With the EPA’s recent development of implementing air quality IOT projects widely in Taiwan, the project was required to choose four industrial parks from central Taiwan to install micro-scaled wind speed and wind direction sensors and use high-definition drone cameras to acquire higher resolution geographical coordinates of the plants in the parks, which would be pre-set in the TrackAIR big data platform to automatically identify the pollution emitting events and their probable polluting sources accordingly. Then a discrepancies investigation among the various environmental permitting documents would be followed for the previously identified plants, which would provide facts for the inspectors to make their plans to either conduct a surrounding survey or enter the target plant for source testing with appropriate scientific tools. Such approach will better the effectiveness and efficiencies of the inspection in a smarter way. Comparing the scientific tools analysis and TrackAIR’s findings for the same time period, it suggested a pretty good consistency. Another issue that CEMS auditing is quite labor intensive due to the large amount of data and information needing manual processing, which therefore sometimes leads to mis-interpretate the CEMS monitoring data, or falsely judge their conformity to legitimate requirements. An automatic assessment technology has been developed as a computer program including the Data Pre-processing Module, Abnormality Detection Module, Data Visualization Module, and a Web Page to access all processed information. The program was tested at the Taipei Neihu Recycling Plant, which demonstrated its benefits in terms of increasing the inspector’s data handling capabilities, reducing auditing time consumed, minimizing human errors, and enlarge auditing capacities. All the above results have been summarized in the promoting activities including an expert consultation seminar, two workshops, promotion films and press release drafts, which were aimed to expedite the adoption of advanced technologies on environmental law enforcements.

Air pollution,，AI smart auditing， CEMS