table game according to claim 1, wherein the management control device further includes a function which specifies dealers in each game and includes a function which specifies at least any one of a participant, a dealer, a player position, a game table, or a room having the game table of a series of games in which the significant difference occurs.
3. The fraudulence monitoring system of a table game according to claim 1 or 2, wherein the management control device includes a calculation function which factorizes the total return amount in a series of games in which the significant difference occurs to specify whether an occurrence cause of the significant difference in the series of games in which the significant difference occurs is due to the winning rate or due to a magnitude of a betted amount of the bet chip.
4. The fraudulence monitoring system of a table game according to claim 1 or 2, wherein the management control device includes a calculation function which stores the bet chip amounts for each game at the bet position having different return rates, and specifies whether the occurrence cause of the significant difference in a series of games in which the significant difference has occurred is associated with the bet position having different return rates.
5. The fraudulence monitoring system of a table game according to claim 1 or 2, wherein the management control device has a plurality of criteria which determine whether there is a significant difference and issues a different kind of warnings for each criterion.
6. The fraudulence monitoring system of a table game according to claim 1 or 2, wherein the management control device has different determination criteria of a different significant difference for the number of games divided by a predetermined rule or for each of the predetermined number of games and issues a different kind of warnings.
7. The fraudulence monitoring system of a table game according to any one of claims 1 to 6, wherein the management control device determines whether there are significant differences for each game sequentially or every time the predetermined number of games is progressed in accordance with the progress of the plurality of games, and issues a warning when the determination criteria on the significant difference exceed.
8. The fraudulence monitoring system of a table game according to any one of claims 1 to 7, wherein the management control device has a plurality of criteria which determine whether there is a significant difference and specifies the game participant or the player position having the fraudulence possibility for each criterion to be able to display scores for each different criteria and display scores or ranks for warnings.
9. The fraudulence monitoring system of a table game according to any one of claims 1 to 8, wherein the management control device obtains the figures obtained by the probability statistic calculation used to determine whether there is a significant difference based on a conditional probability calculation when a specific element is a fixed value.
10. The fraudulence monitoring system of a table game according to any one of claims 1 to 9, wherein the management control device further includes a function which sequentially grasps playing cards or spots of dice from a series of games, and estimates the fraudulence cause in the case in which it is determined that there is a significant difference based on the data of the spots from a series of games and enumerates the fraudulence cause with the possibility.
11. The fraudulence monitoring system of a table game according to any one of claims 1 to 10, wherein the management control device estimates the fraudulence cause determined that there is the significant difference using any one or both of big data of past games or past fraudulent data, and enumerates the cause with the fraudulence possibility.
12. A fraudulence monitoring system of a table game, comprising:
an income and expenditure grasping device which grasps income and expenditure of a casino side for each game table in a plurality of game tables; and
a management control device which stores the number of games performed on each game table and sequentially grasps and stores a transition of the income and expenditure of the casino side in each game,
wherein the management control device includes a calculation function which compares results of the income or expenditure of the casino side with figures obtained by a probability statistic calculation at the time of an end of a predetermined number of games, on the basis of a calculation on a total number of games performed on each game table and the transition of the income and expenditure of the casino side in each game to determine whether there is a significant difference therebetween, and specifies any one of the game table or a room having the game table where the significant difference is occurring.
13. A fraudulence monitoring system of a table game, comprising:
a win or lose determination device which determines win or lose results for each game in a game table;
a bet chip measuring device which grasps an amount of game tokens that a game participant bets on the game table in each game; and
a management control device which stores the number of games performed on the game table and specifies positions and the amount of game tokens that the game participant places on the game table using a measurement result by the bet chip measuring device in each game and stores the specified positions and amount of game tokens in each game participant or player positions of the game table,
wherein the management control device includes artificial intelligence having data of a past fraudulent game taught as training data, and further includes a calculation function which refers to a total number of games in each game participant or player position, a transition of bet chip amounts for each game, a win or lose for each game, and a return amount obtained in each game as calculation basis and determines whether a significant difference with fraudulence possibility occurs in any one of the game participant or player position, the game table, or a room having the game table at the time of an end of a predetermined number of games.
14. The fraudulence monitoring system of a table game according to claim 13, wherein the management control device further includes a function which specifies dealers in each game and includes a function which specifies at least any one of a participant, a dealer, a player position, a game table, or a room having the game table of a series of games in which the significant difference occurs.
