ABSTRACT
During this Covid-19, face masks are used to avoid cross-contamination as part of an infection protection strategy. Wearing a face mask can help avoid infection by preventing individuals from coming into contact with pathogens. When someone coughs, speaks, or sneezes, there is a chance that the infection will spread into the air and affect those nearby. So to prevent the rate of spreading, face masks are highly mandatory. Tracking every individual manually is an expensive task;therefore, we save a lot of time, cost and effort by automating this process. This proposed automation can be done using Artificial Neural Networks. YOLOv3 and MobileNetv2 are popular architectures used in different object detection applications. Hence, paper compares the above architectures by their performance, accuracy from outputs of both under different scenarios. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Post Covid-19 is a real challenge, as students’ faces are not visible to teachers during interaction or nor the students are available physically, leaving teachers clueless about their active learning and active engagement in learning. Achieving graduate attributes poses further challenge as it has to ensure imbibing Higher Order Thinking skills [HOTs] in students. There is a need to develop online integrated pedagogy to overcome this problem. It is observed that creating content specific videos, really creates interest in students and ensures active learning, if they are asked to upload in YouTube provided students are guided with Rubric based learning for video creation. Moodle integrated YouTube [MIY] channel is developed to let the teachers create their own Video of short duration with rubric guidance. The paper presents a case study dedicated to PO7 [Program Outcome Environment and Sustainability], supported by Open Education for better World [OE4BW]. The Moodle based methodology [73 activities in Moodle- Games like crossword, Quiz, Discussion Forum], integrating with google meet to interact with participants, Rubric guidance, query solving, active learner’s motivation and impact of posting in YouTube channel are presented in study. Out of 268 participants, 217 participants peer reviewed videos were selected and added in YouTube channel [Environment and sustainability OE4BW, https://www.youtube.com/channel/UCQWwEFdEMeS7Kc 3MuWw3Jkg/videos] based on quality content [Carbon foot print analysis, Environment and Sustainability computation] created by them. Participant’s happiness index for learning was attributed as A+ [4.79/5] during the entire video development process. © 2021, Rajarambapu Institute Of Technology. All rights reserved.