Advanced search
Start date

FGV Analytics - Public Security Policies Analytics Research Center

Grant number: 20/07019-2
Support Opportunities:Research Grants - Problem-Oriented Research Centers in São Paulo
Duration: February 01, 2023 - January 31, 2028
Field of knowledge:Interdisciplinary Subjects
Principal Investigator:João Luiz Becker
Grantee:João Luiz Becker
Host Institution: Escola de Administração de Empresas de São Paulo (EAESP). Fundação Getúlio Vargas (FGV). São Paulo , SP, Brazil
Pesquisadores principais:
Eduardo de Rezende Francisco ; Leandro Piquet Carneiro ; Roberto Speicys Cardoso
Associated researchers: Alberto Liebling Kopittke Winogron ; Andre Luiz Silva Samartini ; Arley Topalian ; Artur André Almeida de Macedo Oliveira ; Carla Bonato Marcolin ; Ciro Biderman ; Daniele Gutierrez Moreira da Cunha ; Danilo Panzeri Nogueira Carlotti ; Edivaldo Almeida de Souza ; Eduardo Fonseca Mendes ; Fabio Ramazzini Bechara ; Gustavo Correa Mirapalheta ; Hitoshi Nagano ; Joana da Costa Martins Monteiro ; João Henrique Martins ; Jorge Luis Poco Medina ; José Luiz Carlos Kugler ; Maria Alexandra Viegas Cortez da Cunha ; RAFAEL RAMOS DA SILVA ; Roberto Beccaria Calestini ; Rodrigo Marotti Togneri ; Rodrigo Serrano Berthet ; Samuel Figueiredo Silveira
Associated scholarship(s):24/02581-5 - FGV Analytics - Public Security Policies Analytics Research Center, BP.IC


We propose the creation of the FGV Center for Science Applied to Security with the support of the São Paulo State Public Security Secretariat and the IDB, responding to the call of NPOP-SP proposals made by FAPESP Science for Development Program, on the theme of Smart Cities and Public Security. The objective is to establish a research framework to promote the use of artificial intelligence systems to support decisions in the area of public security, providing the technical structure and adequate ambiance of articulation among the key actors in the sector and stimulating the development of evidence-based assessment tools to evaluate public policies. Three pillars structure the proposal, differentiating it from other initiatives: 1. Developing big data and AI tools, decision support systems, and monitoring the results of decisions based upon them; 2. Evaluating public security policies; and 3. Structuring research networks and open innovation processes. The main initial challenges defined together with the project partners are: (1) prediction of crimes to support operational planning, where research to find solutions will involve the creation of computational/statistical models to predict crimes (predictive policing); (2) monitoring and preventing cargo theft, with research involving temporal and similarity analysis, forecasting probabilities of events; (3) granular categorization of information contained in police reports filed by citizens (BOs) and incident reports from police officers (RAIAs), with research for solutions comprising text mining techniques; (4) prediction of serial crimes - the case of automatic teller machines, involving research in temporal and similarity analysis; (5) modeling the behavior of gangs and organized crime, with research focused on network analysis; (6) evaluation of security policies, conducting experiments, quasi-experiments and surveys to find solutions; (7) evaluation of the different policing strategies adopted by the PMESP, with research encompassing the development of a tool to support decisions; (8) effectiveness of policing programs to reduce criminality, where research to find solutions will use ex-post evaluations of programs; (9) understanding whether the technological tools developed really have affected rates of criminality and security perception, including experimental evaluation of technology usage to combat crime; and (10) asymmetry between crime indices and security perception, with research involving development and collection of security perception metrics. (AU)

Articles published in Agência FAPESP Newsletter about the research grant:
Articles published in other media outlets (0 total):
More itemsLess items

Please report errors in scientific publications list using this form.