Awareness Detection System for Unknown Sound Alerts
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Solution Overview
Problem
Users face challenges in receiving personalized alerts on their devices regarding potential dangers in their vicinity, such as unknown voices or unusual sounds, without a comprehensive system to differentiate between known and unknown sounds.
Innovation Solution
The 'Surrounding Awareness' application on user devices captures and analyzes sound data, comparing it to stored voice samples and a library of known sounds, and alerts the user only if an unknown voice is detected, providing visual, audible, or physical alerts based on predefined criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system alerts users for all detected sounds, then users are notified of all potential dangers, but users receive unnecessary alerts for known sounds
Solution Approach 1:
The patent segments sound detection into two distinct categories: known sounds and unknown sounds. The system separates alert generation for these two categories, applying different logic to each. Known sounds (such as those from familiar locations or previously identified sources) do not trigger alerts, while unknown sounds (potentially dangerous or unrecognized) do trigger alerts. This segmentation resolves the contradiction by ensuring alerts are only generated when necessary, improving reliability while eliminating unnecessary notifications.
2Reliability
If the system monitors all sounds continuously, then user safety is enhanced, but device energy consumption increases
Solution Approach 1:
The system implements periodic monitoring rather than continuous monitoring. It uses scheduled intervals to check for unknown sounds and updates alert status periodically. The monitoring intensity and frequency are adjusted based on contextual factors such as user location, time of day, and historical data. This periodic approach maintains user safety by detecting potential dangers while significantly reducing device energy consumption compared to continuous monitoring.
3Measurement precision
If the system stores extensive sound libraries for comparison, then sound identification accuracy improves, but device memory requirements increase
Solution Approach 1:
The system extracts and stores only the essential characteristics of known sounds rather than storing complete sound libraries. It identifies and retains key acoustic features such as frequency patterns, temporal characteristics, and spectral signatures that are sufficient for accurate sound identification. This extraction approach maintains high sound identification accuracy while dramatically reducing the quantity of stored sound data, resolving the contradiction between precision and storage requirements.
Data Source
AI summary
A method may include receiving sensor data, the sensor data including at least one of sound or light; comparing, when the sensor data includes sound, the received sound with sound information included in one or more media files; comparing, when the sensor data includes light, the received light with one or more particular conditions; determining, based on comparing at least one of the received sound or the received light, if alert information should be provided, the alert information indicating a dangerous situation; and providing, when the alert information should be provided, the alert information indicating the dangerous situation.