Patent 10890925B2

Derivative works

Defensive disclosure: derivative variations of each claim designed to render future incremental improvements obvious or non-novel.

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Derivative works

Defensive disclosure: derivative variations of each claim designed to render future incremental improvements obvious or non-novel.

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Defensive Disclosure: Derivatives of US Patent 10890925B2 for Prior Art Generation

This document outlines derivative variations of US Patent 10890925B2, focusing on rendering future incremental improvements by competitors obvious or non-novel. The analysis is based on the core independent claims of the patent, specifically Claim 1 (System) and Claim 11 (Method).

Introduction

The objective of this defensive disclosure is to preemptively address potential future patent claims related to vehicle leveling systems, particularly those leveraging smart devices. By publicly disclosing various technical alternatives, operational expansions, cross-domain applications, integrations with emerging technologies, and failure modes, we aim to establish a broad base of prior art that makes incremental advancements in this field obvious to a person having ordinary skill in the art (POSITA). This strategy focuses on expanding the scope of what is considered "known" in the art, thereby limiting the patentability of future similar inventions.

Derivative Variations for Claim 1 (System)

Claim 1: A leveling system for a vehicle comprising: one or more sensor devices secured to the vehicle to sense at least one of an inclination or an orientation of the vehicle in both a pitch direction and a roll direction; and a smart device in communication with the one or more sensor devices, the smart device comprising: a display screen; a wireless communication module configured to communicate with the one or more sensor devices; and a processor configured to execute a software application, the software application configured to: receive from the one or more sensor devices a pitch angle measurement and a roll angle measurement of the vehicle when the vehicle is at rest; retrieve calibration data of pitch and roll angle measurements taken by the one or more sensor devices when the vehicle was at an initial level position; calculate any needed change in at least one of a pitch direction or a roll direction of the vehicle using the received pitch angle measurement and the received roll angle measurement of the at rest vehicle and the calibration data of the pitch and roll angle measurements to obtain a level position of the vehicle; and display on the display screen of the smart device the calculated change in at least one of the pitch direction or the roll direction of the vehicle needed to obtain the level position of the vehicle.

1. Material & Component Substitution

Derivative 1.1: Piezoelectric Strain Gauge Array for Inclination Sensing

  • Enabling Description: The one or more sensor devices are replaced with a distributed array of micro-electromechanical systems (MEMS) piezoelectric strain gauges affixed to critical structural points of the vehicle chassis. These gauges continuously measure localized strain, which is then correlated to global pitch and roll inclination through a pre-calibrated finite element analysis (FEA) model. The output signals from the strain gauges are fed into an analog-to-digital converter (ADC) on a local microcontroller (e.g., ESP32-S3), which then transmits the digitized strain data wirelessly via Bluetooth Low Energy (BLE 5.2) to the smart device. The smart device's application uses the FEA model to infer pitch and roll angles from the strain data and computes required adjustments. This approach eliminates traditional accelerometers and gyroscopes, offering resilience to vibration and shock.
graph TD
    A[Vehicle Chassis] --> B(Piezoelectric Strain Gauge Array)
    B --> C{ADC & Microcontroller (ESP32-S3)}
    C -- BLE 5.2 --> D[Smart Device]
    D --> E(Software Application)
    E --> F{FEA Model for Pitch/Roll Inference}
    E --> G(Calculation Engine)
    E --> H[Display Screen (Adjustments)]

Derivative 1.2: Liquid Metal Tilt Sensors with Inductive Readout

  • Enabling Description: The inclination sensing is performed by a series of encapsulated liquid metal (e.g., Galinstan) tilt sensors. Each sensor consists of a small reservoir of liquid metal and multiple inductive coils arranged around it. As the vehicle inclines, the liquid metal shifts, changing the mutual inductance between the coils. This change is precisely measured by a high-frequency alternating current (AC) excitation circuit and an impedance analyzer integrated into a custom ASIC within the sensor device. The ASIC converts the impedance changes into pitch and roll data, which is then transmitted via a secure Zigbee mesh network to a gateway, then relayed to the smart device via Wi-Fi. This provides a robust, contact-less, and potentially more stable measurement in certain environments.
graph TD
    A[Vehicle] --> B(Liquid Metal Tilt Sensor Array)
    B --> C{Inductive Readout Circuit & ASIC}
    C -- Zigbee --> D[Zigbee Gateway]
    D -- Wi-Fi --> E[Smart Device]
    E --> F(Software Application)
    F --> G(Pitch/Roll Calculation)
    F --> H[Display Screen]

