Researchers at the University of California, Berkeley seek to evaluate the real-world impacts of diesel emission control technologies that have been standardized on newer heavy-duty diesel trucks in California to help inform future health and climate policies. However, the manual analysis of truck emission data is laborious and time-consuming. Using machine learning, the team developed an application that automates the analysis of truck emissions using synchronized sensor data while emphasizing reliability, usability and controllability.