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Institutional development plan in the area of digital transformation: advanced manufacturing and smart and sustainable cities (PDIp)

Grant number: 17/50343-2
Support Opportunities:Research Grants - State Research Institutes Modernization Program
Duration: May 01, 2018 - April 30, 2024
Field of knowledge:Engineering - Electrical Engineering
Principal Investigator:Zehbour Panossian
Grantee:Zehbour Panossian
Host Institution: Instituto de Pesquisas Tecnológicas S/A (IPT). Secretaria de Desenvolvimento Econômico (São Paulo - Estado). São Paulo , SP, Brazil
Pesquisadores principais:
( Atuais )		Alessandra Cristina Corsi ; Alessandro Guimarães ; Alessandro Santiago dos Santos ; ALINE RIBEIRO MACHADO ; Ana Elisa Silva de Abreu ; Anarosa Alves Franco Brandão ; Andre Luiz Nunis da Silva ; Antonio Carlos Seabra ; Carlos Eduardo Cugnasca ; Chang Chiann ; Cristina Rossi Nakayama ; Fabio Kon ; Fernando Antônio Medeiros Marinho ; GIULIANA DEL NERO VELASCO ; Gregório Cardoso Tápias Ceccantini ; Homero Delboni Junior ; João Paulo Papa ; José Alberto Quintanilha ; José Luís de Paiva ; Juliana Gardenalli de Freitas ; Marcos Massao Futai ; Mario Ricardo Gongora Rubio ; Maurício Vicente Donadon ; Mauro de Mesquita Spinola ; Michael John Brennan ; Olga Satomi Yoshida ; Pedro Luiz Pizzigatti Corrêa ; Rafael Giuliano Pileggi ; Raquel Gonçalves ; Roberto Guardani ; Sérgio Brazolin ; Sergio Takeo Kofuji ; Solange Nice Alves de Souza ; Song Won Park ; Thiago Martins ; Vagner Luiz Gava
Pesquisadores principais:
( Anteriores )		Agenor de Toledo Fleury ; Cíntia Borges Margi ; Denis Fernando Wolf ; Edson Denner Leonel ; Fabio Prates Machado ; Luciana Wasnievski da Silva de Luca Ramos ; MAURÍCIO PINHEIRO DE OLIVEIRA ; Pedro Henrique Santin Brancalion ; Ronaldo Domingues Mansano ; Volnei Tita ; Wilhelmus Adrianus Maria van Noije
Associated grant(s):18/17359-5 - Multi-user equipment approved in grant 2017/50343-2: universal testing machine, AP.EMU
Associated scholarship(s):23/03883-2 - Use of time series models with machine learning tools: study about forecasting demand and water reservation in Peruibe County (Sao Paulo, Brazil)., BP.IC
22/16345-6 - Modeling using the finite element method of processing fast-curing composite materials., BP.TT
22/16562-7 - Machine learning models for assessing biodeterioration aspects of urban trees, BP.MS
 + associated scholarships 20/01275-7 - Evaluation of the use of cyber-physical systems as an innovation mechanism for mobility in smart and sustainable cities, BE.PQ
22/16468-0 - Dynamic flow chamber development for studies of vapor intrusion in contaminated sites, BP.MS
22/11904-7 - Digital transformation of a pilot iron ore milling plant integrated with Cyber-Physical systems to enable experiments for industry 4.0 scenarios., BP.TT
22/12512-5 - Implementation of measurement data processing and communication routines for wireless sensor networks applied to urban tree monitoring., BP.TT
21/05931-9 - Physico-chemical simulation and analysis for the development of 3D microfluidic devices, BP.PD
20/00058-2 - Stream water level forecasting in a built-up basin in Campinas, SP, using machine learning and aiming at structuring a flash flood early warning system, BP.MS
20/12640-8 - Root system analysis and self-optimization processes to prevent urban trees fall, BP.TT
20/01673-2 - Proposal of a tree monitoring system using inertial sensors within the IoT paradigm, BP.MS
20/05961-2 - An investigation into the optimum design parameters of an inertial sensor for use in detecting water leaks from buried pipes, BP.MS
20/01515-8 - Development and evaluation of ecoefficient cementitious compositions for application as 3D printing, BP.MS
19/21693-0 - Information system for analysis of large volumes of contaminated areas data, BP.DR
19/25805-8 - A big data tool for the analysis of data generated by an inertial MEMS sensor, BP.MS
19/22643-7 - Development of a prototype using sensors for remote data acquisition in contaminated sites, BP.MS
19/18287-0 - Real-time Urban Forest Management Using Machine Learning, BP.PD
19/18818-6 - Optimized design of MEMS-based gyroscope, BP.DR
19/17658-5 - Packaging project of inertial sensors using LTCC technology, BP.MS
19/16318-6 - Industry 4.0 deployment model, BP.MS
19/12933-8 - "Development of Etching Processes to Fabricate High Aspect Ratio Microstructures in MEMS", BP.PD
19/14011-0 - Machine learning for river flow modeling and flood prediction, BP.MS
19/08280-9 - Application of bayesian deep learning for Smart City monitoring and chemical industry processes operation, BP.MS
19/08850-0 - Development of fluid dynamics model for bubble column reactors: application in a vacuum degassing system for liquid metal treatment, BP.MS
19/10481-2 - Modelling of the wear of grinding media in the iron ore milling, BP.DR
19/01664-6 - Application of machine learning in the internet of things that compose the cyber-physical ecosystem of smart cities, BE.PQ
18/26226-9 - Study of simulation and optimization models using information generated in smart cities and industry 4.0 environments, BE.PQ
19/05840-3 - Mathematical modeling and computational simulation of gas-solid reactions in moving bed: application to the direct reduction process of iron ore, BP.DR
19/06377-5 - Computational fluid dynamics (CFD) study of a multiphase microorganism propagation step of a high-density bioreactor STR growth, BP.MS
19/03453-2 - MEMS-based inertial sensor for smart cities, BP.DR
19/04167-3 - Characterization and modeling of the geometrical distortion of thermoplastic composites, BP.DR
18/26592-5 - Development of a real-time forecasting model for demand and levels of reservoir with big data of water industry, BP.MS
18/14386-1 - Effect of condition of urban tree plantation in the soil available for its development and root morphology and distribution, BP.MS
18/21279-7 - Structuring geospatial information in big data for decision support, BP.MS
18/23052-0 - Interoperability in the application layer in cyber-physical systems, BP.MS
18/15869-6 - Use of sensor nodes for soil variables monitoring and landslides early detection, BP.MS - associated scholarships

