RT info:eu-repo/semantics/conferenceObject
T1 Evaluation of transport events with the use of Big Data, artificial intelligence and augmented reality techniques
A1 Pérez Diez, Fernando
A1 Cabrerizo Sinca, Julià
A1 Roche Vallès, David
A1 Campos Cacheda, José Magín
K1 Big Data
K1 Inteligencia artificial
K1 Artificial intelligence
K1 Ingeniería civil
K1 Civil engineering
K1 Transporte
K1 Transportation
AB The phenomenon of "smart cities" generalizes the use of Information and CommunicationTechnologies. The generation and use of data to manage mobility is a challenge that manycities are betting on and investing in. Through the Internet of all things (IoT) and the use ofsensors and mechanisms for capturing information, the number of data analysis tools suchas Big Data, Artificial Intelligence (AI), and Augmented Reality (AR) has increased.The tools that are used to interpret events are applied to the analysis of video andphotographic images and comprise of a set of programs, mathematical algorithms andprotocols. The implementation of procedures could enable the automatic interpretation ofimage information, from the most basic such as changes in the presence of objects or people,to the identification of complex shapes and relevant event detection. With the constant useof the assisted process learning (Machine Learning), it’s possible to improve eventinterpretation through the customization of learning protocols.Repetitively trained software can identify relevant events and report changes in criticalscenarios that can trigger a series of protocols. The use of artificial intelligence techniquesmakes it possible to automate monotonous processes and improve transport management.This article analyzes different technologies used to generate transport information and datavalidation. It is intended to experiment with the use of technologies in the detection ofrelevant facts, changes of state, and identification of events. It also measures the reliabilitylevel when detecting events, and studies the implementation of possible solutions into thetransport management system, in order to assist in decision making processes.
PB Universidad de Burgos. Servicio de Publicaciones e Imagen Institucional
SN 978-84-18465-12-3
YR 2021
FD 2021-07
LK http://hdl.handle.net/10259/6863
UL http://hdl.handle.net/10259/6863
LA eng
NO Trabajo presentado en: R-Evolucionando el transporte, XIV Congreso de Ingeniería del Transporte (CIT 2021), realizado en modalidad online los días 6, 7 y 8 de julio de 2021, organizado por la Universidad de Burgos
DS Repositorio Institucional de la Universidad de Burgos
RD 24-abr-2024