Derivative 1.3: Fiber Optic Gyroscopes (FOGs) for High-Precision Angular Rate Sensing

  • Enabling Description: For ultra-high precision leveling applications, the sensor device integrates miniature Fiber Optic Gyroscopes (FOGs) to measure angular rates for pitch and roll. These FOGs operate on the Sagnac effect, detecting phase shifts in light propagating through coiled optical fibers. The output of the FOGs is processed by a dedicated digital signal processor (DSP) to integrate angular rates into precise angle measurements, correcting for drift using an onboard Kalman filter combined with occasional static accelerometer readings. The corrected pitch and roll data are then encrypted (AES-256) and transmitted via a proprietary 433 MHz radio frequency (RF) protocol to the smart device.
graph TD
    A[Vehicle] --> B(Miniature FOG Array)
    B --> C{DSP & Kalman Filter}
    C --> D(Pitch/Roll Angle Calculation)
    D -- 433 MHz RF (AES-256) --> E[Smart Device]
    E --> F(Software Application)
    F --> G[Display Screen]

2. Operational Parameter Expansion

Derivative 2.1: Micro-Scale Autonomous Levelling System for Laboratory Platforms

  • Enabling Description: The leveling system is miniaturized for micro-scale applications, such as ensuring precise horizontal alignment of optical benches, atomic force microscopes, or microfluidic platforms in a laboratory environment. The sensor device is a sub-centimeter MEMS inertial measurement unit (IMU) with picometer resolution accelerometers and gyroscopes, integrated onto the platform. The "vehicle" dimensions for calculation are in millimeters. The "smart device" is a dedicated tablet or workstation, communicating via a high-speed, low-latency Wi-Fi 6 link. The system actively interfaces with piezoelectric micro-actuators or voice coil motors beneath the platform to achieve dynamic, closed-loop leveling to within ±0.0001 degrees, responding to even minute environmental vibrations.
graph TD
    A[Microfluidic Platform] --> B(MEMS IMU Sensor)
    B -- Wi-Fi 6 --> C[Workstation/Tablet]
    C --> D(Software Application)
    D --> E{Real-time Calculation & PID Control}
    E --> F(Piezoelectric Micro-actuators)
    F --> A
    C --> G[Display Screen (μm adjustments)]

Derivative 2.2: Industrial-Scale Dynamic Levelling for Heavy Construction Equipment

  • Enabling Description: The leveling system is scaled for heavy construction equipment, such as large excavators, cranes, or drilling rigs, operating on uneven terrain. The sensor device consists of ruggedized, high-g accelerometers and inclinometers (e.g., using capacitive or electrolytic principles) integrated directly into the hydraulic stabilization outriggers and main chassis. The smart device is a hardened industrial tablet or a proprietary in-cab display unit, communicating over a robust industrial Ethernet (e.g., EtherCAT) or a private 5G network for reliable, real-time data transfer. The system calculates and displays multi-point leveling requirements (e.g., for each outrigger) and can integrate with the vehicle's hydraulic control unit (HCU) for semi-automatic or fully automatic dynamic leveling during operation or deployment, with a tolerance of ±0.1 degrees across vehicle lengths exceeding 20 meters.
graph TD
    A[Heavy Equipment Chassis] --> B(Ruggedized Inclinometers/Accelerometers)
    B --> C{Industrial Controller (PLC)}
    C -- Industrial Ethernet/Private 5G --> D[Hardened Tablet/In-Cab Display]
    D --> E(Software Application)
    E --> F{Multi-point Leveling Algorithm}
    F --> G(Hydraulic Control Unit)
    G --> H[Hydraulic Outriggers]
    H --> A

