Generation of Real Datasets for Network Simulation

• Autor(a) principal: Sanches Quessada, Matheus [UNESP]
• Data de Publicação: 2022
• Outros Autores: Lieira, Douglas [UNESP], Pereira, Rickson [UNESP], Gottsfritz, Euclydes [UNESP], Meneguette, Rodolfo
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1109/TLA.2022.9661462; http://hdl.handle.net/11449/223190
• topic: Dataset; mobile application; real data; simulation; traffic interventions; urban mobility

The high growth of urban centers brings several problems for the population, such as socioeconomic and health problems due to toxins, polluting gases, delay in emergency care, and the stress to which citizens are exposed to traffic. Generally, for predicting the impact of a given action in the city, simulations are used to take into account the mobility of its inhabitants. These simulations must correspond with the environment that you want to be represented. Therefore, datasets with real data, make the simulations more reliable so that the results obtained are more satisfactory. The project aims to build a dataset with real data of user locations and traffic interventions for network simulations, optimize services for intelligent transport systems, and improve urban mobility in the city of Catanduva-SP. The results were performed on the mobile application (TIMELESS) and show that it consumes few smartphone resources (data, memory, and battery) to collect and generate the data set, compared to the use of other applications in the same segment (traffic monitoring and route suggestion).