Abstract
With the rapid development of big data analytics and the Internet of Things (IoT) technology, online learning becomes more and more prevalent. To improve the quality of online learning and help teachers better understand the students’ learning state, this paper proposes a Facial Emotion Recognition (FER) Enabled Education Aids IoT System, named FEAIS. By deploying a well-trained FER model on the remote server, FEAIS can provide instant feedback on students’ learning state by collecting their facial pictures through IoT devices like cameras or vision sensors and making recognization on their emotion. Utilizing this information, teachers can adjust their teaching progress to ensure that everyone could catch up. The experimental results demonstrate that the FEAIS can accurately recognize students’ emotion and give teachers precise feedback automatically, even if the images captured by IoT devices are occluded or deformed.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
