Sunny Verma, Tej Raj, K. Joshi, Preeti Raturi, Harishchander Anandaram, Ashulekha Gupta
{"title":"Indoor Real-Time Location System for Efficient Location Tracking Using IoT","authors":"Sunny Verma, Tej Raj, K. Joshi, Preeti Raturi, Harishchander Anandaram, Ashulekha Gupta","doi":"10.1109/AIC55036.2022.9848912","DOIUrl":null,"url":null,"abstract":"Researchers have broadened the focus of RFID technology development because to the growing need for low-cost edge devices to bridge the physical-digital gap. In addition to item identification, researchers have explored the use of RFID tags for low-power wireless sensing, localization, and activity inference. A security system utilized today is not powerful enough to provide a real-time alert after identifying a problem. Movement detection is a technology for detecting a change in the environment relative to an object. Sensor-based applications can be used to watch activity and receive alerts when movement is detected, which solves the issue and saves time and money. RFID technology is used to track the location of people or things in an interior setting in real time. A reader and several tags, each of which can house a number of sensors, make up an RFID system. In this research, we present the iLocate framework for the IoT, a recently developed real-time locating framework using dynamic RFID for resource the board in indoor settings. iLocate used ubidots to assist with a broad range RFID organization. Our exploratory findings and the actual project have both shown the prevalence. Location tracking indoors will be more effective using this iLocate framework.","PeriodicalId":433590,"journal":{"name":"2022 IEEE World Conference on Applied Intelligence and Computing (AIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE World Conference on Applied Intelligence and Computing (AIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIC55036.2022.9848912","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Researchers have broadened the focus of RFID technology development because to the growing need for low-cost edge devices to bridge the physical-digital gap. In addition to item identification, researchers have explored the use of RFID tags for low-power wireless sensing, localization, and activity inference. A security system utilized today is not powerful enough to provide a real-time alert after identifying a problem. Movement detection is a technology for detecting a change in the environment relative to an object. Sensor-based applications can be used to watch activity and receive alerts when movement is detected, which solves the issue and saves time and money. RFID technology is used to track the location of people or things in an interior setting in real time. A reader and several tags, each of which can house a number of sensors, make up an RFID system. In this research, we present the iLocate framework for the IoT, a recently developed real-time locating framework using dynamic RFID for resource the board in indoor settings. iLocate used ubidots to assist with a broad range RFID organization. Our exploratory findings and the actual project have both shown the prevalence. Location tracking indoors will be more effective using this iLocate framework.