Derivative 2.3: Cryogenic Levelling for Superconducting Magnet Systems

  • Enabling Description: The leveling system operates in extreme cryogenic environments, specifically for aligning large superconducting magnet systems (e.g., for MRI or particle accelerators) housed in liquid helium dewars. The sensor device utilizes specialized cryogenic-compatible optical inclinometers (e.g., based on optical beam deflection) or capacitive sensors with ultralow thermal expansion coefficients, mounted on the magnet support structure. These sensors operate down to 4 Kelvin. The "smart device" is a remotely located control computer that processes the sensor data, communicated via cryo-compatible fiber optic cables to avoid thermal load and electrical interference. The system calculates and displays minute angular deviations (e.g., in microradians) and suggests adjustments to motorized cryogenic jacks or active vibration isolation platforms.
graph TD
    A[Superconducting Magnet System] --> B(Cryogenic Optical/Capacitive Inclinometer)
    B -- Fiber Optic Link --> C[Cryogenic Signal Conditioner]
    C --> D[Remote Control Computer]
    D --> E(Software Application)
    E --> F{Cryogenic Leveling Algorithm}
    F --> G(Motorized Cryogenic Jacks)
    G --> A
    D --> H[Display Screen (µrad adjustments)]

3. Cross-Domain Application

Derivative 3.1: Subsea Habitat Levelling for Oceanographic Research

  • Enabling Description: The leveling system is adapted for maintaining the horizontal orientation of a subsea research habitat or remotely operated vehicle (ROV) on an uneven ocean floor. The sensor device comprises pressure-compensated, corrosion-resistant inclinometers (ee.g., MEMS accelerometers in a sealed, oil-filled housing) and depth sensors, integrated into the habitat's hull. Communication with the "smart device" (a topside control console on a research vessel) is achieved via an acoustic modem (e.g., using WHOI acoustic protocols) or a tethered fiber-optic cable for data transmission and command signals. The software application calculates pitch and roll deviations and provides instructions for adjusting variable buoyancy tanks or deployable hydraulic legs to stabilize the subsea structure.
graph TD
    A[Subsea Habitat/ROV] --> B(Pressure-Compensated Inclinometer/Depth Sensor)
    B --> C{Subsea Control Module}
    C -- Acoustic Modem/Fiber Optic Tether --> D[Topside Control Console]
    D --> E(Software Application)
    E --> F{Buoyancy/Leg Adjustment Algorithm}
    F --> G(Variable Buoyancy Tanks/Hydraulic Legs)
    G --> A
    D --> H[Display Screen (Underwater Level Status)]

Derivative 3.2: Precision Agricultural Equipment Levelling for Sloped Terrain

  • Enabling Description: This system is for precision agriculture, specifically for leveling implements like seed planters, sprayers, or harvesters operating on sloped or terraced fields. The sensor device integrates robust, weather-sealed inclinometers and GPS-RTK (Real-Time Kinematic) sensors, mounted on the implement frame. The smart device is a ruggedized tablet or the tractor's existing ISO-BUS terminal. Communication uses a CAN bus (for implement control) and Wi-Fi Direct for the smart device. The software application uses high-precision GPS elevation data in conjunction with the inclinometer readings to determine ground slope and implement tilt. It calculates adjustments for active hydraulic cylinder linkages on the implement to maintain a constant working angle relative to gravity, optimizing seed depth, spray coverage, or harvest efficiency.
graph TD
    A[Agricultural Implement] --> B(Rugged Inclinometer + GPS-RTK)
    B --> C{Implement ECU (CAN bus)}
    C -- Wi-Fi Direct --> D[Tractor ISO-BUS Terminal/Rugged Tablet]
    D --> E(Software Application)
    E --> F{Slope Compensation Algorithm}
    F --> G(Active Hydraulic Linkages)
    G --> A
    D --> H[Display (Implement Angle/Ground Slope)]

