Please use this identifier to cite or link to this item:
https://rda.sliit.lk/handle/123456789/1868
Title: | lOT enabled Recognition based attendance Management System |
Authors: | Swarnakantha, N.H.P. Ravi Supunya |
Issue Date: | 2018 |
Abstract: | Attendance management is a very important task for each and every university or an institute. Most of institutes doing this attendance marking manually and it is time-consuming as well as it many causes to many errors. Therefore, r searchers tried to come up with automated attendance systems as a result of this issue. Researchers developed different systems using finger print technology, radio frequency identification (RFIO) and face recognition. Many of them used those technologies separately but it is not suitable for places like education in titutes. The purpose of the following research is to design and develop a new system using different technologies together and enable the internet of things to the system. So, this system uses face recognition and radio frequency identification t gether to come up with a proper solution. The system is using an online MySQL database to store entire data of the system. Python is used to program the system and Open CV is used for face recognition. One main finding of the research is to identify the student with different angles of face after getting the RFIO tag value. When getting attendance, the stude t should place his or her RFIO tag on the reader and then the system identifies the student with the tag value. The system then retrieves student's registration details and start compare student's face with sa$faces of that student. If the system identifies the student, then it checks for the subject's time slot to ensure that the student comes to the correct class. If all of them are correct, the system marks attendance for the student and sends a .notification email to the student so the student can know his or her attendance marked successfully for the class. There IS a web application also developed to register courses and subjects on the system and to view attendance details |
URI: | http://rda.sliit.lk/handle/123456789/1868 |
Appears in Collections: | 2018 MSc. in IT |
Files in This Item:
File | Description | Size | Format | |
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IOT enabled_merged.pdf | 5.89 MB | Adobe PDF | View/Open |
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