Derivative works — US Patent 10629024

Defensive Disclosure: Derivative Variations of US Patent 10,629,024

This document outlines derivative variations of US Patent 10,629,024, "Systems, methods, and media for implementing internet-based wagering," to serve as defensive disclosure and establish prior art for future incremental improvements in the domain of enhanced online wagering systems. The variations are systematically derived from the independent claims, particularly Claim 1, to cover a broad scope of potential advancements.

Derivatives Based on Independent Claim 1 (System)

Claim 1: A system for wagering, comprising: a roulette wheel; a ball configured to be used in the roulette wheel; a hardware processor configured to: receive first bet information for a first bet from a first player device of a first player on a spin of the roulette wheel, the first bet information corresponding to at least a first position on the roulette wheel; receive second bet information for a second bet from a second player device of a second player on the spin of the roulette wheel, the second bet information corresponding to at least a second position on the roulette wheel that is different from the first position; determine that the roulette wheel and the ball have been spun for the spin of the roulette wheel; randomly select a first selected position on the roulette wheel for the spin of the roulette wheel prior to the ball falling into a position on the roulette wheel, wherein the first selected position is the same as the first position; determine a first payout for first position and a second payout for the second position for the spin of the roulette wheel, wherein the first payout is higher than the second payout; determine that the ball has fallen in the first position for the spin of the roulette wheel; and indicating that the first player is to be paid at the first payout for the spin of the roulette wheel.

1. Material & Component Substitution

Derivative 1.1: Automated Electromagnetic Ball Propulsion and Sensor Array

Enabling Description: The physical roulette wheel remains, but the conventional human dealer is replaced by an automated electromagnetic ball propulsion system, such as a pulsed solenoid array embedded beneath the wheel track, precisely timed to impart initial velocity to a ferrous or magnetically-tagged ball. The wheel sensor (104) is augmented with a high-resolution, multi-spectral camera array (e.g., CMOS sensors operating in visible and infrared spectra) coupled with a phased-array ultrasonic transponder network. This sensor array provides real-time, sub-millimeter tracking of the ball's trajectory, velocity, and deceleration using optical flow algorithms and acoustic time-of-flight measurements. The hardware processor (108) integrates these data streams to predict the ball's landing pocket with a higher probability distribution, enabling more precise timing for the "prior to the ball falling" random selection. The roulette wheel itself is constructed from a low-friction polymer composite (e.g., PTFE-coated carbon fiber) to minimize mechanical wear and ensure consistent ball dynamics, reducing environmental variability.

graph TD
    A[Automated Electromagnetic Propulsion] --> B(Ferrous/Magnetically-tagged Ball)
    B --> C[Roulette Wheel (Polymer Composite)]
    C --> D[Multi-spectral Camera Array]
    C --> E[Phased-Array Ultrasonic Network]
    D --> F{Hardware Processor 108}
    E --> F
    F --> G[Real-time Ball Tracking & Prediction]
    F --> H[Dynamic Payout Calculation Module]
    G --> H
    H --> I[Player Devices 130, 132, 134]
    I --> F
    F --> J[Display/Visual Effects 136]

Derivative 1.2: Holographic Projection Roulette with Haptic Feedback

Enabling Description: This derivative replaces the physical roulette wheel and ball with a high-fidelity, interactive holographic projection system. The "roulette wheel" and "ball" are rendered via a multi-emitter laser interferometer projecting a 3D volumetric image onto an aerosol or plasma medium, providing a visually indistinguishable experience from a physical wheel. Player devices (130, 132, 134) incorporate haptic feedback modules (e.g., piezoelectric actuators or vibrotactile arrays) to simulate the tactile sensation of placing chips or the "thud" of a ball dropping. The "spin determination" and "ball fall determination" are entirely simulated by a quantum random number generator (QRNG) integrated with the core application computer (108), ensuring true randomness. The "positions" on the wheel are dynamic holographic segments, capable of changing visual characteristics (e.g., color, intensity) to indicate randomly selected enhanced payout positions.

