{"title":"入侵者监控系统中高度滤波的几何算法","authors":"Jaeseok Shim, Yujin Lim, Jaesung Park","doi":"10.1109/ICOIN.2014.6799667","DOIUrl":null,"url":null,"abstract":"Wireless Sensor Network (WSN) has been used for monitoring applications. However, due to the limitation of resources, efficient management of the large volume of sensor data is an important issue to deal with. In recent years, cloud computing has emerged as a new computing paradigm to provide reliable resources, software, and data on demand. It integrates its lots of resources into WSNs to innovate a number of new services. In this paper, we design an intruder monitoring system on top of a cloud platform. In the system, we propose a geometric algorithm for semantic filtering in order to remove meaningless data and reduce the volume of data stored in cloud storages. Through experiments in various environments, we show the performance of our algorithm.","PeriodicalId":388486,"journal":{"name":"The International Conference on Information Networking 2014 (ICOIN2014)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Geometric algorithm for height filtering in intruder monitoring system\",\"authors\":\"Jaeseok Shim, Yujin Lim, Jaesung Park\",\"doi\":\"10.1109/ICOIN.2014.6799667\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wireless Sensor Network (WSN) has been used for monitoring applications. However, due to the limitation of resources, efficient management of the large volume of sensor data is an important issue to deal with. In recent years, cloud computing has emerged as a new computing paradigm to provide reliable resources, software, and data on demand. It integrates its lots of resources into WSNs to innovate a number of new services. In this paper, we design an intruder monitoring system on top of a cloud platform. In the system, we propose a geometric algorithm for semantic filtering in order to remove meaningless data and reduce the volume of data stored in cloud storages. Through experiments in various environments, we show the performance of our algorithm.\",\"PeriodicalId\":388486,\"journal\":{\"name\":\"The International Conference on Information Networking 2014 (ICOIN2014)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The International Conference on Information Networking 2014 (ICOIN2014)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOIN.2014.6799667\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The International Conference on Information Networking 2014 (ICOIN2014)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOIN.2014.6799667","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Geometric algorithm for height filtering in intruder monitoring system
Wireless Sensor Network (WSN) has been used for monitoring applications. However, due to the limitation of resources, efficient management of the large volume of sensor data is an important issue to deal with. In recent years, cloud computing has emerged as a new computing paradigm to provide reliable resources, software, and data on demand. It integrates its lots of resources into WSNs to innovate a number of new services. In this paper, we design an intruder monitoring system on top of a cloud platform. In the system, we propose a geometric algorithm for semantic filtering in order to remove meaningless data and reduce the volume of data stored in cloud storages. Through experiments in various environments, we show the performance of our algorithm.