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MMAP: A Multi-Modal Automated Online Proctor

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Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021) (ICMLBDA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 256))

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Abstract

With the surge in online education, more universities have shifted classes online. The growing popularity of MOOC courses and the changing education landscape could mean more and more people switching to online education. A primary drawback is the difficulty in monitoring of students during an online examination which leads to a lot of malpractices used by candidates. This paper explores computer vision based techniques to propose a five-fold proctoring mechanism for online tests. The features incorporated are authentication, head movement, eye motion tracking, speech detection and object detection. The solution has an overall accuracy of 91% accuracy.

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Authors and Affiliations

  1. Department of Computer Engineering, Sardar Patel Institute of Technology, Mumbai, India

    Aumkar Gadekar, Shreya Oak, Abhishek Revadekar & Anant V. Nimkar

Authors
  1. Aumkar Gadekar
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  2. Shreya Oak
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  3. Abhishek Revadekar
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  4. Anant V. Nimkar
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Corresponding author

Correspondence to Aumkar Gadekar .

Editor information

Editors and Affiliations

  1. Indian Institute of Technology Patna, Patna, India

    Rajiv Misra

  2. Indian Institute of Technology Bombay, Mumbai, India

    Rudrapatna K. Shyamasundar

  3. Indian Institute of Technology (BHU), Varanasi, India

    Amrita Chaturvedi

  4. Cardiff University, Cardiff, UK

    Rana Omer

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Gadekar, A., Oak, S., Revadekar, A., Nimkar, A.V. (2022). MMAP: A Multi-Modal Automated Online Proctor. In: Misra, R., Shyamasundar, R.K., Chaturvedi, A., Omer, R. (eds) Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021). ICMLBDA 2021. Lecture Notes in Networks and Systems, vol 256. Springer, Cham. https://doi.org/10.1007/978-3-030-82469-3_28

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