Derivative 3.3: Spacecraft Docking Alignment System

  • Enabling Description: The leveling system is repurposed for fine angular alignment during spacecraft docking procedures. The "vehicle" is a target spacecraft, and the "smart device" is part of the active spacecraft's flight computer and display. The sensor device on the target spacecraft uses non-contact optical alignment sensors (e.g., laser ranging, star trackers, or photogrammetry) to determine its attitude relative to the active spacecraft. Wireless communication uses a secure S-band or X-band radio link. The flight computer's software application processes the alignment data, retrieves pre-stored nominal docking attitudes (calibration data), and calculates precise pitch, roll, and yaw correctional thruster firings required for safe docking, displayed on the astronaut's control panel.
graph TD
    A[Target Spacecraft] --> B(Optical Alignment Sensors)
    B --> C{Target Spacecraft Avionics}
    C -- S/X-Band Radio Link --> D[Active Spacecraft Flight Computer]
    D --> E(Docking Alignment Software)
    E --> F{Attitude Calculation & Thruster Control}
    F --> G(Reaction Control System Thrusters)
    G --> A
    D --> H[Astronaut Display (Docking Guidance)]

4. Integration with Emerging Tech

Derivative 4.1: AI-Driven Predictive Levelling with IoT Sensor Network

  • Enabling Description: The system integrates an array of IoT-enabled sensor devices (accelerometers, gyroscopes, temperature, humidity, ground pressure sensors) distributed across the vehicle chassis and its immediate environment. These sensors continuously stream data via a long-range wireless protocol (e.g., LoRaWAN) to a cloud-based AI engine. The AI engine, using machine learning models trained on historical leveling data, terrain topology, and weather forecasts, not only calculates immediate leveling adjustments but also predicts future leveling requirements based on anticipated ground settlement, payload shifts, or environmental changes (e.g., soil saturation). The smart device (user's smartphone or an integrated vehicle display) receives these AI-optimized predictive adjustment recommendations, potentially even before the vehicle comes to a complete rest, for more efficient leveling. Blockchain is used to verify the integrity and origin of sensor data for auditing and insurance purposes.
graph TD
    A[Vehicle] --> B(IoT Sensor Array - Accel, Gyro, Temp, Humidity, Pressure)
    B -- LoRaWAN --> C[LoRaWAN Gateway]
    C --> D[Cloud-based AI Engine]
    D --> E{ML Models: Prediction, Optimization}
    D -- Blockchain (Data Integrity) --> F[Smart Device]
    F --> G(Software Application)
    G --> H[Display (AI-Optimized Predictive Adjustments)]

Derivative 4.2: Real-time Leveling using Edge AI and LiDAR-based Terrain Mapping

  • Enabling Description: The sensor device integrates a solid-state LiDAR scanner with an edge AI processor (e.g., NVIDIA Jetson Nano) to perform real-time 3D terrain mapping around the vehicle. Concurrently, a high-resolution IMU provides precise vehicle attitude data. The edge AI processor analyzes the LiDAR point cloud to identify optimal leveling points and detect potential obstacles or unstable ground. It combines this terrain analysis with IMU data to calculate instantaneous multi-point leveling adjustments that are displayed on the smart device (e.g., augmented reality overlay on the vehicle's surroundings shown on the smart device's camera feed). This system allows for proactive, real-time leveling guidance before or during minor repositioning, minimizing manual trial-and-error. Calibration data includes a virtual "perfect ground plane" derived from initial setup.
graph TD
    A[Vehicle] --> B(Solid-State LiDAR)
    A --> C(High-Res IMU)
    B & C --> D[Edge AI Processor (NVIDIA Jetson Nano)]
    D --> E{Real-time Terrain Mapping & Leveling Optimization}
    D -- Wi-Fi Direct (Low Latency) --> F[Smart Device (AR Display)]
    F --> G(Software Application)
    G --> H[Display (Proactive Leveling Guidance)]

