Technological Solution for Crime Prevention in Los Olivos

This research proposes a technological solution for citizen security and crime prevention based on machine learning in the district of Los Olivos, which alerts if the area in which a citizen is located is unsafe, showing a probability of the level of insecurity in each area, making more visible the areas with the highest level of insecurity; this was achieved using a machine Learning model, with the Naive Bayes algorithm exactly. A sample of 108 users was used for validation, with whom the technological solution was tested using a test scenario. In this sense, a questionnaire was elaborated to evaluate the perception of the users with an acceptance level of 93.5%. On the other hand, when using the Naive Bayes algorithm is ensured to obtain a better “Accuracy” and distribution by category in comparison with the following algorithms: classification forest, carboost classifier and KNN respectively. Therefore, it was with the use of one the Naive Bayes algorithm that the technological solution was carried out. The technological solution proposed is innovative for Peru because it uses machine learning as a technology. In addition, this solution could be replicated in any other district of Metropolitan Lima.