An adaptive police duty scheduling system based on machine learning

The research concerns police duty scheduling based on machine learning technology, instead of using manual arrangements. The aim is to have fair duty scheduling for police officers, and to make police projects more efficient. The system carries out police duty scheduling using database tools which we call “dbtools”. It is implemented by analyzing and proposing five working tables from modern police duty scheduling in Taiwan. We carried out analysis on practical police work and port machine learning methodologies onto our system. This results in a more human-oriented and user friendly system. Our system pioneers police duty research on scheduling. We hope that it results in better police management