Open AccessSmart Iot-Based Latecomer / Defaulter Prediction System For Educational Institutions
Author(s) -
S. Amutha,
G. Ananthi,
J. Raja Sekar
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1362/1/012106
Subject(s) - computer science , process (computing) , identification (biology) , object (grammar) , automation , track (disk drive) , internet of things , multimedia , real time computing , computer security , artificial intelligence , operating system , engineering , botany , biology , mechanical engineering
In current scenario, educational institutions insist the learners to be punctual. Usually students who are late to their classes are being monitored manually. It is not feasible to monitor regularly since there is a need for manpower at a particular time to register the students those who are late. In such cases there is a need for an automated system to monitor the late comers. This is implemented by acquiring input information from sensors. Passive Infrared Sensor is used to detect the motion of the object whereas RFID is used to retrieve the student details which can be mapped from their unique Id. Along with this, a camera module is used to capture the images of the unidentified entries those does not wear ID cards. The activation of the monitoring system can be customized with the help of the application deployed at a local server. The system can be made active in particular duration with the various time specified. As part of the automation process, an alert mail will reach the respective authority with the list of latecomers and the images those who are unidentified by RFID. By these methods the identification of the late comers will be automated and makes an easier way to track the late comers.