METHODS FOR GAME PLAYER IDENTIFICATION

Abstract

One embodiment of the invention includes a method of monitoring behavior of a group of casino game players. The method includes identifying a group of casino game players for profiling; profiling the game players based upon their actions in a gaming establishment; and providing options for game play and service to the game players based upon their profile.

Description

RELATED APPLICATION

This application claims priority under 35 U.S.C. 119(e) from U.S. Provisional Application Ser. No. 60/640,663 filed Dec. 30, 2004, which application is incorporated herein by reference.

COPYRIGHT

A portion of the disclosure of this patent document contains material that is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all copyright rights whatsoever. The following notice applies to the software and data as described below and in the drawings that form a part of this document: Copyright © 2005, WMS Gaming Inc.

FIELD

This patent application pertains generally to gaming systems, and more particularly to methods for controlling a gaining machine in response to the machine's environment.

BACKGROUND

Gaming devices such as slot machines offer patrons to purchase an opportunity to plan a game of chance. Modem gaming devices typically employ a computer system and a display that presents a gaming interface to a patron. Patrons in a casino may be offered complimentary services, such as beverages. Casinos typically also includes security personnel who monitor activity of casino patrons. Improved gaming devices are needed.

SUMMARY

One embodiment of the invention includes a method of monitoring behavior of a group of casino game players. The method includes identifying a group of casino game players for profiling; profiling the game players based upon their actions in a gaming establishment; and providing options for game play and service to the game players based upon their profile.

Another embodiment includes a method of identifying suspicious gaming patron activity. The method includes collecting data regarding the activity of a multiplicity of gaming patrons; processing the data with a neural network to identify typical gaming patterns; and analyzing the activity of gaming patrons and identifying activity that departs from the typical gaming patterns.

One other embodiment includes a machine-assisted method. The method includes tracking the gaming activity of a patron; if the gaming activity of the patron meets a criterion, identifying the patron as a preferred status patron, collecting a biometric sample from the patron, and associating the biometric sample with patron's preferred status;

collecting biometric samples from patrons in a gaming establishment;

if one of the biometric samples collected from patrons in the gaming establishment matches the biometric sample of the preferred status patron, declaring that patron from whom the biometric sample was collected should receive preferred treatment.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example and not limitation in the accompanying drawings in which:

FIG. 1 is a flow chart that illustrates a method of operating a gaming device in accordance with a gaming protocol for a jurisdiction.

FIG. 2 is a perspective view of an embodiment of a gaming device.

FIG. 3 is a schematic illustration of components of a gaming device.

FIG. 4 is a schematic illustration of a server in communication with gaming devices over a network.

FIG. 5 is a schematic illustration of servers and gaming devices in communication through a network.

FIG. 6 is a flow chart that illustrates of a method of verifying the location of a gaming device.

FIG. 7 is a flow chart that illustrates a method of identifying suspicious gaming activity.

FIG. 8 is a schematic illustration of the operation of an activity tracking module.

FIG. 9 is a flow chart that illustrates a method of analyzing patron activity using a neural network.

FIG. 10 is a flow chart that illustrates a process by which patron activity is analyzed to detect identity theft.

FIG. 11 is a flow chart that illustrates a method of recognizing a preferred patron using a biometric sample.

FIG. 12 is a schematic representation of a gaming device system.

DETAILED DESCRIPTION

Methods and apparatus for sensing activity and location of a gaming device are described herein. In the following description, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In other instances, well-known circuits, structures, and techniques have not been shown in detail in to avoid obscuring the understanding of this description. Note that in the description, references to “one embodiment” or “an embodiment” mean that the feature being referred to is included in at least one embodiment of the invention. Further, separate references to “one embodiment” in this description do no necessarily refer to the same embodiment; however, neither are such embodiments mutually exclusive, unless so stated and except as will be readily apparent to those of ordinary skill in the art. Thus, the present invention can include any variety of combinations and/or integrations of the embodiments described herein. Moreover, in this description, the phrase “exemplary embodiment” means that the embodiment being referred to serves as an example or illustration.

This description is divided into four sections. First, an exemplary gaming device and exemplary gaming environments are described. The, techniques for detecting tampering and suspicious gaming are described. Next, the use of biometric sensing with gaming devices, systems, and methods is described. Then, geolocation of gaming devices is described.

