{"title":"基于物联网的智能系统推荐合适的环境","authors":"M. Hasan, Anika Nawar, M. H. Khan, Lafifa Jamal","doi":"10.1145/3449301.3449329","DOIUrl":null,"url":null,"abstract":"The demand for a smart monitoring system has been increased to reduce the impact of environmental pollution. In this paper, a smart system has been proposed that includes an IoT device which can monitor the pollution and explosion level of the septic tanks as well as the surroundings. The system can detect whether a particular area is environment friendly or not. A notification system has been designed that notifies the respective individual when there exists any risk factor in the environment. The proposed design has been compared with existing approaches. The proposed system has 93.78% accuracy, 95.68% precision, and 96.52 % recall. It shows 6.11%, 3.37%, and 1.84% improvement in terms of accuracy, precision, and recall respectively over the best existing approach.","PeriodicalId":429684,"journal":{"name":"Proceedings of the 6th International Conference on Robotics and Artificial Intelligence","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An IoT Based Smart System to Recommend Suitable Environment\",\"authors\":\"M. Hasan, Anika Nawar, M. H. Khan, Lafifa Jamal\",\"doi\":\"10.1145/3449301.3449329\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The demand for a smart monitoring system has been increased to reduce the impact of environmental pollution. In this paper, a smart system has been proposed that includes an IoT device which can monitor the pollution and explosion level of the septic tanks as well as the surroundings. The system can detect whether a particular area is environment friendly or not. A notification system has been designed that notifies the respective individual when there exists any risk factor in the environment. The proposed design has been compared with existing approaches. The proposed system has 93.78% accuracy, 95.68% precision, and 96.52 % recall. It shows 6.11%, 3.37%, and 1.84% improvement in terms of accuracy, precision, and recall respectively over the best existing approach.\",\"PeriodicalId\":429684,\"journal\":{\"name\":\"Proceedings of the 6th International Conference on Robotics and Artificial Intelligence\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 6th International Conference on Robotics and Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3449301.3449329\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Robotics and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3449301.3449329","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An IoT Based Smart System to Recommend Suitable Environment
The demand for a smart monitoring system has been increased to reduce the impact of environmental pollution. In this paper, a smart system has been proposed that includes an IoT device which can monitor the pollution and explosion level of the septic tanks as well as the surroundings. The system can detect whether a particular area is environment friendly or not. A notification system has been designed that notifies the respective individual when there exists any risk factor in the environment. The proposed design has been compared with existing approaches. The proposed system has 93.78% accuracy, 95.68% precision, and 96.52 % recall. It shows 6.11%, 3.37%, and 1.84% improvement in terms of accuracy, precision, and recall respectively over the best existing approach.