Back
Journal article Open Access Scopus Source The journal / series is indexed in Scopus (SCImago list). The article itself has not been verified. 1 Citations

A deep learning model for detection of traffic events based on social networks publications

Capela, Sílvio , Pereira, Vítor , Duque, Jorge , Filipe, Vítor
ISLA — Instituto Politécnico de Gestão e Tecnologia
Procedia Computer Science, Volume 204, 2022, pp. 91–98
DOI: 10.1016/j.procs.2022.08.011

Resume

Abstract
Nowadays, social networks are one of the biggest ways of sharing real time information. These networks, have several groups focused on sharing information about road incidents and other traffic events. The work here presented aims the creation of an AI model capable of identifying publications related to traffic events in a specific road, based on publications shared on social networks. A predictive model was obtained by training a deep learning model for the detection of publications related with road incidents with an average accuracy of 95%. The model deployed as a service is already fully functional and is operating in 24/7 while awaits a final integration with the road management system of a company where it will be used to support the Control Center team in the decision making.

Keywords

#traffic incident detection #road incidents #Social media #Deep Learning #real-time data exchange #road administration #text classification #Computer science #Control (management) #Information sharing #Service (business)

Bibliographic Details

Publication Type Journal article
Publication Year 2022
Journal / Conference / Work Procedia Computer Science
ISSN 1877-0509
Volume / Issue Vol. 204
Pagination pp. 91–98
Scopus Indexing Indexed source (via SCImago)

ISLA Authors & Affiliations

J
Jorge Manuel Pereira Duque
jorge.duque@islagaia.pt ID: FD15-6377-8559
Profile