Dog Bark Detection Collar Using Segmented Audio Sampling
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Solution Overview
Problem
Current bark detection systems in pet collars are not reliable or accurate, especially in environments with multiple noises similar to a dog bark, leading to ineffective training and deterrence.
Innovation Solution
A dog collar system with built-in electronics that uses a method involving digital audio samples, scaled second derivatives, and threshold comparisons to detect barking, incorporating a primary and secondary processor to differentiate between barking and non-barking sounds, and activate deterrents when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If simple audible bark detection is used, then the system is easy to operate and responds quickly, but the reliability and accuracy deteriorate due to false positives from similar environmental noises
Solution Approach 1:
The detection process is segmented into two distinct stages: a first digital audio sample taken for a first period of time for initial assessment, and a second digital audio sample taken for a second period of time (longer than the first) for confirmatory analysis. This segmentation allows the system to filter out false positives by requiring both stages to confirm bark presence, thereby improving reliability without requiring overly complex algorithms.
Solution Approach 2:
The system performs preliminary action by taking a first digital audio sample and comparing it to a previous sample to determine if the difference is below a predetermined initial threshold level. Only when this preliminary check passes does the system proceed to take the second, longer digital audio sample. This preliminary filtering action reduces unnecessary processing and improves detection accuracy by eliminating obvious non-bark sounds early in the process.
2Reliability
If continuous audio monitoring is used, then bark detection accuracy is improved, but energy consumption increases
Solution Approach 1:
The system dynamically adjusts its monitoring intensity based on conditions. The first digital audio sample is taken for a shorter first period of time, and only when the difference between samples indicates potential bark activity does the system proceed to the more energy-intensive second sampling stage. This dynamic adjustment of monitoring depth maintains detection accuracy while minimizing unnecessary energy consumption during periods of no bark activity.
Solution Approach 2:
The system employs periodic action by taking digital audio samples at specific intervals rather than continuously monitoring. The first sample is taken for a first period of time, and the second sample is taken for a second period of time when needed. This periodic sampling approach maintains adequate detection accuracy while significantly reducing energy consumption compared to continuous monitoring.
3Measurement precision
If longer audio samples are taken, then detection accuracy is improved, but the response time to detect barks deteriorates
Solution Approach 1:
The audio sampling is segmented into two parts with different durations and purposes. The first digital audio sample is taken for a shorter first period of time for quick initial assessment, while the second digital audio sample is taken for a longer second period of time only when needed for confirmatory analysis. This segmentation allows the system to achieve high measurement precision through the longer second sample while maintaining fast response time through the shorter first sample that quickly eliminates non-bark sounds.
Data Source
AI summary
A dog bark detection and deterrent method and system including a collar configured to be affixed to a pet, the collar having an audio transmitter configured to provide an audio stimulus; and a power source provided within collar operable to provide power to the audio transmitter, and an audio sensor. The collar is configured to determine when a dog is barking and provide stimulus to deter the dog from continuing to bark.