{"title":"Indoor Positioning Using WiFi Fingerprint","authors":"R. Joseph, Swapna Sasi","doi":"10.1109/ICCSDET.2018.8821184","DOIUrl":null,"url":null,"abstract":"Indoor Positioning System helps to locate, monitor and track the devices using the radio signals. This can be used to find the people who are trapped inside a building. Outdoor localization problems can be solved by using Global Positioning System (GPS). Since GPS signals are lost inside the buildings, Indoor Positioning still remains a problem. This paper provides a technique for indoor positioning by using WiFi fingerprint. The intensity of the received signal is measured and is stored in a database. The database consists of the list of signal strength and their corresponding locations. The similarity of the signal detected and those stored in the database can used to detect the position of the user. The prevailing WiFi infrastructure can be used for this purpose. We use deep neural network with stacked autoencoders to determine the floor and building. The classifier is used to detect the building and the floor level .","PeriodicalId":157362,"journal":{"name":"2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)","volume":"214 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSDET.2018.8821184","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
Indoor Positioning System helps to locate, monitor and track the devices using the radio signals. This can be used to find the people who are trapped inside a building. Outdoor localization problems can be solved by using Global Positioning System (GPS). Since GPS signals are lost inside the buildings, Indoor Positioning still remains a problem. This paper provides a technique for indoor positioning by using WiFi fingerprint. The intensity of the received signal is measured and is stored in a database. The database consists of the list of signal strength and their corresponding locations. The similarity of the signal detected and those stored in the database can used to detect the position of the user. The prevailing WiFi infrastructure can be used for this purpose. We use deep neural network with stacked autoencoders to determine the floor and building. The classifier is used to detect the building and the floor level .