(available only in Portuguese)
Thefinal resultsof Call for Scientific Research and Technological Development Projects in Data Science and Artificial Intelligence in Public Administration – 2018 have been announced. The 15 approved projects involve partnerships between R&D units and public administration entities on topics such as health, public transport, water resource management, and the use of data from the European Space Agency's IPSentinel system. In total, the projects represent an investment of almost €4 million over three years.
The selected projects will be presented ata public sessionto be held this Wednesday, October 24, in the Noble Hall of the National Statistics Institute in Lisbon. The event will be attended by the Minister of the Presidency and Administrative Modernization, Maria Manuel Leitão Marques, and the Minister of Science, Technology, and Higher Education, Manuel Heitor.
This initiative is part of the Data Science and Artificial Intelligence in Public Administration Program, the Innovation Roadmap, and axis 5 (research) ofINCoDe.2030, developed by the Ministry of the Presidency and Administrative Modernization and the Ministry of Science, Technology, and Higher Education. The Call find innovative ways to relate data, find patterns, anticipate failures, and optimize processes in Public Administration, in an optimization that aims to benefit society as a whole.
See the presentations of the 15 selected projects:
iLU: Advanced Learning in Urban Data with Situational Context for Optimizing Mobility in Cities – Institute for Systems and Computer Engineering, Research and Development in Lisbon (INESC ID/INESC/IST/ULisboa) | CM Lisboa
Early detection of public transport vehicle malfunctions in an operational environment – Institute for Systems and Computer Engineering, Technology and Science (INESC TEC) | Metro do Porto, SA
Modeling and prediction of traffic accidents in the district of Setúbal – University of Évora (UE) | Setúbal Territorial Command of the National Republican Guard
IPSTERS – IPSentinel Terrestrial Recognition System – Institute for the Development of New Technologies (UNINOVA/FCTUNL/UNL) | Directorate-General for Territory
Intelligent Water Data System – Setúbal Polytechnic Institute | Barreiro City Council, Beja Municipal Water and Sanitation Company, Infraquinta
Detection of addition patterns in online gaming – Higher Institute of Statistics and Information Management – NOVA Information Management School (NOVA IMS) (NOVA IMS/UNL) | Turismo de Portugal, IP
Modeling student flow in the Portuguese education system – FCiências.ID | DGEEC
Understanding the determinants of academic performance: evidence from the Portuguese secondary education system – Higher Institute of Statistics and Information Management – NOVA Information Management School (NOVA IMS) (NOVA IMS/UNL) | DGEEC
EPISA—Inference of Entities and Properties for Semantic Archives – Inesc Tec – Institute for Systems and Computer Engineering, Technology, and Science (INESC TEC) | Directorate-General for Books, Archives, and Libraries (DGLAB)
Use of Artificial Intelligence to enhance Teledermatological Screening – Fraunhofer Portugal Research Association | Administration of Shared Services of the Ministry of Health
Neuroimaging biomarkers for the diagnosis of neuropsychiatric diseases, using artificial intelligence – FCiências.ID | HFF (Fernando da Fonseca Hospital), HSOG (Senhora da Oliveira Hospital, Guimarães), CHLN (Lisbon North Hospital Center), and SPMS (Shared Services of the Ministry of Health)
Identification and Forecasting of Hospital Emergency Demand – Calouste Gulbenkian Foundation | Administration of Shared Services of the Ministry of Health, E.P.E. (SPMS)
Data2Help: Data Science for Optimizing Emergency Medical Services – Institute for Systems and Computer Engineering, Research and Development in Lisbon (INESC ID/INESC/IST/ULisboa) | National Institute of Medical Emergency (INEM)
ICDS4IM – Intelligent Clinical Decision Support in Intensive Care Medicine – University of Minho (UM) | Porto Hospital Center (CHP/MS)
Predicting the risk of complications from surgical treatment and determining the prognosis in cancer patients by integrating clinical and biopathological data – Institute of Mechanical Engineering (IDMEC) | Portuguese Institute of Oncology of Porto Francisco Gentil, EPE
Published on October 23, 2018
