The causes of traffic accidents are diverse, including weather, road conditions, road design, and psychological factors. With the advancement of information technology, big data on traffic accidents can be collected and analyzed more easily than before. To identify the causes of traffic accidents, we analyzed the Traffic Enforcement Case Database and Traffic Accident Database of the Traffic Division of the National Police Agency in Taiwan. The main causes of traffic accidents from 2013 to 2020 were lane drifting, overspeeding, illegal turning, running red lights, and drunk driving. The number of traffic violations has increased every year in the same period, and the number of casualties and injuries has increased since 2018. It is necessary to customize sensor technologies to monitor such violations to prevent related accidents. Advanced data mining technologies should be used to analyze the data and obtain better information to prevent violations and accidents. The results of this study provide a basis for further study related to developing preventive measures for traffic violations and accidents using advanced sensor technologies.