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MEGACHAIN: Blockchain for Integration, Privacy and Audit of Megacity Systems


The world population is mostly urban and the exacerbated growth of the urban environment leads to the emergence of large population clusters, known as megacities, which concentrate millions of inhabitants. In Brazil, there are currently two megacities: São Paulo and Rio de Janeiro. Megacities are complex environments that present various structural, operational, and security challenges that are amplified due to the scale of the environment. The information and communication technologies meet the needs of the megacities, constituting a tool to facilitate the monitoring and management of the city, and to allow coordination and integration among the different systems, enabling the establishment of communication through application program interfaces, constituting a new paradigm called Business-to-Business integration.The MEGACHAIN project has the goal to investigate the applications and feasibility of using the blockchain technology for integration between megacity systems, taking into account issues such as scalability, privacy, availability and auditing. This research will be carried out through implementations, simulations and evaluations in realistic scenarios, with the aid of experimental testbeds, to allow the identification and diagnosis of deficiencies, and the proposition of alternative paths that may influence the future standardizations of megacity systems. Blockchain mechanisms will also be proposed and analyzed to control and manage the exchange of information between the various megacity systems. Given the importance of interoperability among the various systems present in megacities, it is believed that the project will contribute to guarantee a better quality of life for the population through the efficient management and monitoring of the urban environment. The project team is composed by researchers from the Institute of Computing and the School of Engineering of the Fluminense Federal University, and by a researcher from UFJF, as well as PhD, MSc and undergraduate students. (AU)

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Scientific publications (5)
(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)
DE OLIVEIRA, NICOLLAS R.; PISA, PEDRO S.; LOPEZ, MARTIN ANDREONI; DE MEDEIROS, DIANNE SCHERLY V.; MATTOS, DIOGO M. F. Identifying Fake News on Social Networks Based on Natural Language Processing: Trends and Challenges. INFORMATION, v. 12, n. 1 JAN 2021. Web of Science Citations: 0.
NICOLLAS R. DE OLIVEIRA; LUCAS P. BOAVENTURA; TADEU N. FERREIRA; VANESSA P. R. MAGRI; JACQUELINE S. PEREIRA; DIOGO M. F. MATTOS. A Low Cost, High-Reliability Receiver System for Reading Passive RFID Tags. J. Microw. Optoelectron. Electromagn. Appl., v. 20, n. 4, p. 812-822, Dez. 2021.
PASSOS, DIEGO; DE SOUSA, CLEDSON O.; ALBUQUERQUE, CELIO. An NDT Model for Block Designs Operating Under Asymmetrical Duty Cycling. IEEE WIRELESS COMMUNICATIONS LETTERS, v. 9, n. 12, p. 2116-2120, DEC 2020. Web of Science Citations: 0.
MAGALHAES, LUIZ C. S. Association stability and handoff latency tradeoff in dense IEEE 802.11 networks: A case study. COMPUTER COMMUNICATIONS, v. 159, p. 175-185, JUN 1 2020. Web of Science Citations: 0.
DE OLIVEIRA, NICOLLAS R.; MEDEIROS, DIANNE S. V.; MATTOS, DIOGO M. F. A Sensitive Stylistic Approach to Identify Fake News on Social Networking. IEEE SIGNAL PROCESSING LETTERS, v. 27, p. 1250-1254, 2020. Web of Science Citations: 0.

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