6 FUTURE WORK
Future work will include creating sustainability
indicators for monitoring and prevention of natural
disasters, contributing to achieving the goals of the
2030 Agenda, the Sendai Framework for Disaster
Risk Reduction 2015-2030, the National Civil
Protection and Defense Policy through Law
12608/2012; promoting actions within the scope of
the Innovation Ecosystem established in Macaé; and
supporting the development of projects with the
potential to generate technology-based businesses.
It is also planned to analyze the collected data,
geoprocess it, and adapt or resize the models
according to the needs of the Deputy Secretariat for
Civil Defense. In the educational area, an adjustment
of technical and scientific cooperation is planned and
carried out through teaching and/or research, and the
development of projects in the area of Protection and
Civil Defense aligned with Civil Defense projects in
schools.
In a second development cycle, prediction
mechanisms will be implemented through the
analysis of data stored on servers. BI tools (such as
Google Looker) have been applied in the training of
Civil Defense technicians, who, in the second
development cycle, will be advised by
Meteorological Engineering specialists belonging to
the multidisciplinary group in the analysis and
construction of predictability patterns.
REFERENCES
Banara, S., Singh, T., & Chauhan, A. (2022). IoT based
weather monitoring system for smart cities: a
comprehensive review. In 2022 International
Conference for Advancement in Technology. IEEE.
Bandeira, A. G., Marin, S. M., & Witt, R. R. (2014).
Vulnerability to natural disasters: implications for
nursing. Ciên Cuid Saúde, 13(4), 776-1.
Barcellos, P. D. C. L. et al. (2016). Diagnóstico
meteorológico dos desastres naturais ocorridos nos
últimos 20 anos na cidade de Duque de Caxias. Revista
Brasileira de Meteorologia, 31, 319-329.
Chaves, R., Schneider, D., Correia, A., Motta, C. L., &
Borges, M. R. (2019). Crowdsourcing as a tool for
urban emergency management: Lessons from the
literature and typology. Sensors, 19(23), 5235.
da Cruz Costa, J., & Guedes, L. A. (2022). Proposta de
integração curricular com Internet das Coisas na
Educação Profissional Técnica de Nível Médio. In
Anais do XXXIII Simpósio Brasileiro de Informática na
Educação (pp. 244-254). SBC.
de Freitas, C. M., de Carvalho, M. L., Ximenes, E. F.,
Arraes, E. F., & Gomes, J. O. (2012). Socio-
environmental vulnerability, disaster risk-reduction and
resilience-building: lessons from the earthquake in
Haiti and torrential rains in the mountain range close to
Rio de Janeiro in Brazil. Ciência & Saúde Coletiva,
17(6), 1577.
de Freitas, C. M. et al. (2014). Natural disasters and health:
an analysis of the situation in Brazil. Ciência & Saúde
Coletiva, 19(9), 3645.
Dresch, A., Lacerda, D. P., & Júnior, J. A. V. A. (2015).
Design science research: Research method for
advancement of science and technology. Porto Alegre:
Book.
Goecks, L. S., Souza, M. D., Librelato, T. P., & Trento, L.
R. (2021). Design Science Research in practice: review
of applications in Industrial Engineering. Gestão &
Produção, 28.
INMET (2024) Available at: https://portal.inmet.gov.br/ .
Accessed on: January 24, 2024.
Kobiyama, M., Monteiro, L. R., & Goerl, R. F. (2018).
Integração das ciências e das tecnologias para redução
de desastres naturais: Sócio-hidrologia e sócio-
tecnologia. Revista de gestão & sustentabilidade
ambiental. Palhoça, SC. vol. 7,.
Kodali, R. K., & Mandal, S. (2016). IoT based weather
station. In 2016 international conference on control,
instrumentation, communication and computational
technologies (ICCICCT) (pp. 680-683). IEEE.
Machado, C. C., & Machado, J. P. (2019). Análise teórica
dos desastres naturais: Gestão e política de assistência
social. Revista Grifos, 28(46), 160-174.
Math, R. K. M., & Dharwadkar, N. V. (2018). IoT Based
low-cost weather station and monitoring system for
precision agriculture in India. In 2018 2nd international
conference on I-SMAC (pp. 81-86).
Monteiro, V. L., SILVA, I. T. S., & FREITAS, T. D. S.
(2018). ANÁLISE DE TECNOLOGIAS DA IOT
PARA USO EM LOGÍSTICA HUMANITÁRIA E
BUSCA E SALVAMENTO DE PESSOAS.
CIMATech, 1(5).
Oliveira, L. F., Schneider, D., de Souza, J. M., & Rodrigues,
S. A. (2015). Leveraging the crowd collaboration to
monitor the waiting time of day-to-day services. In
2015 CSCWD.
Pentland, A. (2006). Collective intelligence. IEEE
Computational Intelligence Magazine, 1(3), 9-12.
Schneider, D., & De Souza, J. (2015). Engaging citizens
with news stories through social curation: A design
research project. In Proceedings of the 14th Brazilian
Symposium on Human Factors in Computing Systems.
Simões, N. A., & de Souza, G. B. (2016). A low cost
automated data acquisition system for urban sites
temperature and humidity monitoring based in Internet
of Things. In 2016 (INSCIT). IEEE.
Sobral, A. et al. (2010). Desastres naturais-sistemas de
informação e vigilância: uma revisão da literatura.
Epidemiologia e Serviços de Saúde, 19(4), 389-402.
Tulloch, D. (2014). Crowdsourcing geographic knowledge:
volunteered geographic information (VGI) in theory
and practice.