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- Nachgewiesen in: USPTO Patent Grants
- Sprachen: English
- Patent Number: 11961,355
- Publication Date: April 16, 2024
- Appl. No: 17/752087
- Application Filed: May 24, 2022
- Assignees: LNW Gaming, Inc. (Las Vegas, NV, US)
- Claim: 1. A method of controlling a network game, said method comprising: selecting, by an electronic processor, a winning card value of an undealt playing card for the network game, wherein the network game spans a plurality of gaming tables communicatively coupled to a network, wherein each of the plurality of gaming tables includes a deck of cards used for individual card games separate from the network game, wherein each of the plurality of gaming tables has a shuffler device communicatively coupled to the network, and wherein the shuffler device is configured to shuffle the deck of cards for the individual card games; detecting, by the processor in response to analyzing, by a machine learning model, of first image data captured at each of the plurality of gaming tables, that a playing card, having the winning card value, is dealt; determining, by the processor based on analysis of timing data from transceiver signals associated with a given shuffler device that dealt the playing card, a physical location of a closest one of the plurality of gaming tables relative to the given shuffler device; capturing, by the processor via environmental image sensors in a gaming environment at the physical location of the closest one of the plurality of gaming tables, second image data of any participants at the closest one of the plurality of gaming tables; determining, by the processor in response to the analyzing the second image data via the machine learning model, a participant to whom the playing card was dealt; and electronically validating, in response to determining the participant, a win for the network game with an electronic account for the participant.
- Claim: 2. The method of claim 1 further comprising: accessing, by the processor, shuffle data, game rules, and participant data for the individual card games associated with the plurality of gaming tables, wherein the shuffle data is generated via one or more sensors of each shuffler device at the plurality of gaming tables; determining, by the processor based on analysis of the shuffle data, a card order of an undealt portion for each deck of cards; predicting, by the processor, a timing for when a card, associated with the network game, will be dealt from one deck of cards at one of the plurality of gaming tables, wherein the predicting is based on the determined card order, the game rules, and the participant data; and coordinating an event for the network game with the timing.
- Claim: 3. The method of claim 2 , wherein the determining the card order of the undealt portion of each deck of cards comprises; analyzing a set of images captured of each individual card from the deck of cards at each of the plurality of gaming tables, wherein the set of images is captured by the one or more sensors when each shuffler device organizes each shuffled card into a randomized sequential order; identifying, via the machine learning model, a face value of each shuffled card from each of the set of images; assigning, in response to the identifying, a sequential position value to the face value for each card in the each of the of decks of cards, wherein the sequential position value corresponds to the randomized sequential order; and determining, based on analysis of data obtained via the environmental sensors in the gaming environment, a first sequential position value of a top card of the undealt portion of the deck of cards, wherein the top card and each card that follows in the randomized sequential order after the first sequential position value are the undealt portion.
- Claim: 4. The method of claim 3 , wherein the predicting, that the card will be dealt comprises; counting a number of sequential position values from the first sequential position value to a second sequential position value, in the randomized sequential order, which second sequential position value corresponds to the card; comparing the number of sequential position values against a minimum number of cards to be dealt during a subsequent game play round; and determining, based on the comparing, that the number of sequential position values is less than or equal to the minimum number of cards to be dealt.
- Claim: 5. The method of claim 4 further comprising: determining, in response to analysis of the participant data, a number of game participants at one of the plurality of gaming tables; determining, in response to analysis of the game rules, a minimum number of cards to be dealt per participant according to card distribution rules for a wagering game played at the one of the plurality of gaming tables; and multiplying the minimum number of cards to be dealt per participant by the number of game participants, wherein the minimum number of cards to be dealt during the subsequent game play round is equal to a product of the multiplying.
- Claim: 6. The method of claim 5 , wherein analysis of the participant data comprises analysis of environmental image data of one or more of placement of a bet or performance of a game-play action at the one of the plurality of gaming tables.
- Claim: 7. The method of claim 2 , wherein the coordinating comprises: in response to determination that the card will be dealt, providing an anticipatory indicator for presentation via one or more output devices located at the plurality of gaming tables.