15. The fraudulence monitoring system of a table game according to claim 13 or 14, wherein the management control device includes a calculation function which factorizes the total return amount in a series of games in which the significant difference occurs to specify whether an occurrence cause of the significant difference in the series of games in which the significant difference occurs is due to the winning rate or due to a magnitude of a betted amount of a bet chip.
16. The fraudulence monitoring system of a table game according to claim 13 or 14, wherein the management control device includes a calculation function which stores the bet chip amounts for each game at the bet position having different return rates, and specifies whether the occurrence cause of the significant difference in a series of games in which the significant difference has occurred is associated with the bet position having different return rates.
17. The fraudulence monitoring system of a table game according to claim 13 or 14, wherein the management control device has a plurality of criteria which determine whether there is a significant difference and issues a different kind of warnings for each criterion.
18. The fraudulence monitoring system of a table game according to claim 13 or 14, wherein the management control device has different criteria of a different significant difference for the number of games divided by a predetermined rule or for each of the predetermined number of games and issues a different kind of warnings.
19. The fraudulence monitoring system of a table game according to claim 13 or 14, wherein the management control device has a plurality of criteria which determine whether there is a significant difference and specifies the game participant or the player position having the fraudulence possibility for each criterion to be able to display scores for each different criteria and display scores or ranks for warnings.
20. The fraudulence monitoring system of a table game according to any one of claims 13 to 19, wherein the management control device further includes a function which sequentially grasps playing cards or spots of dice from in a series of games, and estimates the fraudulence cause in the case in which it is determined that there is a significant difference based on the data of the spots from a series of games and enumerates the fraudulence cause with the possibility.
21. The fraudulence monitoring system of a table game according to any one of claims 13 to 20, wherein the management control device estimates the fraudulence cause in the case in which there is a significant difference using the big data of the past game as an additional item and enumerates the causes with the fraudulence possibility.
22. A fraudulence monitoring system of a table game, comprising:
an income and expenditure grasping device which grasps income and expenditure of a casino side for each game table in a plurality of game tables; and
a management control device which stores the number of games performed on each game table and sequentially grasps and stores a transition of the income and expenditure of the casino side in each game,
wherein the management control device includes artificial intelligence having data of a past fraudulent game taught as training data, and further includes a calculation function which compares results of the income or expenditure of the casino side with figures obtained by a calculation of the artificial intelligence having the data of the past fraudulent game taught as the training data on the basis of a calculation on a total number of games performed on the respective game tables and the transition of the income and expenditure of the casino side in each game to determine whether there is a significant difference therebetween, and determines a possibility that fraudulence occur in any one of the game table or a room having the game table where the significant difference is occurring.
23. A fraudulence monitoring program of a table game, comprising:
a win or lose determining step of grasping win or lose results for each game in a game table;
a bet chip grasping step of grasping an amount of game tokens that a game participant bets on the game table in each game;
a game progressing, grasping, managing step of storing the number of games performed on the game table and specifying bet patterns of the game tokens that the game participant places on the game table using transition data of a bet chip in the bet chip grasping step in each game and storing the specified bet patterns in each game participant or player positions of the game table; and
a step of verifying occurrence possibility of a fraudulence act, wherein the step of verifying the occurrence possibility of the fraudulence act includes:
a step of grasping and referring a total number of games in each game participant or player position, a transition of a bet chip amount, and a return amount for each game as a calculation basis;
a step of calculating an actual winning rate and a total return amount of each game participant or player position at the time of an end of a predetermined number of games;
a significant different determining step of comparing the obtained winning rate and total return amount with a winning rate and a total return amount based on a probability statistic calculation or past data to determine whether there is a significant difference therebetween in the predetermined number of games; and
an abnormal spot determining step of specifying any one of the game participant or player position, the game table, or a room having the game table where the significant difference is occurring.
24. The fraudulence monitoring program of a table game according to claim 23, wherein the step of verifying the occurrence possibility of the fraudulence act further includes a step of specifying dealers in each game and has a step of specifying the dealer responsible for the series of games in which the significant difference occurs in the abnormal spot determining step.
25. The fraudulence monitoring program of a table game according to claim 23 or 24, wherein the step of verifying the occurrence possibility of the fraudulence act further includes the artificial intelligence learning step that learns data of a past fraudulent game as training data.
