{"title":"使用图形布局可视化Wi-Fi接入点测量和位置数据","authors":"R. Guinness, José M. Vallet García","doi":"10.1109/EURONAV.2017.7954225","DOIUrl":null,"url":null,"abstract":"Building and maintaining a database of Wi-Fi measurements in order to enable global WLAN-based positioning is a challenging and costly task, one whose cost can be minimized by crowdsourcing measurements from mobile phone users. Nonetheless, crowdsourcing Wi-Fi measurements poses a number of challenges, including the sheer size of data one must process and manage. In this paper, we present methods aimed at visualizing a large dataset of Wi-Fi signal strength measurements (n ≈ 2.3 × 106). Some of the measurements include associated location data, whereas a large number do not. This situation led us to represent the data as a graph, capturing the inherent spatial structure of Wi-Fi scan data. We define a subset of Access Points (APs) as “anchor nodes” and estimate their positions using a generalized least squares (GLS) estimator. We then employ a force-directed graph layout algorithm to lay-out the remaining APs in relation to the anchor nodes. The resulting graph layout provides a visualization of the entire dataset, which is inherently useful for further investigations, such as identifying where future data collection campaigns should be targeted.","PeriodicalId":145124,"journal":{"name":"2017 European Navigation Conference (ENC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Visualizing Wi-Fi Access Point measurements and location data using graph layouts\",\"authors\":\"R. Guinness, José M. Vallet García\",\"doi\":\"10.1109/EURONAV.2017.7954225\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Building and maintaining a database of Wi-Fi measurements in order to enable global WLAN-based positioning is a challenging and costly task, one whose cost can be minimized by crowdsourcing measurements from mobile phone users. Nonetheless, crowdsourcing Wi-Fi measurements poses a number of challenges, including the sheer size of data one must process and manage. In this paper, we present methods aimed at visualizing a large dataset of Wi-Fi signal strength measurements (n ≈ 2.3 × 106). Some of the measurements include associated location data, whereas a large number do not. This situation led us to represent the data as a graph, capturing the inherent spatial structure of Wi-Fi scan data. We define a subset of Access Points (APs) as “anchor nodes” and estimate their positions using a generalized least squares (GLS) estimator. We then employ a force-directed graph layout algorithm to lay-out the remaining APs in relation to the anchor nodes. The resulting graph layout provides a visualization of the entire dataset, which is inherently useful for further investigations, such as identifying where future data collection campaigns should be targeted.\",\"PeriodicalId\":145124,\"journal\":{\"name\":\"2017 European Navigation Conference (ENC)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 European Navigation Conference (ENC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EURONAV.2017.7954225\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 European Navigation Conference (ENC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EURONAV.2017.7954225","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Visualizing Wi-Fi Access Point measurements and location data using graph layouts
Building and maintaining a database of Wi-Fi measurements in order to enable global WLAN-based positioning is a challenging and costly task, one whose cost can be minimized by crowdsourcing measurements from mobile phone users. Nonetheless, crowdsourcing Wi-Fi measurements poses a number of challenges, including the sheer size of data one must process and manage. In this paper, we present methods aimed at visualizing a large dataset of Wi-Fi signal strength measurements (n ≈ 2.3 × 106). Some of the measurements include associated location data, whereas a large number do not. This situation led us to represent the data as a graph, capturing the inherent spatial structure of Wi-Fi scan data. We define a subset of Access Points (APs) as “anchor nodes” and estimate their positions using a generalized least squares (GLS) estimator. We then employ a force-directed graph layout algorithm to lay-out the remaining APs in relation to the anchor nodes. The resulting graph layout provides a visualization of the entire dataset, which is inherently useful for further investigations, such as identifying where future data collection campaigns should be targeted.