Automatic Speech Recognition of Public Safety Radio Communications for Interstate Incident Detection and Notification

Most urban areas have Traffic Management Centers that rely partially on communication with 9-1-1 centers for incident detection. This level of awareness is often lacking for rural interstates spanning several 9-1-1 centers. This paper presents a novel approach to extending TMC visibility by automatically monitoring regional 9-1-1 dispatch channels using off-the-shelf hardware and open-source speech-to-text libraries. Our study presents a proof-of-concept study servicing 71 miles of rural I-65 in Indiana, successfully monitoring four county dispatch centers from a single location, and efficiently transcribing live audio within 60 s of broadcast. This work’s primary contribution is demonstrating the feasibility and practical value of automated incident detection systems for rural interstates. This technology is implementation-ready for extending the visibility of Traffic Management Centers in rural interstate segments. Further work is underway for developing scalable procedures for integrating multiple remote sites, extracting more diverse keyword sets, investigating optimal speech-to-text models, and assessing the technical aspects of the experimental procedures of this manuscript.

Authors

Institutions

Publication Details

Journal
Smart Cities
Published
2025-09-24
DOI
https://doi.org/10.3390/smartcities8050157
Primary Topic
Speech and Audio Processing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Automatic Speech Recognition of Public Safety Radio Communications for Interstate Incident Detection and Notification

Darcy M. Bullock, Jairaj Desai, Christopher Gartner, Vihaan Vajpayee
Smart Cities
Speech and Audio Processing
article

Automatic Speech Recognition of Public Safety Radio Communications for Interstate Incident Detection and Notification

Darcy M. Bullock, Jairaj Desai, Christopher Gartner, Vihaan Vajpayee
article en

Abstract

Most urban areas have Traffic Management Centers that rely partially on communication with 9-1-1 centers for incident detection. This level of awareness is often lacking for rural interstates spanning several 9-1-1 centers. This paper presents a novel approach to extending TMC visibility by automatically monitoring regional 9-1-1 dispatch channels using off-the-shelf hardware and open-source speech-to-text libraries. Our study presents a proof-of-concept study servicing 71 miles of rural I-65 in Indiana, successfully monitoring four county dispatch centers from a single location, and efficiently transcribing live audio within 60 s of broadcast. This work’s primary contribution is demonstrating the feasibility and practical value of automated incident detection systems for rural interstates. This technology is implementation-ready for extending the visibility of Traffic Management Centers in rural interstate segments. Further work is underway for developing scalable procedures for integrating multiple remote sites, extracting more diverse keyword sets, investigating optimal speech-to-text models, and assessing the technical aspects of the experimental procedures of this manuscript.

Smart CitiesVol. 8(5)
Purdue University West Lafayette (US)
Openalex Percentile: Top 68%
Speech and Audio Processing
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.