26. The fraudulence monitoring system of a table game according to any one of claims 1 to 22, further comprising:
a device which specifies the game participant of the game table from the information on a face authentication system, ID card used, or a credit card used.
US16/649,191 2017-09-21 2018-09-19 Fraudulence monitoring system of table game and fraudulence monitoring program of table game Abandoned US20200226878A1 (en)

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Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11183012B2 (en) 2019-08-19 2021-11-23 Sg Gaming, Inc. Systems and methods of automated linking of players and gaming tokens
US11205319B2 (en) 2019-06-21 2021-12-21 Sg Gaming, Inc. System and method for synthetic image training of a neural network associated with a casino table game monitoring system
US11393282B2 (en) 2019-10-09 2022-07-19 Sg Gaming, Inc. Systems and devices for identification of a feature associated with a user in a gaming establishment and related methods
US11398127B2 (en) 2019-10-07 2022-07-26 Sg Gaming, Inc. Gaming systems and methods using image analysis authentication
US11495085B2 (en) 2020-07-13 2022-11-08 Sg Gaming, Inc. Gaming environment tracking system calibration
US11861975B2 (en) 2020-03-30 2024-01-02 Lnw Gaming, Inc. Gaming environment tracking optimization
US12080121B2 (en) 2020-03-30 2024-09-03 Lnw Gaming, Inc. Gaming state object tracking

Families Citing this family (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112891910B (en) * 2015-08-03 2024-10-08 天使集团股份有限公司 Cheating detection system for casino
US11049362B2 (en) 2017-09-21 2021-06-29 Angel Playing Cards Co., Ltd. Fraudulence monitoring system of table game and fraudulence monitoring program of table game
CN110889344A (en) * 2019-11-13 2020-03-17 哈工大机器人(合肥)国际创新研究院 Desktop game monitoring method and device
KR102372883B1 (en) * 2020-01-17 2022-03-11 그랜드코리아레저(주) Method and apparatus for detecting abnormal user based on game data
KR102547438B1 (en) * 2020-08-01 2023-06-23 센스타임 인터내셔널 피티이. 리미티드. Image processing method and device, electronic device and storage medium
JP2023511239A (en) * 2020-12-31 2023-03-17 商▲湯▼国▲際▼私人有限公司 Operation event recognition method and device
AU2021204528A1 (en) * 2021-06-24 2023-01-19 Sensetime International Pte. Ltd. Systems, methods, apparatuses, and computer-readable storage media for warning
WO2022269328A1 (en) * 2021-06-24 2022-12-29 Sensetime International Pte. Ltd. Systems, methods, apparatuses, and computer-readable storage media for warning
US11967200B2 (en) 2022-01-12 2024-04-23 Lnw Gaming, Inc. Chip tracking system
WO2023157068A1 (en) * 2022-02-15 2023-08-24 日本電気株式会社 Server device, system, server device control method, and storage medium

Family Cites Families (30)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2997692B2 (en) 1993-02-03 2000-01-11 アルゼ株式会社 Playground management system
US5605334A (en) * 1995-04-11 1997-02-25 Mccrea, Jr.; Charles H. Secure multi-site progressive jackpot system for live card games
US5761647A (en) * 1996-05-24 1998-06-02 Harrah's Operating Company, Inc. National customer recognition system and method
US6126542A (en) * 1997-08-11 2000-10-03 Boyd Gaming Corporation Gaming device and method offering primary and secondary games
US6460848B1 (en) * 1999-04-21 2002-10-08 Mindplay Llc Method and apparatus for monitoring casinos and gaming
JP2003070957A (en) * 2001-09-07 2003-03-11 Aruze Corp Game monitoring system and game playing table
US20080113783A1 (en) * 2006-11-10 2008-05-15 Zbigniew Czyzewski Casino table game monitoring system
US8337296B2 (en) * 2001-09-28 2012-12-25 SHFL entertaiment, Inc. Method and apparatus for using upstream communication in a card shuffler
JPWO2003082420A1 (en) 2002-03-28 2005-07-28 富士通株式会社 Playground chips, chip storage boxes, game tables, chip management systems