- Claim: 8. The method of claim 7 , wherein the providing the anticipatory indicator comprises: synchronizing, by the game controller, presentation of the anticipatory indicator to begin before a contribution pool for the network game reaches a payout threshold value and to terminate after a payout threshold value is reached and after the card is dealt from one of the deck of cards.
- Claim: 9. The method of claim 2 further comprising: in response to the coordinating, electronically validating that the playing card was dealt.
- Claim: 10. The method of claim 9 , wherein the electronically validating comprises: determining, in response to analysis of the second image data by one or more machine learning models, an identity of the participant to whom the playing card was dealt; and associating the identity of the participant with an electronic account related to one or more of the participant, the closest one of the plurality of gaming tables at which the playing card was dealt, the network game, or the given shuffler device.
- Claim: 11. The method of claim 1 wherein determining the physical location of the closest one of the plurality of gaming tables relative to the given shuffler device comprises: electronically communicating, via an additional network, a first transceiver signal from the given shuffler device to any of the plurality of the gaming tables within a threshold range; storing first timestamp data for the first transceiver signal; receiving, in response to the first transceiver signal, one or more second transceiver signals transmitted by the any of the plurality of the gaming tables within the threshold range; storing second timestamp data in response to receipt of the one or more second transceiver signals; computing, based on analysis of the first timestamp data and the second timestamp data relative to a speed of light, a shuffler-device location, of the given shuffler, relative to the closest one of the plurality of gaming tables amongst the any of the plurality of the gaming tables within the threshold range; assigning, by the processor based on a shuffler-device location, the given shuffler device to a known gaming-table location of the closest one of the plurality of gaming tables; instructing, by the processor via the network in response to assigning the given shuffler device to the known gaming-table location, the environmental image sensors to capture the second image data, wherein the environmental image sensors are located in the gaming environment at the known gaming-table location, and wherein the second image data includes an image of the participant to whom the playing card was dealt.
- Claim: 12. The method of claim of 1 , wherein determining the physical location of the closest one of the plurality of gaming tables relative to the given shuffler device comprises using a time-of-flight characteristic or a time-difference-of-arrival characteristic related to the transceiver signals.
- Claim: 13. The method of claim 1 , further comprising capturing the first image data via an internal image sensor of the shuffler device at each of the plurality of gaming tables, and wherein the analyzing the first image data in response to capturing the first image data.
- Claim: 14. A system comprising: image-sensing devices; and an electronic game controller configured to control a network card game, wherein the plurality of image-sensing devices are communicatively coupled to the electronic game controller via a network, said system configured to store instructions, which, when executed by the electronic game controller, cause the system to perform operations to: select a winning card value for the network card game; obtain, via at least some of the plurality of image-sensing devices, first images of cards being dealt from decks of playing cards for a plurality of card games played at a plurality of gaming tables; detect, via analysis of the first images using a neural-network model, a card value of each card that is dealt at each of the plurality of gaming tables; determine, via comparison of each card value to the winning card value, that the playing card having the winning card value is dealt from one of the decks at one of the plurality of gaming tables; determine, based on analysis of timing data from transceiver signals associated with a card-handling device that dealt the playing card, a physical location of a closest one of the plurality of gaining tables that is closest in distance relative to the card-handling device; capture, via at least a portion of the image-sensing devices in a gaming environment at the physical location of the closest one of the plurality of gaming tables, second images of any participants at the closest one of the plurality of gaming tables; determine, via analysis of the second images using the neural-network model, a participant to whom the playing card was dealt; and electronically validate, with an electronic account associated with the participant, a win for the network card game in response to determination that the playing card was dealt.
- Claim: 15. The system of claim 14 , wherein the instructions that cause the system to perform the operations to electronically validate the win includes instructions, which, when executed by the electronic processor, cause the system to perform operations to: in response to determination that the playing card is dealt, associate, via an electronic memory, a first identifier value for the win with a second identifier value for one or more the card-handling device that handled the playing card prior to being dealt or a copy of at least a portion of the images of the cards handled by the card-handling device; and associate, via the electronic memory, the first identifier value with a time-stamp of a time at which the win occurred.