Abstract

The digital transformation is still little consolidated in Brazilian society. Improvements in performance and differentiation resulting of such transformation have not yet been fully absorbed in companies and in the public administration. In general, solutions required for implementing the digital transformation in cities and in manufacturing processes combine advanced connectivity and automation services, cloud computing, dedicated sensors, 3D printing, connection capabilities, computational processes, intelligent algorithms, and the Internet of Things. Combined efforts among companies, government and Reference Institutions of Science and, technology (ICTs from Portuguese) are required to realize this transformation in Brazil. It is understood that IPT can become one of those reference ICTs. In this Institutional Research Development Plan - PDIP from Portuguese, the topic in question is addressed in two research domains - Advanced Manufacturing and Smart and Sustainable Cities. These topics are strongly related to IPT's mission to develop and apply technological solutions to increase the competitiveness of companies and promote the quality of life. In order to do so, it will be necessary to broaden and reinforce IPT's material and human resources for conducting research on core themes such as cyber physical systems, smart sensors and mathematical modeling that are within proposed research domains. This is intended to be achieved through the implementation of this PDIP. The Plan shall be carried out through actions in four areas: Infrastructure, Human Resources, Digital Capability and Creation of Prototypes by means of experimental activities. The expected results from this PDIP are: - To create the bases of a research powerhouse in Digital Transformation having as anchor institutions the IPT itself and the University of São Paulo; - Expand IPT's portfolio and intensify its interaction with companies and society; - To change the profile of the Institute's activities in order to emphasize the ability to conduct applied research and generate innovation. (AU)

Articles published in Agência FAPESP Newsletter about the research grant:
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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)
MALENA DELIA OTERO; ANA ELISA SILVA DE ABREU; AMIN ASKARINEJAD; MARCELA PENHA PEREIRA GUIMARÃES; EDUARDO SOARES DE MACEDO; ALESSANDRA CRISTINA CORSI; RYNALDO ZANOTELE HEMERLY DE ALMEIDA. Use of low-cost accelerometers for landslides monitoring: results from a flume experiment. Soils and Rocks, v. 45, n. 3, . (17/50343-2, 18/15869-6, 19/16458-2)
AZEVEDO, CAIO DA SILVA; GONCALVES, RODRIGO FRANCO; GAVA, VAGNER LUIZ; SPINOLA, MAURO DE MESQUITA. A Benford's Law based methodology for fraud detection in social welfare programs: Bolsa Familia analysis. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, v. 567, . (19/14011-0, 17/50343-2)
JODAS, DANILO SAMUEL; YOJO, TAKASHI; BRAZOLIN, SERGIO; VELASCO, GIULIANA DEL NERO; PAPA, JOAO PAULO. Detection of Trees on Street-View Images Using a Convolutional Neural Network. International Journal of Neural Systems, v. 32, n. 01, . (14/12236-1, 19/07665-4, 13/07375-0, 17/50343-2, 19/18287-0)
AZEVEDO, CAIO DA SILVA; GONCALVES, RODRIGO FRANCO; GAVA, VAGNER LUIZ; SPINOLA, MAURO DE MESQUITA. A Benford's law based method for fraud detection using R Library. METHODSX, v. 8, . (17/50343-2, 19/14011-0)
ROCHA, JAQUELINE F.; HOSTERT, LEANDRO; BEJARANO, MARTHA LUCIA M.; CARDOSO, ROBERTA M.; SANTOS, MATHEUS D.; MARONEZE, CAMILA M.; GONGORA-RUBIO, MARIO R.; SILVA, CECILIA DE CARVALHO CASTRO. Graphene oxide fibers by microfluidics assembly: a strategy for structural and dimensional control dagger. NANOSCALE, . (17/50343-2)

Please report errors in scientific publications list by writing to: cdi@fapesp.br.