Audio Event Presence Detection With Buffered Sound Classification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems for detecting user presence often suffer from high rates of false positives and false negatives, particularly in environments where users may be still or minimally active, leading to inefficient resource usage and inaccurate triggering of responsive actions.
Innovation Solution
A system that uses acoustic signals to differentiate between user-generated and non-user-generated sounds by employing a transducer, capture channel, processor, event classifier, and status generator to generate a user presence indicator, which aggregates detection events over a buffer period and applies weights to reduce false positives and negatives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system uses audio events to detect user presence, then the detection accuracy is improved, but the false positive rate increases due to non-user audio events
Solution Approach 1:
The system dynamically adjusts the detection threshold based on the aggregate count of audio events within a buffer period. By evaluating the rate of detected events over time rather than using a fixed threshold, the system adapts to varying environmental conditions and user activity patterns, thereby reducing false positives while maintaining detection accuracy
Solution Approach 2:
The system incorporates feedback mechanisms by continuously monitoring the aggregate count of detection events and adjusting the presence determination accordingly. The buffer period accumulates event counts and feeds this information back to the status generator, enabling the system to learn from past detections and improve its accuracy over time while filtering out non-user events
2Reliability
If the system monitors audio events continuously to improve detection accuracy, then the detection reliability is improved, but the energy consumption increases
Solution Approach 1:
The system uses periodic action by processing audio events in discrete buffer periods rather than continuous monitoring. The event buffer accumulates events over a defined period, and the status generator evaluates the aggregate count at the end of each buffer period. This periodic processing reduces computational load and energy consumption while maintaining detection accuracy through the accumulated event data
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 effectively reduces false positives and negatives by accurately identifying user presence through weighted aggregation of sound events, ensuring efficient resource management and timely activation/deactivation of responsive functions.
Implementation Method 1
at least one transducer configured to capture sound signals generated within the monitored environment
Data Source
AI summary
A system and method are provided for detecting the presence of animate users, such as people, within a monitored environment, based on audio events. A transducer captures sound signals generated within the monitored environment, which a capture channel converts to form a digital stream. A feature extractor detects predetermined signal features of the digital stream over predetermined extraction periods, and an event classifier uses values of these features to generate a series of detection events reflective of likely sources of sounds in the captured sound signals. Then, an event buffer maintains an aggregate count of detection events generated by the event classifier, and a status generator generates the user presence indicator according to the aggregate count of detection events. A response system triggers one of more functions responsive to one or user presence indicators, thereby responding to the presence or absence of the animate users.