ATD-300 an AI empowered miniature acoustic device for automatic gunshot attacks detection and image capture

Built on over 30 years of acoustic source recognition expertise in transient impulsives signature, recently highly empowered by neural networks, and wave propagation model driven algorithms, ACOEM has developed the ATD-300, an acoustic sensor for automatic gunshot detection, identification and localization. What sets this sensor apart from the competition is its reliability in terms of detection rate over false alarm and robust high resolution shooter pointing capability. Therefore it can be used directly by police departments without third-party human validation. Resulting from the design effort to distribute intelligence among a collaborative sensor network, processing and artificial intelligence algorithms are fully embedded locally, enabling an alert to be raised in less than three seconds and a camera to be pointed at the shooter with only one sensor. In addition, as the system is already installed in several American cities, we will show how a device-to-server distributed artificial intelligence approach continuously improves the performance of the solution, fed by real field data.

Authors

Institutions

Publication Details

Journal
NOISE-CON proceedings
Published
2024-10-04
DOI
https://doi.org/10.3397/in_2024_4030
Citations
1
Primary Topic
Fire Detection and Safety Systems
Type
article
Field-Weighted Citation Impact
0.36
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ATD-300 an AI empowered miniature acoustic device for automatic gunshot attacks detection and image capture

Thierry Mazoyer, Julien PREUILH, Jean-Florent CROS
1 citations
NOISE-CON proceedings
Fire Detection and Safety Systems
0.36
article

ATD-300 an AI empowered miniature acoustic device for automatic gunshot attacks detection and image capture

Thierry Mazoyer, Julien PREUILH, Jean-Florent CROS
article en
1 citations

Abstract

Built on over 30 years of acoustic source recognition expertise in transient impulsives signature, recently highly empowered by neural networks, and wave propagation model driven algorithms, ACOEM has developed the ATD-300, an acoustic sensor for automatic gunshot detection, identification and localization. What sets this sensor apart from the competition is its reliability in terms of detection rate over false alarm and robust high resolution shooter pointing capability. Therefore it can be used directly by police departments without third-party human validation. Resulting from the design effort to distribute intelligence among a collaborative sensor network, processing and artificial intelligence algorithms are fully embedded locally, enabling an alert to be raised in less than three seconds and a camera to be pointed at the shooter with only one sensor. In addition, as the system is already installed in several American cities, we will show how a device-to-server distributed artificial intelligence approach continuously improves the performance of the solution, fed by real field data.

NOISE-CON proceedingsVol. 270(4)
ACOEM (France) (FR)
Openalex Percentile: Top 39%
Fire Detection and Safety Systems
0.36
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.