{"title":"基于简单运动传感器阵列的运动目标室内位置估计","authors":"Ryo Ota, T. Hanyu, Qiangfu Zhao","doi":"10.1109/ICAwST.2019.8923162","DOIUrl":null,"url":null,"abstract":"The purpose of this study is to estimate human location in a room while protecting privacy. Our previous studies have revealed that a sensor array containing several infrared sensors could recognize human locations and preserve privacy. However, the previous location estimations were conducted on stationary human locations. In this paper, we aim to make the estimation more realistic and to estimate and track the locations of a walking person. That is, we want to estimate two functions x(D) and y(D) based on the observed sensor data D, where (x, y) is the coordinate of the location. Experimental results show that the estimated locations follow the real human locations very well even though we do not use the correlation between frames. This also implies that \"tracking\" is possible using a relatively small and sparse sensor array.","PeriodicalId":156538,"journal":{"name":"2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Indoor Location Estimation of a Moving Subject Based on a Simple Motion Sensor Array\",\"authors\":\"Ryo Ota, T. Hanyu, Qiangfu Zhao\",\"doi\":\"10.1109/ICAwST.2019.8923162\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The purpose of this study is to estimate human location in a room while protecting privacy. Our previous studies have revealed that a sensor array containing several infrared sensors could recognize human locations and preserve privacy. However, the previous location estimations were conducted on stationary human locations. In this paper, we aim to make the estimation more realistic and to estimate and track the locations of a walking person. That is, we want to estimate two functions x(D) and y(D) based on the observed sensor data D, where (x, y) is the coordinate of the location. Experimental results show that the estimated locations follow the real human locations very well even though we do not use the correlation between frames. This also implies that \\\"tracking\\\" is possible using a relatively small and sparse sensor array.\",\"PeriodicalId\":156538,\"journal\":{\"name\":\"2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST)\",\"volume\":\"103 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAwST.2019.8923162\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAwST.2019.8923162","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Indoor Location Estimation of a Moving Subject Based on a Simple Motion Sensor Array
The purpose of this study is to estimate human location in a room while protecting privacy. Our previous studies have revealed that a sensor array containing several infrared sensors could recognize human locations and preserve privacy. However, the previous location estimations were conducted on stationary human locations. In this paper, we aim to make the estimation more realistic and to estimate and track the locations of a walking person. That is, we want to estimate two functions x(D) and y(D) based on the observed sensor data D, where (x, y) is the coordinate of the location. Experimental results show that the estimated locations follow the real human locations very well even though we do not use the correlation between frames. This also implies that "tracking" is possible using a relatively small and sparse sensor array.