Audio Behavior Detection With Local Filtering for Low Bandwidth
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Solution Overview
Problem
Current monitoring systems in public spaces consume excessive bandwidth and resources due to the transmission of all image and audio data for review, without discrimination between relevant and irrelevant data.
Innovation Solution
A system with a microphone and computing device that identifies behavior patterns in audio input locally, using machine learning techniques, and reports significant patterns to a remote server, reducing unnecessary data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all image and audio data are transmitted for review, then complete data availability is ensured, but bandwidth consumption and resource usage increase significantly
Solution Approach 1:
The system performs preliminary analysis of audio data at the source device before transmission. The audio stream is processed locally to identify and segment relevant portions, which are then transmitted to the remote server for further review. This preliminary action filters out irrelevant data beforehand, reducing overall bandwidth consumption while maintaining data completeness for important events.
Solution Approach 2:
The audio data is segmented into relevant and irrelevant portions through local analysis. Only the relevant segments (such as conversations containing prohibited words or suspicious behaviors) are transmitted for remote review, while irrelevant segments are discarded locally. This segmentation approach significantly reduces the volume of data transmitted over the network.
2Reliability
If all audio data is transmitted for analysis, then comprehensive behavior detection is achieved, but network bandwidth and computing resources are wasted on unnecessary data
Solution Approach 1:
Local preliminary analysis is performed at the source device to pre-filter audio data before transmission. The system identifies and segments relevant portions (such as conversations with prohibited words or suspicious behaviors) and transmits only these segments to the remote server. This preliminary action maintains detection accuracy by ensuring relevant data is not lost, while improving processing efficiency by reducing the total volume of data that requires remote analysis.
3Loss of energy
If audio data is processed locally, then bandwidth consumption is reduced, but computational resources must be available at the source device
Solution Approach 1:
The system extracts and transmits only the relevant portions of audio data to the remote server after local processing. By taking out and transmitting only the necessary segments (such as conversations containing prohibited words) rather than the entire audio stream, the system reduces bandwidth consumption while the local device handles only the computational tasks required for initial filtering and segmentation.
Data Source
AI summary
A system includes a microphone and a computing device including a processor and a memory. The memory stores instructions executable by the processor to identify a word sequence in audio input received from the microphone, to determine a behavior pattern from the word sequence, and to report the behavior pattern to a remote server at a specified time.