graph TD
    A[QRNG] --> B{Core Application Computer 108}
    B --> C[Multi-emitter Laser Interferometer]
    C --> D[Aerosol/Plasma Medium]
    D --> E(Holographic Roulette Wheel & Ball)
    B --> F[Haptic Feedback Module]
    F --> G[Player Devices 130, 132, 134]
    G --> B
    E --> G
    B --> H[Dynamic Holographic Payout Indicator]

2. Operational Parameter Expansion

Derivative 2.1: Ultra-High Frequency Micro-Roulette for Distributed Micro-Wagering

Enabling Description: The system is scaled down to a micro-electromechanical system (MEMS) roulette wheel, approximately 1-2 millimeters in diameter, fabricated using photolithography and driven by electrostatic or micro-magnetic actuators. The "ball" is a sub-micrometer ferrofluid droplet or a dielectric microparticle, propelled by precisely controlled electric fields. This micro-roulette spins at ultra-high frequencies (e.g., 10,000+ RPM), completing a "spin" cycle and ball-drop simulation within milliseconds. "Bet information" is received via a specialized, low-latency API from embedded player agents on IoT devices (e.g., smartwatches, smart home hubs) enabling distributed micro-wagering with extremely small bet amounts (e.g., fractions of a micro-bitcoin). The hardware processor (108) is a distributed array of field-programmable gate arrays (FPGAs) performing parallel processing for high-throughput bet aggregation and near-instantaneous payout determination. Optical coherence tomography (OCT) provides real-time detection of the microparticle's position.

graph TD
    A[IoT Player Agents] --> B(Low-Latency API)
    B --> C{FPGA Array 108}
    C --> D[Micro-Magnetic/Electrostatic Actuators]
    D --> E[MEMS Roulette Wheel]
    E --> F[Microparticle Ball (Ferrofluid/Dielectric)]
    F --> G[Optical Coherence Tomography (OCT)]
    G --> C
    C --> H[Distributed Payout Processing]
    H --> B

Derivative 2.2: Extreme-Temperature Thermally-Actuated Roulette for Industrial Simulation

Enabling Description: The system is adapted for industrial simulation environments operating at extreme temperatures (e.g., -200°C to 1000°C). The "roulette wheel" is a ceramic composite (e.g., silicon carbide) or superalloy wheel actuated by thermal expansion/contraction mechanisms (e.g., shape memory alloy actuators or thermoelectric coolers/heaters). The "ball" is a small, high-density, inert ceramic sphere (e.g., zirconia) or a metal alloy with a high melting point, propelled pneumatically by inert gases. Sensor data is gathered via high-temperature-rated optical pyrometers and thermal imaging cameras for "spin determination" and "ball fall determination." The "bets" represent probabilistic outcomes in complex industrial processes (eg., material flow in a blast furnace, yield in a chemical reactor). The "payouts" translate into resource allocation efficiency or process optimization bonuses. The hardware processor (108) is housed in a cryo-cooled or passively-cooled enclosure, executing probabilistic simulation models to "randomly select" optimal process parameters which, if matched by real-world conditions (the "ball falling"), yield enhanced efficiency (the "higher payout").

graph TD
    A[Industrial Process Sensors] --> B{Hardware Processor 108 (Temp-Controlled)}
    B --> C[Thermal Actuators (SMA/Thermoelectric)]
    C --> D[Ceramic/Superalloy Roulette Wheel]
    D --> E[Inert Gas Pneumatic Propulsor]
    E --> F[Ceramic/Metal Ball]
    F --> D
    D --> G[Optical Pyrometers & Thermal Cameras]
    G --> B
    B --> H[Process Optimization & Resource Allocation]

