{"title":"Smarttendance: A BLE-Based Mobile Application for Real-Time Session Attendance Tracking","authors":"Vladimir Pleština;Luka Munivrana;Sven Gotovac","doi":"10.1109/JRFID.2026.3680246","DOIUrl":null,"url":null,"abstract":"Tracking attendance in organized sessions is a crucial but time-consuming task in many institutional and professional environments. Traditional methods, such as manual roll calls or paper-based sign-ins, are inefficient, error-prone, and difficult to scale. This paper presents Smarttendance, an automated attendance tracking system that leverages Bluetooth Low Energy (BLE) technology and mobile applications to verify participant presence in real time. The system enables a session coordinator to scan for nearby participants whose mobile devices broadcast anonymized unique identifiers, significantly reducing administrative overhead while improving accuracy and transparency. Developed using Flutter and Dart, Smarttendance offers cross-platform compatibility, currently supports Android devices and is architected for future compatibility with iOS. A dedicated backend infrastructure supports secure identity management and real-time attendance data storage. Experimental evaluation conducted across multiple physical scenarios — including line-of-sight conditions in a <inline-formula> <tex-math>$6\\times 10$ </tex-math></inline-formula> m classroom, detection through a Ytong block wall, and detection with devices enclosed in a wooden cabinet — demonstrates 100% detection success across all conditions (<inline-formula> <tex-math>$n = 20$ </tex-math></inline-formula> per condition), with mean detection latencies ranging from 294 ms to 1125 ms depending on environmental factors. The proposed solution is energy-efficient, utilizing BLE’s low-power communication model to minimize device battery consumption while maintaining reliable detection accuracy.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"10 ","pages":"444-455"},"PeriodicalIF":3.7000,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11473285","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE journal of radio frequency identification","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/11473285/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/4/2 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Tracking attendance in organized sessions is a crucial but time-consuming task in many institutional and professional environments. Traditional methods, such as manual roll calls or paper-based sign-ins, are inefficient, error-prone, and difficult to scale. This paper presents Smarttendance, an automated attendance tracking system that leverages Bluetooth Low Energy (BLE) technology and mobile applications to verify participant presence in real time. The system enables a session coordinator to scan for nearby participants whose mobile devices broadcast anonymized unique identifiers, significantly reducing administrative overhead while improving accuracy and transparency. Developed using Flutter and Dart, Smarttendance offers cross-platform compatibility, currently supports Android devices and is architected for future compatibility with iOS. A dedicated backend infrastructure supports secure identity management and real-time attendance data storage. Experimental evaluation conducted across multiple physical scenarios — including line-of-sight conditions in a $6\times 10$ m classroom, detection through a Ytong block wall, and detection with devices enclosed in a wooden cabinet — demonstrates 100% detection success across all conditions ($n = 20$ per condition), with mean detection latencies ranging from 294 ms to 1125 ms depending on environmental factors. The proposed solution is energy-efficient, utilizing BLE’s low-power communication model to minimize device battery consumption while maintaining reliable detection accuracy.