{"title":"车辆故障检测的大遥测数据分析","authors":"J. Zdravković, N. Ilić, D. Stojanović","doi":"10.1109/TELSIKS52058.2021.9606415","DOIUrl":null,"url":null,"abstract":"Monitoring the correctness of vehicles in modern traffic is very difficult, considering that the condition of a vehicle is constantly changing due to driving and requires constant checking of various parameters. Systems that would deal with this would have to be accurate in their estimates and very fast given that vehicles constantly generate a large amount of data. A Vehicle Fault Detection system has been proposed as a solution to this problem. The system is distributed and autonomous and uses linear regression as a classifier. The proposed solution was implemented and tested and detailed performance and accuracy analysis were performed.","PeriodicalId":228464,"journal":{"name":"2021 15th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Big Telemetry Data Analytics for Vehicle Fault Detection\",\"authors\":\"J. Zdravković, N. Ilić, D. Stojanović\",\"doi\":\"10.1109/TELSIKS52058.2021.9606415\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Monitoring the correctness of vehicles in modern traffic is very difficult, considering that the condition of a vehicle is constantly changing due to driving and requires constant checking of various parameters. Systems that would deal with this would have to be accurate in their estimates and very fast given that vehicles constantly generate a large amount of data. A Vehicle Fault Detection system has been proposed as a solution to this problem. The system is distributed and autonomous and uses linear regression as a classifier. The proposed solution was implemented and tested and detailed performance and accuracy analysis were performed.\",\"PeriodicalId\":228464,\"journal\":{\"name\":\"2021 15th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS)\",\"volume\":\"140 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 15th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TELSIKS52058.2021.9606415\",\"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 15th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TELSIKS52058.2021.9606415","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Big Telemetry Data Analytics for Vehicle Fault Detection
Monitoring the correctness of vehicles in modern traffic is very difficult, considering that the condition of a vehicle is constantly changing due to driving and requires constant checking of various parameters. Systems that would deal with this would have to be accurate in their estimates and very fast given that vehicles constantly generate a large amount of data. A Vehicle Fault Detection system has been proposed as a solution to this problem. The system is distributed and autonomous and uses linear regression as a classifier. The proposed solution was implemented and tested and detailed performance and accuracy analysis were performed.