Análise de padrão em base de dados de monitoramento de rodovias

Abstract

This study aims to analyze patterns from a road monitoring database, applying computational techniques to process and interpret data collected by the private company responsible for managing highways BR-365 and BR-364. The information is extracted from the geographical coordinates of monitored vehicles based on data provided by the concessionaire, enabling the identification of traffic patterns, as well as segments where there are gaps in monitoring coverage and in the effectiveness of the service provided by the concessionaire. Data processing and organization were carried out using Python, PostgreSQL, and some reverse geocoding APIs for this analysis. The adopted methodology included the creation of a database, adaptation of records, and application of statistical techniques to assess the regularity of monitoring. The results showed that although some regions exhibit satisfactory coverage in a general analysis, when examining specific points, there are segments with significant monitoring failures by the concessionaire, and greater attention should be given to these areas. It is concluded that data analysis plays a fundamental role in optimizing road management, allowing concessionaires to direct investments to improve monitoring and ensure greater safety for road users. The study also suggests improvements in monitoring infrastructure and the use of more robust technologies to mitigate failures in data collection.