3. Cross-Domain Application

Derivative 3.1: Predictive Maintenance & Supply Chain Optimization in Logistics

Enabling Description: The system is re-purposed for dynamic routing and predictive maintenance in a large-scale logistics network. The "roulette wheel" represents a geographical map with "positions" being critical transport hubs or individual delivery vehicles. The "ball" represents a potential anomaly or critical event (e.g., vehicle breakdown, adverse weather affecting a route). "First bet information" could be a logistics manager betting on a specific hub/vehicle to not experience an issue, while "second bet information" is a bet on a different hub/vehicle. The "hardware processor" (108) ingests real-time sensor data (GPS, telematics, weather forecasts) and historical performance data. "Spin determination" corresponds to the start of a new operational period. "Randomly selecting a first selected position" means the system (using AI/ML models) identifies a specific hub/vehicle (the "first position") that could be optimized or might fail, before the actual event. If the actual operational outcome (the "ball falling") matches this predicted "first position" (e.g., successful proactive maintenance avoiding failure, or unexpected efficiency gains), an "enhanced payout" (e.g., bonus points for the manager, optimized resource allocation) is triggered.

graph TD
    A[GPS/Telematics Sensors] --> B{Hardware Processor 108 (AI/ML)}
    C[Weather Data API] --> B
    D[Historical Performance DB] --> B
    B --> E[Real-time Network Map (Roulette Wheel)]
    E --> F[Critical Hubs/Vehicles (Positions)]
    B --> G[Predictive Anomaly Detection]
    G --> H[Manager Input (Bet Information)]
    H --> B
    B --> I[Dynamic Payout/Optimization Trigger]
    J[Actual Operational Outcome] --> I

Derivative 3.2: Personalized Learning Path Gamification in Education

Enabling Description: This system is applied to gamify personalized learning paths within an adaptive educational platform. The "roulette wheel" is a student's curriculum, with "positions" representing specific learning modules, skill competencies, or challenging problems. The "ball" is the student's current learning engagement or performance trajectory. "First bet information" is the student (or an AI tutor agent on their behalf) "betting" that they will master a particular challenging module (first position) within a session. "Second bet information" is a bet on a different, perhaps easier, module. The "hardware processor" (108) monitors student progress, engagement, and cognitive load using various sensors (e.g., eye-tracking, keyboard/mouse activity, correct/incorrect answer ratios). "Spin determination" signifies the start of a new learning segment. "Randomly selecting a first selected position" means the AI tutor proactively identifies a specific learning module (that the student "bet" on) to be "boosted" with extra motivational content or a higher "achievement multiplier" before the student completes it. If the student successfully masters that module (the "ball falling" in the first position), they receive a significantly "higher payout" in gamified points, badges, or accelerated progress.

graph TD
    A[Student Learning Progress Sensors] --> B{Hardware Processor 108 (AI Tutor)}
    C[Engagement/Cognitive Load Data] --> B
    B --> D[Curriculum Map (Roulette Wheel)]
    D --> E[Learning Modules/Skills (Positions)]
    B --> F[Student/AI Bet Input]
    F --> B
    B --> G[Dynamic Achievement Multiplier Selection]
    G --> H[Gamified Payout Calculation]
    I[Student Module Mastery] --> H

Derivative 3.3: Genetic Trait Selection in Bio-Agriculture

Enabling Description: The system is applied to optimize genetic trait selection in high-throughput agricultural breeding programs. The "roulette wheel" represents a population of plant or animal genetic crosses, with "positions" being specific genetic markers or desired phenotypic traits (e.g., drought resistance, increased yield, disease immunity). The "ball" represents the outcome of a breeding experiment. "Bet information" is placed by geneticists or automated algorithms on promising genetic combinations or traits. The "hardware processor" (108) controls robotic phenotyping platforms and genomic sequencing equipment. "Spin determination" is the initiation of a new generation of breeding. "Randomly selecting a first selected position" involves the processor, using predictive genomic models, highlighting a specific genetic marker or trait (the "first position" that was bet on) for an "enhanced validation" or "accelerated selection" status before the full experimental results are known. If the actual breeding outcome (the "ball falling") confirms the presence and desired expression of that "first selected position," then an "enhanced payout" in terms of research funding, priority for future crosses, or expedited commercialization is awarded.

