IoT Enabled Real Time Appearance System using AI Camera and Deep Learning for Student Tracking

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Published: Jun 10, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i6s.6885
Keywords:
internet of things, deep learning, artificial intelligent, image prosessing

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Pushpendra Kumar Verma
Associate Professor, School of Computer Science and Application, IIMT University, Meerut, Uttar Pradesh, India-250001
Vikas Sharma
Assistant Professor, School of Computer Science and Application, IIMT University, Meerut, Uttar Pradesh, India-250001
Prashant Kumar
Assistant Professor, School of Computer Science and Application, IIMT University, Meerut, Uttar Pradesh, India-250001
Shashank Sharma
Assistant Professor, School of Computer Science and Application, IIMT University, Meerut, Uttar Pradesh, India-250001
Sachin Chaudhary
Assistant Professor, School of Computer Science and Application, IIMT University, Meerut, Uttar Pradesh, India-250001
Preety
Assistant Professor, Faculty of Management, Swami Vivekanand Subharti University, Meerut ,Uttar Pradesh, India-25002

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.

Article Details

How to Cite
Verma, P. K. ., Sharma, V. ., Kumar, P. ., Sharma, S. ., Chaudhary, S. ., & Preety, P. (2023). IoT Enabled Real Time Appearance System using AI Camera and Deep Learning for Student Tracking. International Journal on Recent and Innovation Trends in Computing and Communication, 11(6s), 249–254. https://doi.org/10.17762/ijritcc.v11i6s.6885
Issue
Vol. 11 No. 6s (2023): Advances in Computational Modeling and Simulation of Computing Systems
Section
Articles

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