Adaptive Audio Alarm Detection System Using Template Learning
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Solution Overview
Problem
Existing audible alarm systems rely on the assumption that a person is present to hear the alarms, which can be limiting for hearing-impaired individuals or those in large facilities, as they may not be able to hear alarms even when nearby.
Innovation Solution
A system and method for adaptive detection of audio alarms that uses a microphone, communications interface, and processor to analyze sounds, learn alarm characteristics, and compare them to stored templates, allowing for the generation and storage of new alarm templates based on user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If audible alarms are used to communicate device states or events to users, then users can be notified of important information, but hearing-impaired individuals or persons in large facilities cannot hear these alarms even when present at the same location
Solution Approach 1:
The patent introduces a microphone and signal processing system as an intermediary between the alarm sound and the user. The system captures the alarm audio signal, processes it to extract characteristics, and relays it to the user through a computing device, bridging the gap for those who cannot hear the alarm directly.
Solution Approach 2:
The patent replaces the direct acoustic transmission mechanism (human hearing) with an electronic signal processing system. The microphone converts sound waves to electrical signals, which are then processed and transmitted digitally, substituting the mechanical/acoustic pathway with an electronic one.
2Measurement precision
If the system analyzes received sounds to determine alarm characteristics using signal processing algorithms, then the system can detect and recognize audio alarms, but the system complexity increases
Solution Approach 1:
The patent segments the sound analysis process into distinct functional modules: audio capture by microphone, signal processing to extract characteristics, template matching for identification, and notification generation. This modular segmentation manages complexity by breaking down the overall function into manageable, independent components.
Solution Approach 2:
The system performs preliminary actions by pre-storing alarm templates with their characteristic patterns before actual alarm detection is needed. When an alarm occurs, the system compares the captured signal against these pre-prepared templates, avoiding the need for complex real-time analysis from scratch and simplifying the detection process.
3Productivity
If the system stores a defined set of alarm templates for comparison, then the system can quickly identify matching alarms, but the system cannot detect new or previously unseen alarm types
Solution Approach 1:
The patent implements feedback by allowing users to provide input when an unrecognized alarm is detected. The system presents the detected alarm characteristics to the user, who can confirm or correct the identification. This feedback loop enables the system to learn and adapt to new alarm types while maintaining rapid identification of known alarms through template matching.
Solution Approach 2:
The system transitions from a static template-matching approach to a dynamic adaptive system. The alarm template database can be updated based on user feedback and newly detected alarm patterns, allowing the system to evolve and recognize new alarm types while preserving the efficiency of template-based recognition for established alarms.
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 the detection and recognition of audio alarms even when the user is not present, providing alerts to client devices and allowing for the learning and storage of new alarm templates, thereby improving alarm detection and notification in various environments.
Implementation Method 1
a microphone configured to receive a series of sounds
Data Source
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AI summary
Systems and methods are provided for the adaptive detection of audio alarms. A system comprises a microphone configured to receive a series of sounds, a memory configured to store a defined set of alarm templates, a communications network interface, and a processor. The processor is configured to receive and analyze sounds for alarm or background sound characteristics and compare them to a defined set of alarm templates stored in the memory. If not contained in the defined set of alarm templates previously stored in the memory, new alarm templates are learned and stored. An alert is then transmitted to a client device that an audio alarm has been recognized.