graph TD
    A[Genomic Sequencing Data] --> B{Hardware Processor 108 (Predictive Models)}
    C[Robotic Phenotyping Platforms] --> B
    B --> D[Genetic Cross Population (Roulette Wheel)]
    D --> E[Genetic Markers/Traits (Positions)]
    B --> F[Geneticist/Algorithm Bet]
    F --> B
    B --> G[Enhanced Validation/Selection Trigger]
    G --> H[Research Allocation/Commercialization Payout]
    I[Actual Breeding Outcome] --> H

4. Integration with Emerging Tech

Derivative 4.1: AI-Optimized Real-Time Predictive Payouts with IoT Sensor Integration

Enabling Description: The system integrates advanced AI/ML models (e.g., deep learning for vision-based ball tracking, reinforcement learning for payout optimization) on a dedicated GPU cluster with a comprehensive network of IoT sensors. The wheel sensor (104) is replaced by an array of high-speed LIDAR sensors providing sub-millisecond 3D point cloud data of the wheel and ball, transmitting via MQTT to the core application computer (108). The core application computer (108) hosts a predictive AI engine that analyzes ball trajectory, wheel rotation, air density (from environmental IoT sensors), and even subtle dealer micro-movements (from high-res cameras with pose estimation) to predict the ball's final landing position probability distribution with continuously refining confidence intervals. This AI system dynamically adjusts the "first payout" and "second payout" in real-time based on current game state and historical patterns, ensuring game fairness and operator profitability, while still adhering to the "randomly select prior to ball falling" rule for enhanced positions.

graph TD
    A[LIDAR Sensor Array] -- MQTT --> B{Core Application Computer 108 (GPU Cluster)}
    C[Environmental IoT Sensors] -- MQTT --> B
    D[High-res Cameras + Pose Estimation] -- MQTT --> B
    B --> E[Predictive AI Engine (DL/RL)]
    E --> F[Real-time Ball Tracking & Probability Distribution]
    F --> G[Dynamic Payout Adjustment Module]
    G --> H[Player Devices 130, 132, 134]
    H --> B
    B --> I[Game Display 136]

Derivative 4.2: Blockchain-Verified Wagering and Fair Payout Distribution

Enabling Description: The system leverages blockchain technology (e.g., Hyperledger Fabric or a custom EVM-compatible chain) to ensure transparency and immutability of bet information, random number generation, and payout distribution. "First bet information" and "second bet information" are recorded as immutable transactions on the blockchain. The "randomly selected position" (210) is derived from a verifiable random function (VRF) or a decentralized oracle network (e.g., Chainlink) providing a provably fair random seed that is also recorded on the blockchain prior to the ball falling. Smart contracts automatically execute the "payout determination" and "indicating that the first player is to be paid" steps once the "ball has fallen in the first position" is confirmed by an external oracle (e.g., certified human verifier or a tamper-proof sensor data feed) and attested to the blockchain. Player accounts and balances are maintained on the blockchain, enabling instant, trustless payouts.

graph TD
    A[Player Devices 130, 132, 134] --> B(Bet Smart Contract)
    B --> C[Blockchain Network]
    D[Decentralized Oracle Network/VRF] --> E(Random Selection Smart Contract)
    E --> C
    F[Wheel Sensor 104 / Certified Verifier] --> G(Outcome Attestation Oracle)
    G --> H(Payout Smart Contract)
    H --> C
    C --> I[Player Wallets on Blockchain]
    B --> H
    E --> H