Exemplary Gaming Devices, Systems and Environments

Referring now to FIG. 1, a gaming device 10 is in communication with a biometric processing system 20. A biometric sensor 30 such as a video camera sends a biometric sample to the biometric processing system, which compares the biometric sample against a database of biometric samples 40. The biometric processing system is preferably a networked system that is remote from the gaming device, but can also be a component of the gaming system. In an embodiment, the biometric sensor is connected to the biometric system through a network. The biometric sensor can also be connected to the gaming device that is configured to send the biometric sample to the biometric processing system. A global positioning system (GPS) 50 is in communication with the gaming device.

FIG. 2 shows a perspective view of an example of a gaming device 200. One or more central processing units (CPU's) (not shown) interacts with a memory circuit, data storage, and a network interface to present a game of chance on a display 225. A patron can interact with the gaming device through an input mechanism 230 such as buttons 231. The input mechanism can also include a touch-sensitive screen, a lever arm, or other known input mechanisms. A gaming device typically can receive payment for game play through one or more of a bill collector 233, coin slot 234, or card slot 234. The device typically can provide a payoff in coin form or on a card.

FIG. 3 shows schematic representation of a gaming device system. A game is played through a CPU that is coupled to a memory circuit 310 and data storage 315 such as a hard drive. A network interface 320 allows the gaming device to interact with a server (not shown in FIG. 3) to coordinate multiple devices, for example in a progressive jackpot environment. A display device 325 presents game choices and results to a patron. In varying embodiments, advertisements, entertainment, videos, or other content can also be presented on the display device. An input 330 such as a button system or touch-sensitive screen allows input from a game patron. A coin/credit detector 340 monitors receipt of payment for game play through coins, bills, cash-value cards, player tracking cards, or credit cards. A separate card reader 375 can also be provided and configured to read a patron tracking card. In varying embodiments, gaming devices are networked, and player activity is tracked throughout one or more casinos player's tracking card.

A payoff mechanism 345 allows for payoff through coins, bills, or a card. A switch 335 allows the device to be shut off. A light sensor 355 is configured inside the gaming device to detect if the gaming device is opened. A motion sensor 360, such a tilt sensor, is configured to detect movement of the device. A biometric sensor 365 such as a video sensor is configured to detect a patron in the vicinity of the device. A global positioning system 370 is mounted in the gaming device and coordinated with a satellite system to identify the geographic location of the gaming device. It is understood that FIGS. 2 and 3 are merely examples, and that a variety of gaming device systems are possible. While various components are shown in communication with the CPU for sake of illustration, it is understood that components can also communicate with each other, and that various components are connected through one or more system buses or other connections.

Referring now to FIG. 4, a networked gaming environment is schematically illustrated. A server 410 is connected to a network 420 through a wired or wireless system. A plurality of gaming devices 430 are connected to the network. In varying embodiments, the network 420 is a private network or a public network, and includes a plurality of networks connected together. In an embodiment, the network 420 includes the Internet. The networked gaming environment can allow gaming devices 430 to communicate with a server or with each other. In an embodiment, for example, a progressive jackpot is accumulated based upon activity in multiple games and coordinated by a remote system through server 410.

FIG. 5 provides a schematic illustration of another exemplary networked gaming environment. A server 505 is connected to a network 510. Gaming devices 515 and 520 are connected to the network and in communication with the server through the network. A second server 525 can also be connected to the network 510. A second network 530 is connected to the main network 510 through the second server 525. Gaming devices 535, 540, 545 are connected to the second server 525 through the second network 530. A gaming device can also include a global positioning unit that communicates with a global positioning satellite 550 to identify the location of the device.

Detecting Tampering or Suspicious Gaming

In varying embodiments, techniques are used to detect tampering with a gaming device. In an embodiment, physical access to the device is detected using a light sensor or motion sensor. For example, in an embodiment, a light sensor is configured so that if a sealed machine is opened, the light sensor detects light that enters the machine when it is opened. This event is communicated to a security system and/or security personnel through a network connection. In another embodiment, a motion sensor is configured to detect movement of a device or motion inside a device and send a notice of the movement. This allows detection that a machine is being stolen, abused, or otherwise tampered with. In varying embodiments, evidence of possible tampering is analyzed by the gaming device, or by a computer system accessible through a network.

In varying embodiments, tampering or other improper use of gaming devices is detected by monitoring user activity. Referring now to FIG. 6, a tracking module 610 tracks the activity of a gaming patron. Profile module 620 develops a patron gaming profile based on the activity of the gaming patron. Compare module 630 compares the activity of the gaming patron to the gaming profile for the gaming patron. Detect deviation operation 640 determines whether the activity of the gaming patron deviates from the patron gaming profile. If the activity of the patron deviates from the patron gaming profile, declare module 650 declares that the patron activity is suspicious. If the activity of the patron does not deviate from the patron gaming profile, tracking module 610 continues tracking the patron.

In varying embodiments, patron activity is be tracked through other techniques, including player identification cards. A tracking card is an object, usually a card that fits in a wallet, that contains a unique code for a game patron. In varying embodiments, a bar code, magnetic code, or radio frequency identification (RFID) tag is used as a patron identification code. Embodiments of gaming devices are equipped with a code reader, so that the machine can recognize the gaming patron. As the patron engages games in a casino (or multiple casinos), the patron's activity is tracked through the tracking card, and unusual patron behavior is identified, monitored, and analyzed. For example, unusual cash out patterns or betting patterns by a particular patron are tracked as the patron visit gaming machines or casinos.

FIG. 7 is a schematic illustration information collected by an exemplary tracking module 700. The tracking module collects information from a patron's tracking card 710, a patron's inputs to the game 720, such as the pressing of buttons or the screen, non-input touching of the display screen 730, and purchase of gaming credits 740 including the insertion of bills in the device and the value of bills inserted, and the insertion of coins. The tracking module also collects betting pattern 750 and cash out patterns 760, as well as the types of games played 770.

In varying embodiments, the user inputs and cash out occurrences are monitored and analyzed by one or more computer systems to identify unusual or suspect behavior. For example, a pattern of bill insertion soon followed by a cash out can indicate the use of counterfeit currency. Unusual cash out patterns can also indicate that tampering is occurring. More complex patterns, or departures from expected patterns, can also be detected. For example, repeated or unusual sequences of user inputs can indicate tampering or other improper use of a gaming device that should be investigated.

In another embodiment, tampering or improper use are detected by monitoring activity across a number of networked devices. Activity patterns are observed and stored, and patron activity is compared to observed patterns. For example, new patron activity is compared against stored activity patterns, and patron activity that deviates from the range of activity predicted by the patterns is identified as suspicious. Instances of identification theft, for example through a stolen credit card, are detected.

In varying embodiments, a gaming profile (or “signature”) are developed for an individual gaming patron, or for patrons generally. In an embodiment, if the activity of a gaming patron deviates from his or her gaming profile, a possible case of identity theft is declared and investigated. In another embodiment, a general profile that applies to patrons generally is developed based upon ranges of activity that are expected from gaming patrons. If a particular gaming patron's activity deviates from a range of activity predicted by the general profile, the patron is declared suspicious, and responsive action is taken. In varying embodiments, patron activity are analyzed with a neural network. Neural networks are discussed in U.S. Pat. Nos. 6,067,535, 6,038,555, 5,966,650, 5,010,512, and 4,876,731, which are incorporated herein by reference.

In an embodiment, unusual or idiosyncratic gaming activity is used to identify a particular patron from a group of patrons. For example, tracking sufficient unusual input sequences occurring at a multiple devices, or sequential use of devices, allows identification of a particular patron.

Referring now to FIG. 8, a method of analyzing patron activity is shown. Collect data module 810 collects data regarding the activity of a multiplicity of gaming patrons. Neural network module 820 processes the data with a neural network to identify typical gaming patterns. Analyze module 830 analyzes the activity of gaming patrons in view of patterns identified by the neural network and identifies activity that departs from typical gaming patterns.

In an embodiment, both an individual and a general profile are used to detect possible identity theft. Referring now to FIG. 9, collect data module 910 collects data regarding the activity of a multiplicity of gaming patrons. Patron profile module 920 identifies the gaming activity of an individual gaming patron and develops a gaming profile for the individual gaming patron. Data collection module 930 collects further activity associated with the patron. For example, in an embodiment, activity associated with a patrons tracking card or credit card is tracked. Profile match operation 940 determines whether the activity of the gaming patron matches the profile. If the activity does not match the profile, declare identity theft module 950 declares a possible identity theft. If the activity does match the individual patron profile, tracking module 960 continues tracking patron activity. A profile for the general population is also developed: Profile module 970 develops a profile for a general gaming population that predicts a range of expected gaming activity. Suspicious activity operation 980 determines whether gaming activity that falls outside the range of expected gaming activity. If the activity of a gaming patron falls outside the range of expected gaming activity, a possible gaming theft is declared.

