Light-Fixture Gunshot Detection With Edge Machine Learning
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Solution Overview
Problem
Existing gunshot detection systems face challenges in accurately locating gunshots in urban environments due to bandwidth and processing requirements, echo interference, and device obstructions, leading to delayed notifications and potential evidence loss.
Innovation Solution
A network of recording devices mounted on light fixtures uses machine learning and multilateration techniques to process audio data locally and transmit only spectrograms of gunshots to a remote server, reducing bandwidth and processing load while accurately determining gunshot locations using machine learning and multilateration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If recording devices continuously stream audio data to a remote server, then gunshot detection capability is improved, but network bandwidth consumption increases significantly
Solution Approach 1:
The patent extracts and processes only the essential information (gunshot detection results and spectrograms) at the edge recording devices, transmitting only this processed data to the remote server instead of streaming all raw audio data. This extraction approach maintains detection capability while dramatically reducing network bandwidth consumption.
Solution Approach 2:
The system segments the audio processing function between edge recording devices and the remote server. Edge devices perform local preprocessing and gunshot detection, while the server performs multilateration and final location determination. This segmentation allows selective transmission of only necessary data, reducing overall bandwidth requirements.
2Measurement precision
If multiple recording devices are deployed across a city, then gunshot location accuracy is improved, but processing power requirements at the remote server increase significantly
Solution Approach 1:
The patent segments the computational workload by performing gunshot detection and spectrogram generation at edge recording devices, then transmitting only these processed results to the remote server for multilateration. This segmentation reduces the processing power burden on the remote server while maintaining the ability to utilize multiple devices for accurate location determination.
Solution Approach 2:
The system performs preliminary gunshot detection and audio processing at the edge recording devices before data reaches the remote server. This preliminary action filters out non-gunshot audio data, so the remote server only needs to process relevant spectrograms from multiple devices, significantly reducing its processing requirements.
3Ease of operation
If recording devices are placed at ground level, then ease of installation is improved, but recording accuracy deteriorates due to obstructions from passerby objects
Solution Approach 1:
The patent transitions the recording devices from ground level (2D plane) to elevated positions on light fixtures (3D vertical dimension). This dimensional change places microphones above passerby objects, eliminating obstructions while maintaining ease of installation by utilizing existing light fixture infrastructure.
4Reliability
If recording devices are mounted on light fixtures, then recording accuracy is improved by avoiding obstructions, but device complexity increases
Solution Approach 1:
The patent makes the recording devices universal by designing them to mount on existing light fixtures, which serve dual purposes: providing elevated positioning for accurate audio recording and providing power through the electrical infrastructure. This multi-functionality approach reduces installation complexity despite the elevated mounting requirement.
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
This approach enables rapid and precise gunshot detection and notification to authorities, allowing timely intervention and evidence collection.
Implementation Method 1
A microphone may be mounted within or on the housings mounted to the light fixtures
Implementation Method 2
The sound waves of gunshots can be loud and can echo off of buildings surrounding the streets in a city
Data Source
AI summary
An apparatus for detecting gunshots. The apparatus may include a device housing configured to removably couple to a light fixture; a microphone inside or mounted to the device housing; and a processor inside the device housing and electrically coupled to the microphone. The processor can be configured to receive audio data from the microphone; execute a machine learning model using the audio data as input to determine whether the audio data corresponds to a gunshot; and responsive to determining the audio data corresponds to a gunshot, transmit the audio data to a remote processor.