Wheel Assembly Sensor Tampering Detection
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Solution Overview
Problem
Current vehicle systems are inadequate in detecting wheel assembly tampering, often resulting in false positives and insufficient protection against theft, as they rely on single sensors like inclination sensors and tire pressure monitoring systems.
Innovation Solution
A system utilizing multiple sensors, including multi-axis accelerometers, pressure sensors, and signal strength receivers, to collect and analyze acceleration, pressure, and inclination data to produce a reliable output indicative of wheel assembly tampering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional single sensors (inclination sensors or tire pressure monitoring) are used to detect wheel assembly tampering, then the system complexity is low, but the detection reliability is insufficient and produces false positives
Solution Approach 1:
The patent combines multiple sensor types (accelerometer, pressure sensor, inclination sensor, and signal strength receiver) into an integrated wheel assembly sensor system. This merging of sensors allows the system to detect tampering through multiple independent measurements, significantly improving detection reliability while reducing false positives compared to traditional single-sensor systems.
Solution Approach 2:
The wheel assembly sensor system performs multiple functions simultaneously: detecting acceleration patterns, monitoring pressure changes, measuring inclination angles, and tracking signal strength. This multi-functionality enables comprehensive tamper detection across different tampering scenarios, enhancing reliability without requiring separate specialized systems for each detection type.
2Measurement precision
If multiple sensor types are integrated to improve tampering detection accuracy, then false positives are reduced, but the device complexity increases
Solution Approach 1:
The patent integrates multiple sensor types (accelerometer, pressure sensor, inclination sensor, and signal strength receiver) into a unified wheel assembly sensor system. This merging approach improves measurement precision by cross-validating data from multiple sensors, while the integrated architecture manages complexity through shared processing and unified data interpretation.
Solution Approach 2:
The system continuously monitors data from multiple sensors and uses feedback mechanisms to adjust detection thresholds and interpret sensor readings in context. This feedback approach allows the system to distinguish between normal variations (reducing false positives) and actual tampering events, improving measurement precision while managing the complexity of multiple sensors through intelligent data processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides real-time, accurate detection of wheel assembly tampering, reducing false positives and enhancing protection against theft by integrating data from various sensors.
Implementation Method 1
In one embodiment, the wheel assembly sensor includes a multi-axis accelerometer configured to produce acceleration data
Implementation Method 2
the sensor also includes a pressure sensor configured to produce pressure data
Implementation Method 3
the sensor also includes an inclination sensor configured to produce inclination data
Implementation Method 4
the sensor also includes a transmitter configured to transmit a signal to a receiver
Data Source
AI summary
A vehicle includes two or more wheel assemblies, each having a wheel assembly sensor. Each of the wheel assembly sensors is configured to produce acceleration data and pressure data associated with its associated wheel assembly. A wheel assembly tampering module communicatively coupled to the plurality of wheel assembly sensors is configured to produce an output indicative of wheel assembly tampering based on at the acceleration data and the pressure data. Inclination data and signal strength data (associated with each of the wheel assembly sensors) may also be used to determine wheel assembly tampering.