5. The "Inverse" or Failure Mode

Derivative 5.1: Low-Power "Guardian" Mode for Long-Term Storage

  • Enabling Description: The leveling system includes a "Guardian Mode" for extended vehicle storage. In this mode, the sensor device (e.g., a low-power MEMS accelerometer with integrated microcontroller) transitions to a deeply sleep-cycled state, waking only once every 24-48 hours. During its brief awake cycle, it takes a single, low-resolution pitch and roll measurement, compares it against a pre-set "storage level" threshold (e.g., ±2 degrees from perfectly level), and logs the data locally. If the deviation exceeds the threshold, it triggers a low-power, single-packet data transmission via a narrow-band IoT (NB-IoT) cellular module to the smart device (or associated cloud service) as an alert. No continuous display or complex calculations are performed, conserving battery life for months or years.
stateDiagram-V2
    [*] --> DeepSleep
    DeepSleep --> CheckInterval: Timer (24-48h)
    CheckInterval --> Awake: Wake
    Awake --> MeasureLevel: Low-Res Measurement
    MeasureLevel --> CompareThreshold: Compare to Storage Level
    CompareThreshold --> Alert: if > Threshold
    Alert --> SendNB_IoT: Send Alert (NB-IoT)
    SendNB_IoT --> DeepSleep: Return to Sleep
    CompareThreshold --> DeepSleep: if <= Threshold

Derivative 5.2: Safe-Fail Emergency Leveling for Damaged Vehicles

  • Enabling Description: In the event of a vehicle-damaging incident (e.g., tire blowout, suspension failure), the leveling system enters a "Safe-Fail Emergency Leveling" mode. This mode prioritizes stability over perfect level. The sensor device, which includes redundant accelerometers and gyroscopes, continuously monitors for rapid, uncontrolled changes in pitch and roll or excessive vibration indicative of damage. Upon detection, the smart device application immediately overrides normal leveling algorithms. Instead, it calculates the minimum adjustments required to stabilize the vehicle at its current highest load-bearing points, preventing further collapse or tip-over, rather than achieving a perfectly level state. The display provides urgent, simplified instructions for manual intervention or directs an automated system to deploy emergency stabilizing jacks to pre-defined, mechanically secure positions. The system avoids attempting to achieve a precise "level" which could exacerbate instability on a compromised structure.
graph TD
    A[Vehicle] --> B(Redundant Accel/Gyro)
    B --> C{Damage Detection Module}
    C -- Detect Damage --> D[Smart Device]
    D --> E(Software Application)
    E --> F{Emergency Leveling Algorithm}
    F --> G(Minimum Stability Calculation)
    G --> H[Display (Urgent Stabilization Instructions)]
    G --> I(Emergency Stabilizing Jacks)

Derivative 5.3: Limited-Functionality "Manual Override" Mode

  • Enabling Description: Should the wireless communication link between the sensor device and the smart device fail, or if the smart device's battery is depleted, the sensor device itself enters a "Manual Override" mode. The sensor device, equipped with a simple onboard microcontroller and a small, segmented LED display or a series of indicator lights, continues to calculate approximate pitch and roll deviations. Instead of transmitting data, it uses a pre-programmed visual code (e.g., specific LED patterns or numeric codes on the segmented display) to indicate general direction and magnitude of tilt (e.g., "Left High," "Front Low," "Adjust +2 units"). This provides basic, standalone leveling guidance without the need for the smart device, enabling essential functionality even in degraded conditions.
graph TD
    A[Sensor Device] --> B(Onboard Microcontroller)
    B --> C(Pitch/Roll Calculation)
    C -- No Smart Device Link --> D[Limited-Functionality Mode]
    D --> E(Pre-programmed Visual Code Output)
    E --> F[Segmented LED Display/Indicator Lights]
    F --> G[User (Manual Adjustment)]

Combination Prior Art Scenarios

These scenarios combine the teachings of US10890925B2 with existing open-source standards to further expand the prior art landscape.