- Claim: 16. A system comprising: a plurality of shuffler devices, wherein each of the plurality of shuffler devices is configured to communicatively couple with a respective one of a plurality of gaming tables connected via a network; and an electronic game controller for a progressive jackpot game, wherein the plurality of shuffler devices are communicatively coupled to the game controller via the network, said electronic game controller configured to perform operations that cause the system to: detect a payout proximity trigger for the progressive jackpot game, wherein the progressive jackpot game is configured to pay out when a contribution pool reaches a payout threshold value; analyze, in response to detection of the payout proximity trigger, shuffle-state image data of each of the plurality of shuffler devices; determine, in response to analysis of the shuffle-state image data, a card order of an undealt portion for each deck of cards shuffled by the plurality of shuffler devices; determine, based on the card order and based on card distribution rules, that a mystery card will be dealt from one deck of cards shuffled by one of the plurality of shuffler devices for a subsequent game play round of a wagering game during which the payout threshold value is reached; determine, based on analysis of timing data from transceiver signals associated with the one of the plurality of shuffler devices, a physical location of a closest one of the plurality of gaming tables relative to the one of the plurality of shuffler devices; capture, via environmental image sensors in a gaming environment at the physical location of the closest one of the plurality of gaming tables, environmental image data of any participants at the closest one of the plurality of gaming tables; determine, in response to analysis of the environmental image data via a machine learning model, a participant to whom the mystery card was dealt; and electronically validate, in response to determination of the participant, a win for one or more of the wagering game or the progressive jackpot game with an electronic account for the participant.
- Claim: 17. The system of claim 16 , wherein the electronic game controller is configured to perform operations that cause the system to detect player activity at the plurality of gaming tables, wherein the plurality of gaming tables are associated with the progressive jackpot game, wherein the determining that the mystery card will be dealt for the subsequent game play round is based at least in part on the player activity; and wherein detection of the player activity is in response to analysis of the environmental image data of one or more of placement of a bet or performance of a game-play action.
- Claim: 18. The system of claim 16 , wherein the electronic game controller configured to determine the card order of the undealt portion for each deck of cards is configured to perform operations that cause the system to: analyze a set of images captured by one or more sensors of each shuffler device when the shuffler device organizes each individual card into a randomized sequential order; assign, via a neural network model, a sequential position value to each individual card in the each of the of decks of cards according to the randomized sequential order; determine, based on analysis of images of dealt cards, a top card of an undealt portion of at least one of the deck of cards; count a number of sequential position values in the sequential order from a top-card sequence position to a mystery-card sequence position in the at least one of the deck of cards; compare the number of sequential position values against a minimum number of cards to be dealt during the subsequent game play round for a wagering game for which the at least one of the deck of cards is used; and determine, based on the comparison, that the number of sequential position values is less than or equal to the minimum number of cards to be dealt.
- Claim: 19. The system of claim 18 , wherein the electronic game controller is configured to perform operations to cause the system to determine the minimum number of cards to be dealt being configured to perform operations to: determine a number of game participants for the wagering game; determine a minimum number of cards to be dealt per participant according to card distribution rules for the wagering game; and multiply the minimum number of cards to be dealt per participant by the number of game participants, wherein the minimum number of cards to be dealt during the subsequent game play round is equal to a product of the multiplication.
- Patent References Cited: 5722893 March 1998 Hill et al. ; 6886829 May 2005 Hessing et al. ; 7950663 May 2011 Schubert et al. ; 8100753 January 2012 Soltys ; 8702101 April 2014 Krenn et al. ; 9316597 April 2016 Blazevic ; 9474957 October 2016 Haushalter et al. ; 9776072 October 2017 Riordan et al. ; 10086260 October 2018 Grauzer et al. ; 10286291 May 2019 Wadds et al. ; 10343054 July 2019 Czyzewski et al. ; 10525328 January 2020 Riordan et al. ; 11113932 September 2021 Chun ; 20070238502 October 2007 Pokorny et al. ; 20080051169 February 2008 Michaelson et al. ; 20150021272 January 2015 Ko et al. ; 20160203672 July 2016 Acres ; 20160354678 December 2016 Grauzer et al. ; 20190060738 February 2019 Riordan ; 20200098223 March 2020 Lyons et al. ; 20200402342 December 2020 Kelly et al. ; 20220383698 December 2022 Lyons ; 03026763 April 2003 ; 2015021272 February 2015 ; 2015051312 April 2015
- Primary Examiner: Laneau, Ronald
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