Biometric Sensing

In varying embodiments, biometric techniques are used to identify and/or track patrons. In an embodiment, a video sensor in a gaming establishment and is connected to a computer system that analyzes data from the video sensor. A video sensor, such as a video camera, is configured to communicate with a gaming device or other computer system through a wired or wireless direct connection or through a network. Facial recognition technology is used to identify a patron from a video image. A faceprint is generated from the image. The faceprint is compared to face prints in a faceprint database to identify a patron of interest.

In varying embodiments, a list of patrons is designated for VIP treatment: If the faceprint of a VIP patron is identified from a video image, special services is directed to the patron.

Referring now to FIG. 10, a tracking module 1010 tracks the gaming activity of a patron. A preferred patron identifier operation 1020 determines whether the gaming activity of the patron meets a criterion. If the activity of the patron meets a criterion, status module 1030 identifies the patron as a preferred status patron. Biometric sample module 1040 collects a biometric sample from the patron. Associate status module 1050 stores the biometric sample and associates the biometric sample with the patrons preferred status. Collect data module 1060 collects a new biometric sample from a patron in a gaming establishment. Identify preferred patron module 1070 determines whether the newly collected biometric sample matches the stored biometric sample of the preferred status patron. Preferred treatment module 1080 declares that the patron from whom the new biometric sample was collected should receive preferred treatment.

In other embodiments, faceprints for other categories of patrons are be cataloged and referenced. In an embodiment, faceprints of problem gamblers, banned patrons, and minors are tracked. In one embodiment, a known minor is recognized. In another embodiment, a faceprint is analyzed to determine whether the patron is a minor, based upon the dimensions of the faceprint.

In another embodiment, biometric technology is used to confirm that the patron using a tracking card is actually the patron associated with the tracking card. In varying embodiments, a gaming device compares the patron identity indicated by a player tracking card to the identity associated with a faceprint of the patron who is using the machine to determine whether the patron using the card is actually the patron associated with the card. This confirmation of patron identity prevents a patron from lending a tracking card to another patron. Instances of fraudulent use of tracking cards is also identified. Gaming devices that are equipped with facial recognition technology generally require increased storage and processing capacity compared to comparable gaming systems that lack recognition technology.

Other biometric techniques can also be used to identify patrons. For example, in an embodiment, fingerprint scanning or iris scanning techniques are used to recognize a patron. Biometric sampling and analysis is further described in U.S. Pat. Nos. 6,810,480, 6,810,135, 6,801,641, 6,783,459, 6,728,881, 6,722,985, 6,709,333, 6,612,928, and 6,508,709, which are incorporated herein by reference.

Geolocation

In an embodiment, gaming device includes a system for identifying the geographic location of the device. In one embodiment, a global positioning system (GPS) is used to locate the device. Global positioning systems are described in U.S. Pat. No. 6,104,815, which is incorporated herein by reference. In another embodiment, a cellular transmission is used to locate the gaming device through triangulation.

In another embodiment, an internet protocol is used to identify where a gaming device is located. In an embodiment, a traceroute check can follow the path that TCP/IP packets take going from one point to another and identify the source of a transmission. Alternatively, an IP address is be checked against a database of countries of origin of IP addresses or a database of IP address owners. A geolocation database is available from QUOVA, INC, for example. Further geolocation techniques are described in U.S. Pat. No. 6,684,250, which is incorporated herein by reference. In an embodiment, operation of a gaming device that is operating from an illegitimate IP address (e.g. from an IP address that differs from the realm of expected IP addresses) is detected and discontinued.

In varying embodiments, geolocation techniques allow identification of illegal or unauthorized operation of a gaming machine. For example, identification of the geographic location of a gaming device allows for detection a stolen gaming device or unauthorized transport of the game. In an embodiment, if a gaming device is operated in an unauthorized or unexpected location, the unauthorized use device is handled through deactivation, retrieval, or blockage of network access to a gaming network.

In another embodiment, a portable gaming devices is controlled or disabled based upon data received from a geographic locating system and a database of data for geographic regions. In varying embodiments, gaming devices on cruise ships or aircraft are be located, and that operation of the gaming device is coordinated with jurisdictional regulations as the craft moves about the world. For example, if a cruise ship moves to waters where gaming is not permitted, the gaming device is shut off.

