The first section of the presentation focuses on the use of artificial intelligence to improve manufacturing and reduce carbon emissions (see 2019 report). Formosa's efforts go back to 2017, when the company was one of five business that each invested NT$30million in the creation of Taiwan’s first AI Academy, initiated by scholars at Academia Sinica (see also Lin 2018). According to the Ministry of Foreign Affairs “[t]he academy has drawn faculty from scholarly institutions ranging from Taiwan’s major universities to foreign research institutes, Academia Sinica and the Industrial Technology Research Institute, as well as from the corporate sphere, with AI managers and entrepreneurs coming in to share their real-world AI experience.” Further, they state that by 2020, FPG had trained over 100 workers through courses offered by the academy.
This news article (CNA 2023) focuses on a new data systrem developed by university researchers for modeling dioxin pollution in Taiwan, with Yunlin among those counties with high levels:
"EMSM is the world's first "integrated hybrid spatial estimation model" developed using geographic artificial intelligence. It uses the daily concentration of dioxins monitored by the Environmental Protection Agency's monitoring stations from 2006 to 2016 as the basis for modeling data, and uses the advantages of machine learning to integrate and stack A variety of spatial estimation methodologies are integrated to simulate the long-term, high-resolution atmospheric dioxin concentration changes in Taiwan."
"The "Integrated Hybrid Spatial Estimation Model" also shows the average concentration distribution of dioxins in Taiwan in 2015, among which Yunlin, Chiayi, Tainan, and Kaohsiung are areas with high atmospheric dioxin concentrations."
"Wu Zhida said that he will continue to study more detailed fine-grained methods, including time and space distribution presentation, to provide more detailed and accurate information, and add new algorithms and data collection to fill in the future sector forecasts as soon as possible, providing public sector, medical Unit-related information, and for the public to use practical reference and prepare for daily prevention."
From Tu (2020): "In Taiwan, the community air-monitoring projects often have difficulties in identifying the specific pollution sources due to the historical patterns of industrial development that tend to set up dense clusters of different factories in the industrial parks along the west coast (Liu 2012).3 The agglomeration of polluting facilities complicates pollution identification that further creates significant knowledge gaps between the predicted emission, the actual emission, and the community sensory experiences throughout the policy process. This pattern of development has somehow constrained Taiwan community air monitoring to target the specific polluters."