Automated classroom monitoring with connected visioning system

Jian Han Lim, Eng Yeow Teh, Ming Han Geh, Chern Hong Lim

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

19 Citations (Scopus)

Abstract

Internet of Things (IoT) with the concept of integrating connectivity, sensors, data analysis and decision making in an underlying framework has ease many real world problems. In this work, we study the application of IoT for education purpose. Student's behavior and performance in the class is always the main concern of every educator. The instructors are responsible to ensure the smoothness of the classroom activities alongside with monitoring the students' attendance, attention, and activities like entering or leaving the classroom. Manual observation on these could affect the teaching and learning process and causes the distraction from the main syllabus. With the incorporation of IoT devices and computational algorithms such as computer vision techniques, machine learning and data analysis, it can ease the monitoring task and the analysis of students' performance in the class. In advance, it can perform automated real-time observation on the student's behavior through network and react immediately to critical situation if necessary. Nonetheless, the students' long-term performance can be recorded and the data can be used for continuous assessment in the future. In this work, we propose an IoT framework that focused on three analysis modules: Face recognition, motion analysis, and behaviour understanding to effectively perform classroom monitoring tasks such as taking attendance, identify entering and leaving activities and analyse the students concentration level.

Original languageEnglish
Title of host publicationProceedings - Ninth Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
EditorsChang-Su Kim, Wai Lam Hoo
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages386-393
Number of pages8
ISBN (Electronic)9781538615423, 9781538615416
ISBN (Print)9781538615430
DOIs
Publication statusPublished - 2017
Externally publishedYes
EventAnnual Summit and Conference of the Asia-Pacific-Signal-and-Information-Processing-Association (APSIPA) 2017 - Kuala Lumpur, Malaysia
Duration: 12 Dec 201715 Dec 2017
Conference number: 9th
https://ieeexplore.ieee.org/xpl/conhome/8270695/proceeding (Proceedings)

Conference

ConferenceAnnual Summit and Conference of the Asia-Pacific-Signal-and-Information-Processing-Association (APSIPA) 2017
Abbreviated titleAPSIPA ASC 2017
Country/TerritoryMalaysia
CityKuala Lumpur
Period12/12/1715/12/17
Internet address

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