Techniques for crime prediction using official data considering time and space

• Heytor Norberth Leite da Silva UFPI
• Saul Sousa da Rocha UFPI
• Glauber Dias Gonçalves UFPI

DOI: https://doi.org/10.5753/ercemapi.2024.243773

Abstract

This paper proposes the use of official data to predict crime rates in metropolitan areas, with the aim of providing support for more effective public policies. To this end, a dataset was compiled that covers specific characteristics of urban regions, correlating them with official crime rates over time. The methodology adopted included the application of regression models and time series, which were evaluated for their ability to identify seasonal patterns and trends in crime occurrence. The results obtained demonstrate the effectiveness of these models in predicting crime rates, highlighting the importance of analytical tools in proactive decision-making by authorities and communities, aiming at preventing and combating crime.

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