In an embodiment, a gaming device is automatically configured to comply with regulations in a jurisdiction where gaming is permitted, based upon the data received from a geographic locating system. For example, a geographic locating system also allows a device to be configured based upon which casino it is placed in. In an embodiment, a database of geographical coordinates for casinos is maintained, and a gaming device is matched to a particular casino based upon the geographic locating data obtained from the device. A database of configuration information for the casinos is maintained and used to configure gaming devices based upon which casino matches the gaming device location.

Referring now to FIG. 11, a database 20 includes gaming protocols associated with jurisdictions. In an embodiment, protocol module 1110 stores gaming protocols designed to comply with the laws of particular states or reservations. Locate device module 1120 identifies the location of the gaming device. Jurisdiction module 1130 identifies a jurisdiction to which the gaming device is subject, based on the location of the gaming device. Operate module 1140 selects a protocol from the database and operates the gaming device in accordance with the gaming protocol for the identified jurisdiction.

In varying embodiments, anti-spoofing strategies are used to prevent faking of a device location. For example, multiple geolocating systems are employed so that a spoofed location is identifiable from inconsistencies among the systems.

Referring now to FIG. 12, a method of confirming the location of a gaming device is shown. GPS locate module 1210 locates a gaming device using a global positioning system (GPS). Jurisdiction module 1220 identifies a jurisdiction based upon the location of the gaming device. Communication module 1230 communicates from the gaming system to a remote system through an internet connection. IP locate module determines the internet protocol (IP) address from which the communication is sent. Confirm location module 1240 determines whether the IP address is consistent with the location of the gaming device determined by the GPS. Is the IP address is inconsistent with the location of the gaming device determined by the GPS, the device is disabled.

Claims

1. A method of monitoring behavior of a group of casino game players, comprising:

Identifying a group of casino game players for profiling;

Profiling the game players based upon their actions in a gaming establishment; and

Providing options for game play and service to the game players based upon their profile.

2. The method of claim 1 wherein the profiles are categorized.

3. The method of claim 2 wherein the categories comprise one or more of high rollers, gambling addicts and game cheaters.

4. The method of claim 1 wherein profiling is performed using artificial intelligence.

5. The method of claim 1 wherein options are provided using artificial intelligence.

6. The method of claim 1 wherein the players are profiled using biometric parameters.

7. The method of claim 1, further comprising maintaining a database of players and a profile for each player.

8. The method of claim 6, further comprising maintaining options for game play and for service for each player in the database.

9. The method of claim 1 wherein the options include limiting access to gaming machines for players having a preselected profile.

10. The method of claim 1 wherein the options include providing additional services for players having a preselected profile.

11. The method of claim 1 wherein the options include banning players having a preselected profile from playing games.

12. The method of claim 1 wherein the options include monitoring player behavior and identifying correlations with behavior of other players.

13. The method of claim 11 wherein correlations are identified with artificial intelligence.

14. A method of identifying suspicious gaming patron activity comprising:

collecting data regarding the activity of a multiplicity of gaming patrons;

processing the data with a neural network to identify typical gaming patterns; and

analyzing the activity of gaming patrons and identifying activity that departs from the typical gaming patterns.

15. The method of claim 13 comprising identifying the gaming activity of an individual gaming patron and developing a gaming profile for the individual gaming patron from the data collected from the individual gaming patron.

16. The method of claim 14 further comprising comparing the activity of a gaming patron to the patron's gaming profile and declaring a possible identify theft if the activity of the gaming patron deviates from the patron's gaming profile.

17. The method of claim 13 comprising processing data from a general gaming population to develop a range of expected gaming activity, and identifying gaming activity that falls outside the range of expected gaming activity as suspicious.

18. The method of claim 13, further comprising processing data to identify behavior indicative of a conspiracy by more than one patron to defraud a casino.

19. The method of claim 17, further comprising analyzing the behavior of groups of patrons in order to identify conspiracies.

20. A machine-assisted method comprising:

tracking the gaming activity of a patron;

if the gaming activity of the patron meets a criterion, identifying the patron as a preferred status patron, collecting a biometric sample from the patron, and associating the biometric sample with patron's preferred status;

collecting biometric samples from patrons in a gaming establishment;

if one of the biometric samples collected from patrons in the gaming establishment matches the biometric sample of the preferred status patron, declaring that patron from whom the biometric sample was collected should receive preferred treatment.

21. The method of claim 19, further comprising developing a profile for identifying high rollers and comparing a patron's activities to the profile.