5. The "Inverse" or Failure Mode

Derivative 5.1: Safe-Mode Low-Volatility Wagering with Partial Functionality

Enabling Description: In the event of a critical system failure (e.g., primary power loss, network instability, sensor malfunction, or regulatory compliance issue), the system automatically transitions into a "safe-mode" or "low-volatility" state. In this mode, the "roulette wheel" (102) reverts to a purely visual display on game display (136) or player devices (130, 132, 134) (i.e., no physical spin or ball). The "ball fall" and "random selection" are determined by a pre-certified, deterministic pseudo-random number generator (PRNG) with reduced maximum payouts (e.g., a cap of 10:1 instead of 499:1). Bet information reception is limited to simple "red/black" or "odd/even" bets, disabling complex inside bets. All game activity is recorded locally on non-volatile memory (606) for audit purposes and synchronized upon restoration of full functionality. This ensures continuous, albeit limited, operation while preventing excessive losses due to system errors or exploitation of vulnerabilities.

stateDiagram-v2
    state NormalOperation {
        [*] --> GameInProgress
        GameInProgress --> BetReception
        BetReception --> SpinExecution
        SpinExecution --> RandomSelectPayout
        RandomSelectPayout --> BallFallDetect
        BallFallDetect --> PayoutDistribute
        PayoutDistribute --> GameInProgress
    }

    state FailureMode {
        [*] --> LimitedBetting
        LimitedBetting --> DeterministicRandom
        DeterministicRandom --> CappedPayout
        CappedPayout --> LimitedBetting
    }

    NormalOperation --> FailureMode : CriticalSystemFailure
    FailureMode --> NormalOperation : SystemRecovery
    CriticalSystemFailure --> AuditingData
    CappedPayout --> AuditingData

Derivative 5.2: Educational Demo Mode with Augmented Reality Guidance

Enabling Description: The system incorporates an "educational demo mode" designed to operate in a limited-functionality state for training or demonstration purposes without real money wagering. In this mode, the "roulette wheel" and "ball" function physically, but all "bet information" is simulated or provided as guided examples. An Augmented Reality (AR) overlay, projected onto the physical wheel area (via display 136 or player device AR capabilities), visually highlights suggested "first selected positions" and demonstrates potential "higher payouts" with animated graphical explanations. The "hardware processor" (108) orchestrates this AR guidance, providing real-time feedback on "virtual bets" and simulating outcomes. This mode helps new players understand the game mechanics, especially the concept of dynamically enhanced payouts, without financial risk. It can also operate in a low-power state, using reduced video stream quality and disabling certain advanced visual effects (126) to conserve resources.

graph TD
    A[Player Device (AR Enabled)] --> B(Virtual Bet Input)
    B --> C{Hardware Processor 108}
    C --> D[AR Overlay Generator]
    D --> E[Game Display 136 / Physical Wheel]
    E --> F[Simulated Spin & Ball Fall]
    C --> G[AR Payout Guidance]
    G --> A
    C --> H[Local/Simulated Payout Calculation]
    A --> H

Combination Prior Art Scenarios with Open-Source Standards

Here are three scenarios where the core invention of US10629024 is combined with existing open-source standards, thereby establishing prior art for such integrations:

