INTERNET OF THINGS (IOT) BASED ADVANCED ONLINE EXAMINATION USING RASPBERRY PI

  • Mr.KunalS.Pawar E&TC, Sinhgad Institute of Technology Lonavala, India
  • Prof.Pravin C. Latane E&TC, Sinhgad Institute of Technology Lonavala, India
Keywords: Facial Recognition, Facial Identification, Neural Network Classification, PIR Sensor, Raspberry Pi.

Abstract

In this research we have proposed IOT based advanced Online examination using Raspberry pi for Alarm system and border security. With the event of recent education, considering the defect of current online exam system, a replacement projection of online exam system primarily based on Raspberry pi IOT is projected, and also the key implementation techniques and ways also are represented. Internet of Things (IOT) has provided a promising chance to make powerful Examination systems and applications by leverage the growing omnipresence of wireless, RFID mobile and detector devices. a large vary of IOT applications are developed in recent years. In a shot to grasp the event of IOT in on-line examination, here we tend to propose this analysis of IOT, IOT key facultative technologies, major IOT applications in on-line examination and identifies analysis trends and challenges. Here we tend to introduce all the examiner details square measure holds on within the server. Then if somebody needs to starts on-line examination, 1st they ought to apply face recognition (in Open CV based) technique. as a result of it slow unwanted person conjointly enter to Wright the examination, thus this can be the simplest thanks to known any culprits square measure found or not. Then examination enter to Wright the exam, here conjointly I am apply some security. Currently a day’s already queries square measure hold on within the on-line or any paper written copy.

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References

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Published
2018-05-31
How to Cite
Pawar, K., & Latane, P. (2018). INTERNET OF THINGS (IOT) BASED ADVANCED ONLINE EXAMINATION USING RASPBERRY PI . International Journal of Engineering Technologies and Management Research, 5(5), 26-32. https://doi.org/10.29121/ijetmr.v5.i5.2018.223