{"title":"基于物联网中间件的协同感知隐私保护步态跟踪","authors":"C. Shih, Tim-Yuao Wang, Jyun-Jhe Chou, Ze-Yu Chuang, Ching-Chih Chuang, Kwei-Jay Lin, Wei-Dean Wang, Kuo-Chin Huang","doi":"10.1145/3129676.3129696","DOIUrl":null,"url":null,"abstract":"Gait velocity has become a valid and important metric for senior populations. However, existing approaches to measure gait velocity are either limited to specific location or too expensive to be applied. IoT middleware allows the systems to collect data in a large space in a collaborative manner. However, it is a great challenge of integrating large numbers of low-cost devices to accomplish the task. This paper presents the design, implementation, and findings of using low-cost thermal sensors to monitor the activity index in home environment. The system is built on top of WuKong middleware. The evaluation results show that the system can measure the gait velocity with negligible errors. When the parameters for noise filtering are correctly configured, the F-Score of the heat source detection can achieve 0.99.","PeriodicalId":326100,"journal":{"name":"Proceedings of the International Conference on Research in Adaptive and Convergent Systems","volume":"151 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Collaborative Sensing for Privacy Preserving Gait Tracking Using IoT Middleware\",\"authors\":\"C. Shih, Tim-Yuao Wang, Jyun-Jhe Chou, Ze-Yu Chuang, Ching-Chih Chuang, Kwei-Jay Lin, Wei-Dean Wang, Kuo-Chin Huang\",\"doi\":\"10.1145/3129676.3129696\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Gait velocity has become a valid and important metric for senior populations. However, existing approaches to measure gait velocity are either limited to specific location or too expensive to be applied. IoT middleware allows the systems to collect data in a large space in a collaborative manner. However, it is a great challenge of integrating large numbers of low-cost devices to accomplish the task. This paper presents the design, implementation, and findings of using low-cost thermal sensors to monitor the activity index in home environment. The system is built on top of WuKong middleware. The evaluation results show that the system can measure the gait velocity with negligible errors. When the parameters for noise filtering are correctly configured, the F-Score of the heat source detection can achieve 0.99.\",\"PeriodicalId\":326100,\"journal\":{\"name\":\"Proceedings of the International Conference on Research in Adaptive and Convergent Systems\",\"volume\":\"151 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the International Conference on Research in Adaptive and Convergent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3129676.3129696\",\"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 Research in Adaptive and Convergent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3129676.3129696","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Collaborative Sensing for Privacy Preserving Gait Tracking Using IoT Middleware
Gait velocity has become a valid and important metric for senior populations. However, existing approaches to measure gait velocity are either limited to specific location or too expensive to be applied. IoT middleware allows the systems to collect data in a large space in a collaborative manner. However, it is a great challenge of integrating large numbers of low-cost devices to accomplish the task. This paper presents the design, implementation, and findings of using low-cost thermal sensors to monitor the activity index in home environment. The system is built on top of WuKong middleware. The evaluation results show that the system can measure the gait velocity with negligible errors. When the parameters for noise filtering are correctly configured, the F-Score of the heat source detection can achieve 0.99.