The technological evolution and recent advances in machine learning have transformed how ordinary tasks are performed. Due to many technological, cultural and health related changes (such as Covid 19 pandemic), the means for managing attendance has been transformed with Internet of Things (IoT) based technologies. Attendance management system (AMS) is a system that documents and keeps track of employee and student hours and stores them on local repository or in the cloud. Manual approach to recording and keeping track of attendance is prone to human errors and time consuming. Although many studies have proposed new IoT biometric based solutions to enhance this process, achieving accuracy, efficiency and expense affordability can be a challenging task. The most used biometric approach recently is face recognition IoT solutions. Face recognition can be challenging during the Covid 19 pandemic because of face masks. Taking these issues into consideration, we propose a GPS-enabled Iris-based biometric approach for the attendance management system with smartwatches' compatibility feature. The system performs two main tasks: identification and real time localization. The identification is achieved with iris-based identification while localization is using GPS technology and smart watches. The proposed system addresses many fundamental issues such as the expense factors of manufacturing dedicated tracking wearable devices. It also provides an efficient means of identification using iris-based biometric identification which provides many advantages such as accuracy and enhanced friendly experience without relying on face recognition. The proposed IoT Attendance management systems will be designed to provide better automation for managing attendance and reduce many human errors resulting from manual approaches. © 2021 ACM.
IoT based Attendance Management System (AMS) with Smartwatches Compatibility