Sound Source Localization and Classification for Emergency Vehicle Siren Detection Using Resource Constrained Systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00375301" target="_blank" >RIV/68407700:21230/24:00375301 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/RADIOELEKTRONIKA61599.2024.10524053" target="_blank" >https://doi.org/10.1109/RADIOELEKTRONIKA61599.2024.10524053</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/RADIOELEKTRONIKA61599.2024.10524053" target="_blank" >10.1109/RADIOELEKTRONIKA61599.2024.10524053</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Sound Source Localization and Classification for Emergency Vehicle Siren Detection Using Resource Constrained Systems

Popis výsledku v původním jazyce

The present work introduces an intelligent system for sound source localization and classification, focusing on the critical task of detecting emergency vehicle sirens. Leveraging the STM32F411RE microcontroller and SPH0645LM4H microphones, the methodology combines generalized crosscorrelation with phase transformation for precise sound source localization, alongside Mel Frequency Cepstral Coefficients (MFCC) for robust signal processing. A neural network model, expertly trained and deployed on the microcontroller, enables real-time sound classification. The integrated printed circuit board (PCB) with eight LEDs provides visual cues, enhancing emergency vehicle detection. This work contributes significantly to sound localization, digital signal processing, and embedded systems, ultimately improving safety and responsiveness in emergency scenarios. The work is vital for enhancing road safety and emergency response efficiency by providing an intelligent system that accurately identifies and localizes the sound of emergency vehicle sirens, minimizing response times and potential hazards for all road users.

Název v anglickém jazyce

Sound Source Localization and Classification for Emergency Vehicle Siren Detection Using Resource Constrained Systems

Popis výsledku anglicky

The present work introduces an intelligent system for sound source localization and classification, focusing on the critical task of detecting emergency vehicle sirens. Leveraging the STM32F411RE microcontroller and SPH0645LM4H microphones, the methodology combines generalized crosscorrelation with phase transformation for precise sound source localization, alongside Mel Frequency Cepstral Coefficients (MFCC) for robust signal processing. A neural network model, expertly trained and deployed on the microcontroller, enables real-time sound classification. The integrated printed circuit board (PCB) with eight LEDs provides visual cues, enhancing emergency vehicle detection. This work contributes significantly to sound localization, digital signal processing, and embedded systems, ultimately improving safety and responsiveness in emergency scenarios. The work is vital for enhancing road safety and emergency response efficiency by providing an intelligent system that accurately identifies and localizes the sound of emergency vehicle sirens, minimizing response times and potential hazards for all road users.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2024 34th International Conference Radioelektronika (RADIOELEKTRONIKA)

ISBN

979-8-3503-6216-9

ISSN

2767-9969

e-ISSN

2767-9969

Počet stran výsledku

5

Strana od-do

—

Název nakladatele

IEEE Czechoslovakia Section

Místo vydání

Praha

Místo konání akce

Žilina

Datum konání akce

17. 4. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001229165000002