US10629024 + MQTT (Message Queuing Telemetry Transport)
- Description: The system (100) utilizes MQTT, an ISO standard (ISO/IEC PRF 20922) lightweight messaging protocol, for all telemetry data exchange between distributed components and the core application computer (108). Specifically, the wheel sensor (104), cameras (112, 114), and audiovisual control system (122) publish real-time data streams (e.g., wheel rotation speed, ball velocity, image frames, LED matrix status) as MQTT topics. The core application computer (108) subscribes to these topics, enabling low-latency, bandwidth-efficient communication crucial for precise "spin determination," "ball fall determination," and synchronized visual effects. Player devices (130, 132, 134) can also subscribe to game state updates via MQTT, receiving notifications of "bets closed," "randomly selected positions," and "payout indications" almost instantaneously, enhancing responsiveness for internet-based wagering.
```
sequenceDiagram
    participant WS as Wheel Sensor 104
    participant C as Cameras 112, 114
    participant AVCS as AV Control System 122
    participant MQB as MQTT Broker
    participant CAC as Core Application Computer 108
    participant PD as Player Devices

    WS->>MQB: Publish "wheel/speed", "ball/position"
    C->>MQB: Publish "video/stream/main", "video/stream/closeup"
    AVCS->>MQB: Publish "led/status", "audio/effects/active"
    MQB->>CAC: Subscribe "wheel/#", "video/#", "led/#"
    CAC->>PD: Publish "game/state", "payout/indication"
    PD->>MQB: Subscribe "game/#", "payout/#"
    CAC->>MQB: Publish "betting/status/closed"
    CAC->>MQB: Publish "random/position/selected"
```
US10629024 + OpenCV (Open Source Computer Vision Library)
- Description: The hardware processor (108), in conjunction with an image processing unit, utilizes OpenCV, an open-source library for computer vision, to perform sophisticated analysis of video feeds from cameras (112, 114). OpenCV modules are employed for:
  - Ball Tracking: Real-time object detection (e.g., Haar cascades or deep learning models) and Kalman filtering to precisely track the ball's trajectory and velocity, critical for "spin determination" and predicting its landing zone.
  - Wheel Position Recognition: Template matching or feature detection algorithms to accurately identify the numbered pockets on the roulette wheel and determine the final "ball fall position."
  - Visual Effect Synchronization: Analyzing video frames to ensure that "lightning visual effects" (as per Claim 5) and other visual enhancements on game display (136) are perfectly synchronized with actual ball movement and game state transitions.
    This enhances the accuracy and reliability of automated game play and visual feedback.
```
graph TD
    C(Cameras 112, 114) --> I[Image Processing Unit]
    I --> O[OpenCV Library]
    O --> A[Object Detection (Ball)]
    O --> B[Kalman Filtering (Trajectory)]
    O --> C2[Template Matching (Wheel Pockets)]
    O --> D[Feature Detection (Visual Effects Sync)]
    A --> HP{Hardware Processor 108}
    B --> HP
    C2 --> HP
    D --> HP
    HP --> V[Video/Audio Encoder 116]
    HP --> E[Audiovisual Control System 122]
```
US10629024 + WebRTC (Web Real-Time Communication)
- Description: The system employs WebRTC, an open-source project providing real-time communication capabilities to web browsers and mobile applications, to deliver low-latency, high-quality live video and audio streams from the game studio to player devices (130, 132, 134). Instead of a traditional video/audio encoder (116) streaming via RTMP or HLS, WebRTC's peer-to-peer or server-assisted connections minimize buffering and delay, essential for replicating a "real casino environment." The "video area 302" on player devices is powered by a WebRTC client, receiving live feeds of the "roulette wheel," "game presenter," and "visual effects" directly. This allows players to experience the game with minimal lag, ensuring that the "randomly select a first selected position...prior to the ball falling" event and subsequent "payout indications" are seen by players in near real-time, enhancing engagement and trust.
```
sequenceDiagram
    participant Cam as Cameras 112, 114
    participant Mic as Microphone 120
    participant Srv as Core Application Computer 108 (WebRTC Server)
    participant PD1 as Player Device 130
    participant PD2 as Player Device 132

    Cam->>Srv: Live Video Feed
    Mic->>Srv: Live Audio Feed
    Srv->>PD1: WebRTC Offer (Video/Audio Stream)
    PD1->>Srv: WebRTC Answer
    Srv-->>PD1: Establish WebRTC Peer Connection
    Srv->>PD2: WebRTC Offer (Video/Audio Stream)
    PD2->>Srv: WebRTC Answer
    Srv-->>PD2: Establish WebRTC Peer Connection
    loop Real-time game play
        Srv->>PD1: Stream Live Video/Audio
        Srv->>PD2: Stream Live Video/Audio
    end
    PD1->>Srv: Bet Information (via established connection)
    Srv->>PD1: Payout Indication (via established connection)
```