This project generated audit reports on high-risk industries by integrating heterogeneous data and building automated data analysis modules; comparing the heterogeneous data of water, air, and waste; and automatically connecting the integrated and analyzed data for cross-comparison using visual and artificial intelligence analytics. Visual reporting was delivered to strengthen intuitive browsing for audit results, to shorten the time for auditors to review data, and to improve the efficiency of audit comparisons. The overall effectiveness of this project as indicated below: 1. Data was integrated and analyzed from Environmental Protection Administration’s Environmental Enforcement Management System (EEMS), Environmental Management System (EMS), Water Pollution Source Control Information Management System, Industrial Waste Report and Management System, Stationary Pollution Source Management Information Management, Public Nuisance Pollution Reporting System, Toxic Chemical Substances Registration and Declaration System. Data integration and data cleaning were completed on more than 3 million cross-system heterogeneous data records, which generated standardized data available for analysis. 2. A pollution risk assessment mechanism was established based on data of water, air, waste and potential areas. Through cross-comparison of the data using visual and artificial intelligence analytics, audit reports of 15 high-risk pollution industries were created. 3. Courses for visual analytics software that feature experience design, data analysis, and techniques of using visual analytics tools were offered to enhance inspectors’ data analysis and investigation capabilities, and improve the efficiency of investigating environmental crime.

Audit Using Artificial Intelligence, Visual Analytics, GPS Trajectory Analysis of Disposing and Transporting Waste