Fraudulence monitoring system of table game and fraudulence monitoring program of table game
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.
1. A fraudulence monitoring system comprising:
a game tracking unit configured to track each of a plurality of games played on a game table;
at least one second sensor configured to detect objects on the game table; and
a processor that is communicatively coupled to the game tracking unit and to the at least one second sensor, the processor is configured to:
track, based on communication with the game tracking unit, a plurality of games played at the game table;
based on the processor being coupled to the game tracking unit and to the at least one second sensor, correlate respective movements of the objects on the game table to respective ones of the tracked plurality of games, and thereby identify results regarding a respective income and a respective expenditure of a casino side at the game table for each of the plurality of games;
at an end of a predetermined number of the plurality of games, compare the results regarding the identified respective incomes and the identified respective expenditures of the casino side over the predetermined number of the plurality of games with corresponding figures obtained by a probability statistic calculation to determine whether there is a significant difference therebetween according to each of a plurality of predefined criteria; and
based on a determination that the significant difference is present:
identify according to which of the plurality of predefined criteria the significant difference was identified; and
identify the game table from a plurality of game tables and/or a room having the game table where the significant difference occurred.
2. The fraudulence monitoring system according to claim 1 , wherein the processor is configured to factorize a total return amount of a respective game participant in a series of games in which the significant difference occurs to determine whether a cause of the significant difference in the series of games in which the significant difference occurs is due to a respective winning rate of the respective game participant or due to a magnitude of a betted amount.
3. The fraudulence monitoring system according to claim 1 , wherein the processor is configured to, for each of the plurality of games, for each of at least one game participant or for each of at least one player position, store an indication of an identified respective amount of game tokens in association with a respective return rate, and determine whether a cause for the significant difference is one or more of the return rates.
4. The fraudulence monitoring system according to claim 1 , wherein the processor is configured to select one or more of a plurality of predefined warnings for output in response to the significant difference and according to which particular criteria of the plurality of predefined criteria the significant difference was determined.
5. The fraudulence monitoring system according to claim 4 , wherein the particular criteria includes a quantification of a difference based on a number of at least one game divided by a predetermined rule.
6. The fraudulence monitoring system according to claim 1 , wherein the processor is configured to perform the comparison to determine whether there is the significant difference for each of at least two sequentially played ones of the plurality of games or in response to the predetermined number of the plurality of games, and issue a warning when the significant difference is determined to be present.
7. The fraudulence monitoring system according to claim 1 , wherein the processor is configured to determine respective scores for each of the plurality of predefined criteria.
8. The fraudulence monitoring system according to claim 1 , wherein the processor is configured to determine whether the significant difference is present based on a conditional probability calculation.
9. The fraudulence monitoring system according to claim 1 , wherein the processor is configured to identify cards or identify spots of dice used in the plurality of games, and determine a cause of the significant difference based on the identified cards or the identified spots.
10. The fraudulence monitoring system according to claim 1 , wherein the processor is configured to identify and output a cause of the significant difference.
11. The fraudulence monitoring system according to claim 1 , wherein the processor is configured to:
determine whether the significant difference is present by executing an artificial intelligence program developed with data of a past fraudulent game as training data; and
identify the game table from the plurality of game tables and/or the room having the game table where the significant difference occurred.
12. The fraudulence monitoring system according to claim 1 , wherein the processor is configured to:
identify respective dealers managing respective ones of the plurality of games; and
determine which of a plurality of game participants, which of the dealers, and/or which of a plurality of player positions, is associated with occurrence of the significant difference.
13. The fraudulence monitoring system according to claim 1 , wherein the processor is configured to identify each of at least one game participant using a face authentication, information obtained from an ID card, or information from a credit card that is used.
14. The fraudulence monitoring system according to claim 1 , wherein the processor is configured to identify the results regarding the respective income and the respective expenditure even regarding one or more of the objects that are at least partially hidden from view based on input from the at least one second sensor.
15. The fraudulence monitoring system according to claim 14 , wherein the at least one second sensor includes a camera and/or a Radio Frequency Identification (RFID) sensor.
16. The fraudulence monitoring system according to claim 1 , wherein the at least one second sensor includes a camera and/or a Radio Frequency Identification (RFID) sensor.
17. The fraudulence monitoring system according to claim 1 , wherein the objects being sensed by the at least one second sensor include game tokens and/or currency.