RT book part
T1 A real-time traffic alert system based on image recognition: A case of study in Spain
A1 Muñoz Ortega, Andrés
A1 Martínez España, Raquel
A1 Guerrero Contreras, Gabriel José
A1 Balderas Díaz, Sara
A1 Bueno Crespo, Andrés
A2 Ingeniería Informática
K1 traffic monitoring
K1 Deep Learning
K1 alert system
K1 image recognition
K1 real-time system
AB The management of road traffic incidents is a problem faced by governments in many countries. Normally, road operators have the infrastructure in place to monitor such incidents, albeit in a reactive manner.  In Spain, there are traffic cameras on major roads to check for possible incidents, however, incident notification is slow and not automated.  As an alternative, this paper proposes a system for automatic real-time traffic alerts. Thus, 1,500 camera images from the Dirección General de Tráfico (DGT) deployed on the main Spanish roads are analyzed in real time every 4 minutes. These images are not preprocessed, they have different qualities and are also affected by weather conditions such as fog, rain, sun reflections, etc. The system uses several Deep Learning classification models trained on a well-known dataset of traffic images including flowing traffic, dense traffic, accidents and fires. These models are used to classify the DGT images in real time, with satisfactory initial results, detecting both flowing traffic and dense traffic.
PB IEEE
SN 979-8-3503-1222-5
SN 2472-7571
YR 2023
FD 2023-07-14
LK http://hdl.handle.net/10498/34138
UL http://hdl.handle.net/10498/34138
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 06-nov-2026