IoT Based Automated Attendance with Face Recognition System
D. Narendar Singh1, M. Kusuma Sri2, K. Mounika3
1D.Narendar Singh, Department of ECE, Anurag Group of Institutions Hyderabad (Telangana), India.
2M.Kusuma Sri, Department of ECE, Anurag Group of Institutions Hyderabad (Telangana), India.
3K.Mounika, Department of ECE, Anurag Group of Institutions Hyderabad (Telangana), India.
Manuscript received on 13 December 2018 | Revised Manuscript received on 22 December 2018 | Manuscript Published on 30 December 2018 | PP: 372-377 | Volume-8 Issue-2S, December 2018 | Retrieval Number: 100.1/ijeat.B10761282S18/18©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Our Paper involves the student attendance and faculty attendance. The student attendance is marked by face recognition. For face detection and face recognition the raspberry pi. If the camera is connected to Raspberry pi USB port then only images will capture of the students who are available in the class for face detection. The captured images recognises with stored images then in that images we will recognize the faces of every student and according to that attendance will be given to that subject class. This process is carried out for every class and students are given attendance accordingly. Faculty attendance is monitored with this project. A unique RFID card is given to the faculty, when faculty enters the classroom swipes the RFID card attendance will be marked with date and time. ESP8266 is used along with OLED to display the faculty attendance. We can mark the attendance at any time without any human Intervention.
Keywords: Student Attendance, Raspberry Pi, Camera, Face Detection, Face Recognition, Image Processing, Open CV, Python, Faculty Attendance, ESP8266, OLED.
Scope of the Article: IoT