U4SSC – Case study – Crime prediction for more agile policing in cities – Rio de Janeiro, Brazil
In this issue
Rio de Janeiro is the second most populated municipality in Brazil and the sixth most populated in the Americas. Designated a UNESCO World Heritage Site and home to many prominent educational institutions, thriving industries, and beautiful landscapes, the economic disparity between the rich and poor is drastic. In 2017, Brazil experienced a murder rate of 30.8 per 100,000 people. Crime Prediction for More Agile Policing in Cities – Rio de Janeiro, Brazil is a case study that shows how leaders in Rio predicted the crime rate and developed an agile policy to lower it. The city developed a digital platform that can predict crime based on available crime data and used its predictive analytics model to police crime while facing challenges of using artificial intelligence as a tool for crime prevention. Based on this study, authorities believe predictive analytics can be used to predict crime in other localities.
