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Na atualidade, a aplicação de sistemas baseados em inteligência artificial (IA) no combate à sinistralidade rodoviária já é uma realidade, apresentando resultados significativos. Em Portugal já foram dados os primeiros passos nesta área, principalmente através de projetos de investigação desenvolvidos por algumas Academias, dos quais se destaca o projeto da Universidade de Évora MOPREVIS.
Partindo do argumento que a aplicação de metodologias de IA na construção de modelos preditivos potencia a prevenção e o alerta da sinistralidade rodoviária, afigurou-se pertinente analisar de que forma podem ser potenciados os contributos da IA no combate ao flagelo da sinistralidade rodoviária, usando como caso de estudo o modelo MOPREVIS.
Para cumprir este desiderato, recorreu-se a um processo metodológico assente no raciocínio indutivo, materializado por uma estratégia de investigação mista, na qual se recorreu a técnicas de análise documental, inquéritos por entrevista e inquéritos por questionário, num desenho de pesquisa de estudo de caso.
Foi possível concluir que a forma de potenciar os contributos da IA para a prevenção e alerta da sinistralidade rodoviária deve ser sustentada nas seguintes linhas de orientação estratégica: LOE1 - Assegurar qualidade e rigor; LOE2 - Automatizar; LOE3 - Desenvolver e diversificar; e LOE 4 - Cooperar e colaborar.
Currently, the application of artificial intelligence (AI) systems in combating road accidents is already a reality, with significant results. In Portugal, the first steps have already been taken in this area, mainly through research projects developed by some universities, including the MOPREVIS project at the University of Évora. Given that the application of AI methodologies in the construction of predictive models can enhance the prevention and alert of road accidents, it was pertinent to analyse how the contributions of AI can be enhanced in combating the scourge of road accidents, using the MOPREVIS model as a case study. To achieve this goal, a methodological process based on inductive reasoning was used, materialized by a mixed research strategy, which included techniques of documentary analysis, interview surveys, and questionnaire surveys in a case study research design. It was possible to conclude that the way to enhance the contributions of AI to the prevention and alert of road accidents should be based on the following strategic guidelines: LOE1 - Ensuring quality and rigor; LOE2 - Automating; LOE3 - Developing and diversifying; and LOE 4 - Cooperating and collaborating.
Currently, the application of artificial intelligence (AI) systems in combating road accidents is already a reality, with significant results. In Portugal, the first steps have already been taken in this area, mainly through research projects developed by some universities, including the MOPREVIS project at the University of Évora. Given that the application of AI methodologies in the construction of predictive models can enhance the prevention and alert of road accidents, it was pertinent to analyse how the contributions of AI can be enhanced in combating the scourge of road accidents, using the MOPREVIS model as a case study. To achieve this goal, a methodological process based on inductive reasoning was used, materialized by a mixed research strategy, which included techniques of documentary analysis, interview surveys, and questionnaire surveys in a case study research design. It was possible to conclude that the way to enhance the contributions of AI to the prevention and alert of road accidents should be based on the following strategic guidelines: LOE1 - Ensuring quality and rigor; LOE2 - Automating; LOE3 - Developing and diversifying; and LOE 4 - Cooperating and collaborating.
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Inteligência Artificial Sinistralidade rodoviária Prevenção Alerta MOPREVIS Artificial Intelligence Road accidents Prevention Alert