Abstract

Internet of Things based Automatic Attendance Management systems that use Artificial Intelligent cameras and deep learning algorithms can suggestively advance the accuracy and proficiency of class presence following in schools, colleges as well as universities. This technology involves the use of cameras that are placed in classrooms or other areas where attendance needs to be monitored.The cameras are equipped with advanced deep learning algorithms that can detect and recognize students based on their unique facial features. These algorithms use machine learning techniques to analyse images and identify individual faces, even in varying lighting conditions and different angles.The data collected by the cameras is then transmitted to an Intenet of Things based platform, which stores and approach the attendance data in real time. This platform can also be used to generate reports and analytics on attendance, helping teachers and administrators make data driven decisions to improve student performance.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.