Mobile Noise Source Location via Sound and Image Data Comparison
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Solution Overview
Problem
Existing systems lack an effective method to locate and identify noisy vehicles or aircraft that exceed statutory noise standards, making it difficult to enforce noise pollution regulations.
Innovation Solution
A system comprising a sound sensing device, an image pickup device, a spectrogram database, and an information processing unit that captures and compares sound and image data to identify noise sources, associating current data with default entries if similarity thresholds are met, and updates the database for improved identification and reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sound sensing and image capture devices are deployed to monitor mobile noise sources, then noise source identification capability is improved, but system complexity and cost increase
Solution Approach 1:
The system divides the monitoring task into separate functional modules: sound sensing devices for acoustic detection, image pickup devices for visual identification, and information processing units for data analysis. This segmentation allows each component to be optimized independently while maintaining overall system effectiveness.
Solution Approach 2:
The patent introduces an information processing unit as an intermediary that receives data from both sound sensing and image pickup devices, processes the information, and generates identification results. This intermediary component coordinates the multiple sensors and reduces the complexity burden on individual devices.
2Measurement precision
If multiple sensing devices are used to capture both sound and image data, then identification accuracy is improved, but loss of information increases due to data integration challenges
Solution Approach 1:
The patent merges sound characteristic information from sound sensing devices with image data from pickup devices within the information processing unit. By combining these different data types, the system achieves more accurate identification of mobile noise sources than would be possible with either sensor type alone.
Solution Approach 2:
The system incorporates feedback mechanisms where the information processing unit analyzes incoming data, compares it against stored profiles, and uses the results to refine ongoing monitoring. This feedback loop ensures that information from multiple sources is integrated effectively rather than lost.
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
Enables accurate location and identification of noisy vehicles or aircraft, facilitating enforcement of noise regulations through automated data comparison and reporting, with the potential for continuous database improvement for enhanced accuracy.
Implementation Method 1
a sound sensing device, which catches a sound wave of the mobile noise source passing a specified area within a specified time period
Implementation Method 2
an image pickup device, which catches an image of the mobile noise source
Data Source
AI summary
In a system and a method for locating a mobile noise source, a sound sensing device catches a sound wave of the mobile noise source, and generates and stores a current sound characteristic information corresponding to the sound wave. An image pickup device catches an image of the mobile noise source, and generates and stores an entry of current image data corresponding to the mobile noise source. A spectrogram and image database stores entries of default spectrogram data and entries of default image data. An information processing unit compares the current sound characteristic information with the entries of default spectrogram data, and stores and associates the current sound characteristic information with the mobile noise source in the spectrogram and image database if no similarity between the current sound characteristic information and the entries of default spectrogram data reaches a preset value.