2UEI -- internet 2.0 and mobility internet as heterogeneous data sources for smart cities

• Grant number: 15/24423-3
• Support Opportunities: Regular Research Grants
• Duration: October 01, 2017 - December 31, 2019
• Field of knowledge: Physical Sciences and Mathematics - Computer Science
• Convênio/Acordo: MCTI/MC
• Principal Investigator: Ana Lúcia Cetertich Bazzan
• Grantee: Ana Lúcia Cetertich Bazzan
• Host Institution: Instituto de Informática. Universidade Federal do Rio Grande do Sul (UFRGS). Ministério da Educação (Brasil). Porto Alegre , SP, Brazil
• Associated researchers: Jorge Leonid Aching Samatelo ; Marcia Pasin ; Rosaldo Jose Fernandes Rossetti
• Associated scholarship(s): 18/25919-0 - 2UEI internet 2.0 and mobility internet as heterogeneous data sources for smart cities, BP.TT; 18/05150-4 - 2 UEI Internet 2.0 and boarded by vehicle as heterogeneous sources data on intelligent cities, BP.TT; 17/27072-2 - 2UEI -- Internet 2.0 and mobility internet as heterogeneous data sources for smart cities, BP.TT

Abstract

Estimates show that the loss of time in traffic in Brazil generates losses of billions of Brazilian reais per year.Although Brazilian traffic authorities act au pair with the most effective techniques in traffic engineering, the use of Internet has evolved little in this area.As a consequence, one has an interesting panorama in Brazil: users (of public as well as private transportation means) are organizing themselves to fill the gap left by the authorities, which do not provide the information users want.Currently, this process is centered around Waze, MapLink and Google, without a real synergy with traffic authorities in charge.In fact, the presence of mobile devices and Internet 2.0 in this scenario is more and more ubiquitous.In the future, we will also have the so-called \textit{mobility Internet}, thus cars will exchange information.Extracting this potential from such diverse data sources will require new paradigms of data gathering, information broadcast, simulation and optimization.This way, the Internet and its new associated Technologies can potentially not only provide information to the traveller (as it is already the case), but also fill the gap that affects authorities, which do not have the means to use state-of-the-art monitoring tools, to run simulations at microscopic level, and to optimize the control (e.g., of traffic lights).This way, this project proposes methods for gathering and using of data from Internet-based heterogeneous sources, in order to provide information to traffic authorities, as well as to logistics, and to the traveller (in this case, considering his/her own context, something which is less common in the literature).Such sources are: text from social networks as Twitter; weather information; cultural and sports events; images about the density of traffic; car to car communication; etc.This way, as it is typically the case when one talks about Internet 2.0, the information flow is two-way, and both, traveller and authority, take advantage of it. (AU)

Scientific publications

(4)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

CHAMBY-DIAZ, JORGE C.; ESTEVAM, RHUAM SENA; BAZZAN, ANA L. C.. Identifying traffic conditions from non-traffic related sources. JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, NOV 2020. (15/24423-3)

LESSA RIBEIRO, MATHEUS VIEIRA; ACHING SAMATELO, JORGE LEONID; CETERTICH BAZZAN, ANA LUCIA. A New Microscopic Approach to Traffic Flow Classification Using a Convolutional Neural Network Object Detector and a Multi-Tracker Algorithm. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, v. 23, n. 4, p. 5-pg., 2022-04-01. (15/24423-3, 18/05150-4)

BAZZAN, A. L. C.; CHAMBY-DIAZ, J. C.; ESTEVAM, R. S.; SCHMIDT, L. DE A.; PASIN, M.; SAMATELO, J. L. A.; RIBEIRO, M. V. L.; NEDEVSCHI, S; POTOLEA, R; SLAVESCU, RR. Using Information from Heterogeneous Sources and Machine Learning in Intelligent Transportation Systems. 2019 IEEE 15TH INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTER COMMUNICATION AND PROCESSING (ICCP 2019), v. N/A, p. 8-pg., 2019-01-01. (15/24423-3)

CHAMBY-DIAZ, JORGE C.; ESTEVAM, RHUAM SENA; BAZZAN, ANA L. C.. Identifying traffic conditions from non-traffic related sources. JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, v. 26, n. 1, p. 12-pg., 2020-11-16. (15/24423-3)