{"title":"基于AI引导雾霾图像识别算法的大气污染智能控制效果评价","authors":"Jinpeng Guo, Ting Xu","doi":"10.1109/ICOEI51242.2021.9452967","DOIUrl":null,"url":null,"abstract":"Effectiveness evaluation of air pollution intelligent control based on AI guided haze image identification algorithm is conducted in this paper. Firstly, we choose median filter to denoise the image, choose the global fog image enhancement method to enhance the image, and segment the image through the Gaussian mixture model algorithm based on spatio-temporal information. Secondly, the novel AI system is designed for the implementations of the environment sensing framework that can collect the data, pre-process the data and finally extract the overall information for analysis. Lastly, the intelligent control system is desinged and implemented. Reflecting from the simulation results, the proposed monitoring system can comprehensively analysis the data well.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effectiveness Evaluation of Air Pollution Intelligent Control Based on AI Guided Haze Image Identification Algorithm\",\"authors\":\"Jinpeng Guo, Ting Xu\",\"doi\":\"10.1109/ICOEI51242.2021.9452967\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Effectiveness evaluation of air pollution intelligent control based on AI guided haze image identification algorithm is conducted in this paper. Firstly, we choose median filter to denoise the image, choose the global fog image enhancement method to enhance the image, and segment the image through the Gaussian mixture model algorithm based on spatio-temporal information. Secondly, the novel AI system is designed for the implementations of the environment sensing framework that can collect the data, pre-process the data and finally extract the overall information for analysis. Lastly, the intelligent control system is desinged and implemented. Reflecting from the simulation results, the proposed monitoring system can comprehensively analysis the data well.\",\"PeriodicalId\":420826,\"journal\":{\"name\":\"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOEI51242.2021.9452967\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOEI51242.2021.9452967","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Effectiveness Evaluation of Air Pollution Intelligent Control Based on AI Guided Haze Image Identification Algorithm
Effectiveness evaluation of air pollution intelligent control based on AI guided haze image identification algorithm is conducted in this paper. Firstly, we choose median filter to denoise the image, choose the global fog image enhancement method to enhance the image, and segment the image through the Gaussian mixture model algorithm based on spatio-temporal information. Secondly, the novel AI system is designed for the implementations of the environment sensing framework that can collect the data, pre-process the data and finally extract the overall information for analysis. Lastly, the intelligent control system is desinged and implemented. Reflecting from the simulation results, the proposed monitoring system can comprehensively analysis the data well.
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