US7309284B2 (en) 2004-01-12 2007-12-18 Igt Method for using a light valve to reduce the visibility of an object within a gaming apparatus
CN1954346A (en) * 2004-04-15 2007-04-25 百利娱乐国际公司 Systems and methods for scanning gaming chips placed on a gaming table
JP2008522744A (en) * 2004-12-06 2008-07-03 ケイス ヴェンチャー マネージメント リミテッド ライアビリティ カンパニー System and method for interactive multi-participant games
US7559839B2 (en) * 2005-03-09 2009-07-14 Reuben Bahar Method and apparatus for verifying players' bets on a gaming table
US7389990B2 (en) * 2006-01-06 2008-06-24 Raphael Mourad Method of playing a card game involving a dealer
US7717429B2 (en) 2006-09-06 2010-05-18 Cfph, Llc Card game with counting
US8221244B2 (en) 2007-08-14 2012-07-17 John B. French Table with sensors and smart card holder for automated gaming system and gaming cards
US9082388B2 (en) 2012-05-25 2015-07-14 Bose Corporation In-ear active noise reduction earphone
AU2014200314A1 (en) * 2014-01-17 2015-08-06 Angel Playing Cards Co. Ltd. Card game monitoring system
US9734659B2 (en) * 2014-08-06 2017-08-15 Mido Play Inc. Single platform system for multiple jurisdiction lotteries and social media
JP2016093458A (en) 2014-11-12 2016-05-26 エンゼルプレイングカード株式会社 Table game system
JP6417203B2 (en) 2014-12-18 2018-10-31 株式会社ユニバーサルエンターテインメント Game table equipment
CN108055828B (en) * 2015-08-03 2021-10-15 天使集团股份有限公司 Management system for table game, substitute money for game, inspection device, and management system for substitute money for game
CN112891910B (en) * 2015-08-03 2024-10-08 天使集团股份有限公司 Cheating detection system for casino
JP6329927B2 (en) 2015-08-18 2018-05-23 株式会社ユニバーサルエンターテインメント GAME INFORMATION ANALYSIS SYSTEM, ANALYSIS SERVER, AND GAME INFORMATION ANALYSIS METHOD
US10573124B2 (en) 2015-08-18 2020-02-25 Universal Entertainment Corporation Game information analysis system
JP2017056166A (en) * 2015-09-14 2017-03-23 エンゼルプレイングカード株式会社 Abnormality detection system in game parlor
JP6679307B2 (en) 2015-12-15 2020-04-15 エンゼルプレイングカード株式会社 Table game management system and carton for disposal
JP6080145B1 (en) * 2016-07-05 2017-02-15 セガサミークリエイション株式会社 Game table and management system
JP2017094101A (en) * 2016-12-05 2017-06-01 エンゼルプレイングカード株式会社 Management system of table game and game token
US11049362B2 (en) 2017-09-21 2021-06-29 Angel Playing Cards Co., Ltd. Fraudulence monitoring system of table game and fraudulence monitoring program of table game

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11205319B2 (en) 2019-06-21 2021-12-21 Sg Gaming, Inc. System and method for synthetic image training of a neural network associated with a casino table game monitoring system
US12094288B2 (en) 2019-06-21 2024-09-17 Lnw Gaming, Inc. System and method for synthetic image training of a machine learning model associated with a casino table game monitoring system
US11183012B2 (en) 2019-08-19 2021-11-23 Sg Gaming, Inc. Systems and methods of automated linking of players and gaming tokens
US11398127B2 (en) 2019-10-07 2022-07-26 Sg Gaming, Inc. Gaming systems and methods using image analysis authentication
US11854337B2 (en) 2019-10-07 2023-12-26 Lnw Gaming, Inc. Gaming systems and methods using image analysis authentication
US11393282B2 (en) 2019-10-09 2022-07-19 Sg Gaming, Inc. Systems and devices for identification of a feature associated with a user in a gaming establishment and related methods
US12014597B2 (en) 2019-10-09 2024-06-18 Sg Gaming, Inc. Systems and devices for identification of a feature associated with a user in a gaming establishment and related methods
US11861975B2 (en) 2020-03-30 2024-01-02 Lnw Gaming, Inc. Gaming environment tracking optimization
US12080121B2 (en) 2020-03-30 2024-09-03 Lnw Gaming, Inc. Gaming state object tracking
US11495085B2 (en) 2020-07-13 2022-11-08 Sg Gaming, Inc. Gaming environment tracking system calibration

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