{"title":"存在分析:利用WLAN数字印记发现人类存在的有意义模式","authors":"M. H. S. Eldaw, M. Levene, George Roussos","doi":"10.1145/2896387.2896438","DOIUrl":null,"url":null,"abstract":"In this paper we illustrates how aggregated WLAN activity traces provide anonymous information that reveals invaluable insight into human presence within a university campus. We show how technologies supporting pervasive services, such as WLAN, which have the potential to generate vast amounts of detailed information, provide an invaluable opportunity to understand the presence and movement of people within such an environment. We demonstrate how these aggregated mobile network traces offer the opportunity for human presence analytics in several dimensions: social, spatial, temporal and semantic dimensions. These analytics have real potential to support human mobility studies such as the optimisation of space use strategies. The analytics presented in this paper are based on recent WLAN traces collected at Birkbeck College of University of London, one of the participants in the Eduroam network.","PeriodicalId":342210,"journal":{"name":"Proceedings of the International Conference on Internet of things and Cloud Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Presence Analytics: Discovering Meaningful Patterns about Human Presence Using WLAN Digital Imprints\",\"authors\":\"M. H. S. Eldaw, M. Levene, George Roussos\",\"doi\":\"10.1145/2896387.2896438\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we illustrates how aggregated WLAN activity traces provide anonymous information that reveals invaluable insight into human presence within a university campus. We show how technologies supporting pervasive services, such as WLAN, which have the potential to generate vast amounts of detailed information, provide an invaluable opportunity to understand the presence and movement of people within such an environment. We demonstrate how these aggregated mobile network traces offer the opportunity for human presence analytics in several dimensions: social, spatial, temporal and semantic dimensions. These analytics have real potential to support human mobility studies such as the optimisation of space use strategies. The analytics presented in this paper are based on recent WLAN traces collected at Birkbeck College of University of London, one of the participants in the Eduroam network.\",\"PeriodicalId\":342210,\"journal\":{\"name\":\"Proceedings of the International Conference on Internet of things and Cloud Computing\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the International Conference on Internet of things and Cloud Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2896387.2896438\",\"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 International Conference on Internet of things and Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2896387.2896438","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Presence Analytics: Discovering Meaningful Patterns about Human Presence Using WLAN Digital Imprints
In this paper we illustrates how aggregated WLAN activity traces provide anonymous information that reveals invaluable insight into human presence within a university campus. We show how technologies supporting pervasive services, such as WLAN, which have the potential to generate vast amounts of detailed information, provide an invaluable opportunity to understand the presence and movement of people within such an environment. We demonstrate how these aggregated mobile network traces offer the opportunity for human presence analytics in several dimensions: social, spatial, temporal and semantic dimensions. These analytics have real potential to support human mobility studies such as the optimisation of space use strategies. The analytics presented in this paper are based on recent WLAN traces collected at Birkbeck College of University of London, one of the participants in the Eduroam network.