On the analysis of urban computing heterogeneous data

• Grant number: 20/05121-4
• Support Opportunities: Regular Research Grants
• Duration: April 01, 2021 - March 31, 2023
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Convênio/Acordo: MCTI/MC
• Principal Investigator: Heitor Soares Ramos Filho
• Grantee: Heitor Soares Ramos Filho
• Host Institution: Instituto de Ciências Exatas (ICEx). Universidade Federal de Minas Gerais (UFMG). Ministério da Educação (Brasil). Belo Horizonte , SP, Brazil
• Associated researchers: Alejandro César Frery Orgambide ; Aline Carneiro Viana Iannone ; André Luiz Lins de Aquino ; Antonio Alfredo Ferreira Loureiro ; Jefersson A dos Santos ; João Batista Borges Neto ; João Guilherme Maia de Menezes ; Leandro Aparecido Villas
• Associated scholarship(s): 21/04140-8 - Time series characterization and mining, BP.TT

Abstract

This project aims to investigate scientific research in Urban Computing, where new methods for analyzing social sensing data (participatory sensing, social network analysis, and opportunistic sensing) and remote sensing in the context of urban environments will be proposed. Initially, we will investigate new ways of representing time-series collected through social sensing based on the representation of ordinal patterns. Then, we will propose novel metrics from the proposed representations to advance the state-of-the-art of data mining of time-series for Urban Computing data. In summary, this project presents the proposal for scientific research in four lines: (i) mining of time series for Urban Computing, (ii) analysis of social sensing and urban mobility, (iii) data analysis of vehicle networks, Internet of things and wireless sensor networks, and (iv) remote sensing image analysis for urban environments. (AU)

Scientific publications

(13)

(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)

BARROS, PEDRO H.; RAMOS, HEITOR S.; IEEE. A novel aggregation method to promote safety security for poisoning attacks in Federated Learning. 2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022), v. N/A, p. 6-pg., 2022-01-01. (20/05121-4)

RODRIGUES, DIEGO O.; BRAUN, TORSTEN; MAIA, GUILHERME; VILLAS, LEANDRO; IEEE. Mobility-aware Software-Defined Service-Centric Networking. 2022 31ST INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATIONS AND NETWORKS (ICCCN 2022), v. N/A, p. 10-pg., 2022-01-01. (20/05121-4, 18/23064-8, 18/19639-5, 15/24494-8, 18/12447-3)

RODRIGUES, DIEGO O.; BRAUN, TORSTEN; MAIA, GUILHERME; VILLAS, LEANDRO; IEEE. Towards SDN-enabled RACH-less Make-before-break Handover in C-V2X Scenarios. 2021 17TH INTERNATIONAL CONFERENCE ON WIRELESS AND MOBILE COMPUTING, NETWORKING AND COMMUNICATIONS (WIMOB 2021), v. N/A, p. 8-pg., 2021-01-01. (20/05121-4, 20/11259-9, 18/23064-8, 18/19639-5, 15/24494-8, 18/12447-3)

REY, ANDREA A.; FRERY, ALEJANDRO C.; LUCINI, MAGDALENA; GAMBINI, JULIANA; CHAGAS, EDUARDA T. C.; RAMOS, HEITOR S.. Exploring Rates of Adherence and Barriers to Time-Restricted Eating. Entropy, v. 25, n. 5, p. 16-pg., 2023-04-28. (20/05121-4)

BARROS, PEDRO; QUEIROZ, FABIANE; FIGUEIREDO, FLAVIO; DOS SANTOS, JEFERSSON A.; RAMOS, HEITOR. A New Similarity Space Tailored for Supervised Deep Metric Learning. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, v. 14, n. 1, p. 25-pg., 2023-02-01. (20/05121-4)

CHAGAS, E. T. C.; FRERY, A. C.; GAMBINI, J.; LUCINI, M. M.; RAMOS, H. S.; REY, A. A.. Statistical properties of the entropy from ordinal patterns. Chaos, v. 32, n. 11, p. 13-pg., 2022-11-01. (20/05121-4)

CARDOSO-PEREIRA, ISADORA; LOBO-PAPPA, GISELE; RAMOS, HEITOR S.; IEEE. Neural Architecture Search for Resource-Constrained Internet of Things Devices. 26TH IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (IEEE ISCC 2021), v. N/A, p. 6-pg., 2021-01-01. (20/05121-4)

CHAGAS, EDUARDA T. C.; QUEIROZ-OLIVEIRA, MARCELO; ROSSO, OSVALDO A.; RAMOS, HEITOR S.; FREITAS, CRISTOPHER G. S.; FRERY, ALEJANDRO C.. White Noise Test from Ordinal Patterns in the Entropy-Complexity Plane. INTERNATIONAL STATISTICAL REVIEW, v. N/A, p. 23-pg., 2022-02-14. (20/05121-4)

CARDOSO-PEREIRA, ISADORA; BORGES, JOAO B.; BARROS, PEDRO H.; LOUREIRO, ANTONIO F.; ROSSO, OSVALDO A.; RAMOS, HEITOR S.. Leveraging the self-transition probability of ordinal patterns transition network for transportation mode identification based on GPS data. NONLINEAR DYNAMICS, v. 107, n. 1, NOV 2021. (20/05121-4, 21/04140-8)

BORGES, JOAO B.; RAMOS, HEITOR S.; LOUREIRO, ANTONIO A. F.. A Classification Strategy for Internet of Things Data Based on the Class Separability Analysis of Time Series Dynamics. ACM TRANSACTIONS ON INTERNET OF THINGS, v. 3, n. 3, p. 30-pg., 2022-08-01. (15/24494-8, 18/23064-8, 20/05121-4)

DE MATTOS, EKLER P.; DOMINGUES, AUGUSTO C. S. A.; SANTOS, BRUNO P.; RAMOS, HEITOR S.; LOUREIRO, ANTONIO A. F.. The Impact of Mobility on Location Privacy: A Perspective on Smart Mobility. IEEE SYSTEMS JOURNAL, v. 16, n. 4, p. 12-pg., 2022-02-25. (20/05121-4, 18/23064-8)

BARROS, PEDRO H.; CHAGAS, EDUARDA T. C.; OLIVEIRA, LEONARDO B.; QUEIROZ, FABIANE; RAMOS, HEITOR S.. Malware-SMELL: A zero-shot learning strategy for detecting zero-day vulnerabilities. COMPUTERS & SECURITY, v. 120, p. 18-pg., 2022-09-01. (20/05121-4)

CHAGAS, EDUARDA T. C.; BARROS, PEDRO H.; CARDOSO-PEREIRA, ISADORA; PONTE, IGOR V.; XIMENES, PABLO; FIGUEIREDO, FLAVIO; MURAI, FABRICIO; COUTO DA SILVA, ANA PAULA; ALMEIDA, JUSSARA M.; LOUREIRO, ANTONIO A. F.; et al. ffects of population mobility on the COVID-19 spread in Brazi. PLoS One, v. 16, n. 12, DEC 7 2021. (20/05121-4)