  1. US10890925B2 + ROS (Robot Operating System) for Autonomous Vehicle Levelling:

    • Description: The core sensing and calculation methodology of US10890925B2 is integrated into an autonomous ground vehicle (e.g., a robotic platform for surveying or logistics) running a Robot Operating System (ROS) framework. The sensor device (IMU, inclinometers) publishes pitch and roll data as ROS topics. The smart device functionality (processing, display, adjustment calculation) is implemented as a ROS node. This node subscribes to the sensor data, computes desired leveling actions, and publishes command messages to actuator nodes (e.g., controlling a robotic leg or active suspension system). The ROS standard provides a robust, modular, and open-source software architecture for developing and deploying robotic applications, making the integration of leveling capabilities an obvious extension for autonomous vehicles requiring stable platforms. This combination would demonstrate an obvious integration of patent claims with a widely adopted open-source robotics framework.
    • Prior Art Value: Establishes the use of the core leveling system within a standardized, open-source robotics control architecture for autonomous vehicle leveling.
    graph TD
    A[Sensor Device (IMU/Inclinometers)] --> B(ROS Node: Sensor Publisher)
    B -- /vehicle_pose Topic --> C[ROS Master]
    C -- /vehicle_pose Topic --> D(ROS Node: Leveling Calculator)
    D -- /leveling_commands Topic --> E(ROS Node: Actuator Controller)
    E --> F[Vehicle Actuators (Robotic Legs/Suspension)]
    D --> G[Smart Device (ROS GUI/RVIZ Display)]

  2. US10890925B2 + OpenStreetMap (OSM) for Location-Aware Levelling Profiles:

    • Description: The leveling system of US10890925B2 is enhanced by integrating with OpenStreetMap (OSM) data. The smart device's software application utilizes the vehicle's GPS location to query OSM for terrain elevation data, parking lot gradients, or specific user-contributed "leveling profiles" associated with known camping spots or industrial sites. This allows the system to proactively retrieve or suggest optimal initial leveling strategies based on geospatial information, rather than purely reactive measurements. For instance, if OSM indicates a known slope at a particular campground spot, the system could pre-calculate and display approximate block heights needed for the uphill side before the vehicle even pulls in fully. The OSM data is an open-source, crowd-sourced geographic database.
    • Prior Art Value: Demonstrates the obviousness of integrating real-time leveling guidance with publicly available, open-source geospatial data for predictive or enhanced leveling.
    graph TD
    A[Vehicle Location (GPS)] --> B(Smart Device)
    B --> C(Software Application)
    C -- Query Location --> D[OpenStreetMap API]
    D -- Terrain/Gradient Data --> C
    C --> E{Leveling Strategy Calculation}
    E --> F[Display (Location-Aware Leveling Guidance)]
    F --> G[Sensor Device (Verification)]

  3. US10890925B2 + Matter (Open Standard for IoT) for Smart Home Integration:

    • Description: The vehicle leveling system, when parked (e.g., an RV at home or in a smart campground), integrates its sensor device and smart device functionality into a broader Matter-compliant smart home ecosystem. The sensor device's pitch and roll data are exposed as Matter "attributes" through a Matter bridge or directly if the sensor device is Matter-enabled. This allows other smart home devices (e.g., smart lighting, thermostats, automated shades) to react to the RV's level status. For example, if the RV is significantly unlevel, smart lights inside could subtly adjust color to indicate the direction of tilt, or smart blinds could automatically adjust to compensate for perceived unevenness. The "smart device" acts as a Matter controller.
    • Prior Art Value: Shows the straightforward integration of vehicle leveling status into common, open-source IoT home automation standards, making the sharing and reactive use of leveling data in a broader context obvious.
    graph TD
    A[Sensor Device (Pitch/Roll)] --> B(Matter-enabled Gateway/Bridge)
    B -- Matter Protocol --> C[Matter Controller (Smart Device)]
    C --> D[Smart Home Hub]
    D --> E(Smart Lights/Thermostat/Blinds)
    C --> F(Software Application Display)

Generated 6/19/2026, 6:04:22 PM