Acoustic Window Status Detection Without Wiring Harness Changes
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Solution Overview
Problem
Existing vehicle window control systems are inefficient and costly to implement, as they require significant changes to mechanical and electrical components, making it difficult to effectively detect the status of vehicle windows and maintain interior environment integrity in the Internet of Vehicles (IoV) and location-based services (LBS) contexts.
Innovation Solution
A method that collects scene audio data, extracts vehicle interior background noise, and determines window status based on noise intensity thresholds, allowing for the prediction of window openness without altering the vehicle's wiring harness, using cloud computing or in-vehicle electronic devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional window status detection systems are implemented, then window status can be detected, but significant changes to mechanical and electrical components are required, increasing system complexity and cost
Solution Approach 1:
The patent replaces traditional mechanical and electrical window status detection systems with an acoustic detection system. Audio sensors capture sound waves inside the vehicle cabin, and signal processing algorithms analyze these acoustic signals to determine window status. This substitutes complex mechanical/electrical wiring with acoustic field-based detection, reducing wiring harness complexity while maintaining detection accuracy.
Solution Approach 2:
The patent introduces acoustic signals as an intermediary medium to detect window status. Instead of direct electrical contact or mechanical switches, the system uses sound wave propagation characteristics (reflected, absorbed, or transmitted sounds) as intermediaries to indirectly sense window position, thereby avoiding direct integration with vehicle electrical systems.
2Device complexity
If acoustic-based window detection is used, then wiring harness changes are avoided, but detection accuracy may be affected by background noise and environmental factors
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors acoustic signals and adjusts its analysis based on detected patterns. By comparing acoustic signatures against known window states and using adaptive signal processing, the system learns to distinguish true window status changes from noise, improving precision over time while maintaining the simplicity of the acoustic sensing approach.
Solution Approach 2:
The patent analyzes multiple acoustic parameters (frequency, amplitude, timing, spectral characteristics) rather than relying on a single metric. By changing and comparing multiple acoustic parameters simultaneously, the system can distinguish genuine window status changes from background noise, maintaining high detection accuracy without requiring complex hardware modifications.
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
This approach provides a lightweight and cost-effective solution for detecting vehicle window status, enabling accurate prediction of connectivity between interior and exterior environments, thus improving service provision such as alerting drivers to close windows in polluted conditions.
Implementation Method 1
An audio sensor may be used to collect acoustic waves (i.e., sound)
Data Source
AI summary
A method, system, and computer program product, include obtaining window status decision information based on vehicle interior background noise and determining switch status of the vehicle window(s) based on the obtained window status decision information.