skip to main content
10.1145/3274005.3274014acmotherconferencesArticle/Chapter ViewAbstractPublication PagescompsystechConference Proceedingsconference-collections
research-article

Computer Vision and Internet of Things: Attention System in Educational Context

Authors Info & Claims
Published:13 September 2018Publication History

ABSTRACT

In the contemporary education system, many information and communication technologies (ICT) and their applications already are an essential requisite. The value that they add to the traditional pedagogical practice makes it more engaging, flexible and efficient. Internet of things (IoT) as well as various multimedia and smart technologies enables implementation of more enhanced teaching approaches not only at universities but also at some innovative school classrooms. This research discusses a case study of the integration of computer vision (CV) and IoTs in the education and in particular, how they can support the learning process by making students more engaged. Further, this work presents some of the use-cases where the technology gadgets that shape smart learning environment completely benefit both the teaching-learning process itself and its managing.

References

  1. Elena Shoikova, Roumen Nikolov, Eugenia Kovatcheva. 2017. Conceptualizing of Smart Education. Electrotechnica & Electronica E+E, 52(3-4), 29--37.Google ScholarGoogle Scholar
  2. Maria Ianos, Gabriela Oproiu. 2017. Moodle Platform in Learning: Student's Voice. In Proceedings of 13th International Scientific Conference eLearning and Software for Education, Bucharest. 379--386.Google ScholarGoogle ScholarCross RefCross Ref
  3. Teodor Savov, Valentina Terzieva, Katia Todorova, Petia Kademova-Katzarova. 2017. Contemporary Technology Support for Education. In Proceedings of CBU International Conference on Innovations in Science and Education, Prague, 802--806.Google ScholarGoogle ScholarCross RefCross Ref
  4. Paul Ekman and Wallace V. Friesen. 1971. Constants across Cultures in the Face and Emotion. Journal of Personality and Social Psychology, 17(2), 124--129.Google ScholarGoogle ScholarCross RefCross Ref
  5. Lan Li and Ji-hua Chen. 2006. Emotion Recognition Using Physiological Signals. Advances in Artificial Reality and Tele-Existence, Springer Berlin Heidelberg, 437--446. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Boyan Bontchev. 2016. Adaptation in Affective Video Games: a Literature Review. Journal of Cybernetics and Information Technologies, 16(3), 3--34. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Boyan Bontchev and Dessislava Vassileva. 2017. Affect-Based Adaptation of an Applied Video Game for Educational Purposes. Interactive Technology and Smart Education, 14(1), 31--49.Google ScholarGoogle ScholarCross RefCross Ref
  8. Qualcomm Technologies Inc. 2017. Qualcomm Snapdragon 410E (APQ8016E) Processor Device Specification, LM80-P0436-7 Rev. F, Qualcomm Technologies. Retrieved May 2, 2018 from https://developer.qualcomm.com/qfile/28813/lm80-p0436-7_f_410e_proc_apq8016e_device_spec.pdfGoogle ScholarGoogle Scholar
  9. Valentina Terzieva, Teodor Savov, Katia Todorova, Rumen Andreev, Petia Kademova-Katzarova. 2017. Internet of Things in Education: Smart Environment. In Proceedings of 10th International Conference of Education, Research and Innovation, IATED, 4679--4685.Google ScholarGoogle ScholarCross RefCross Ref
  10. Alexander Mordvintsev and Abid Rahman K. 2017. OpenCV-Python Tutorials Documentation Release 1. Retrieved May 2, 2018 from https://media.readthedocs.org/pdf/opencv-python-tutroals/latest/opencv-python-tutroals.pdfGoogle ScholarGoogle Scholar
  11. Raja Ramiz. 2017. Face Detection Using Opencv and Python: A Beginner's Guide. Retrieved May 2, 2018 from https://www.superdatascience.com/opencv-face-detection/Google ScholarGoogle Scholar
  12. OpenCV Tutorials 2017. Face Recognition with OpenCV-Fisherfaces. Retrieved May 2 from https://docs.opencv.org/2.4/modules/contrib/doc/facerec/facerec _tutorial.html#fisherfacesGoogle ScholarGoogle Scholar
  13. Takeo Kanade, Jeffry Cohn, Yingli Tian. 2000. Comprehensive Database for Facial Expression Analysis, Retrieved May 2, from http://www.consortium.ri.cmu.edu/data/ck/Google ScholarGoogle Scholar
  14. Pooja Routhu, Rohit, Rekha G S. 2016. A Survey on Sleepy Eye Detection. International Journal of Engineering and Technical Research, 4(3), 136--140.Google ScholarGoogle Scholar
  15. Paul van Gent. 2016. Emotion Recognition with Python, OpenCV and a Face Dataset. A Tech Blog about Fun Things with Python and Embedded Electronics. Retrieved May 2, 2018 from http://www.paulvangent.com/2016/04/01/emotion-recognition-with-python-opencv-and-a-face-dataset/Google ScholarGoogle Scholar

Index Terms

  1. Computer Vision and Internet of Things: Attention System in Educational Context

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Other conferences
          CompSysTech '18: Proceedings of the 19th International Conference on Computer Systems and Technologies
          September 2018
          206 pages
          ISBN:9781450364256
          DOI:10.1145/3274005

          Copyright © 2018 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 13 September 2018

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article
          • Research
          • Refereed limited

          Acceptance Rates

          Overall Acceptance Rate241of492submissions,49%

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader