Granite classification using machine learning and edge computing [version 1; peer review: 1 approved, 2 approved with reservations]

Background: The outlook and the aura of any place are highly dependent on how a place is decorated and what materials are used in designing it. Granite is such a kind of rock which is vastly used for this purpose. Granite flooring and counters have a major influence on the interior d ́ecor which is essential to set the mood and ambience of a house. A system is needed to help the end users differentiate between granites, which enhance the grandeur of their house and also check the frauds of different color granite being sent by the merchant as compared to what was selected by the end user. Several models have been developed for this cause using CNN and other image processing techniques. However, a solution for this purpose must be precise and computationally efficient. Methods: For this purpose,researchers in this work developed a machine learning based granite classifier using Edge Computing and a website to help users in choosing which granite would go well with their d ́ecor is also built. The developed system consists of a color sensor [TCS3200] integrated with an ESP8266 board. The data pertaining to RGB contrasts of different rocks is acquired by using the color sensor from a dealership.This data is used to train a Machine Learning algorithm to classify the rock into different granite types from a granite dealer and yield the category prediction. Results: The proposed system yields a result of 94% accuracy when classified using Random Forest Algorithm. Conclusion: Thus, this system provides an upper hand for the end users in differentiating between different types of granites

Research on efficacy of webinars organized for faculty during lockdown of COVID-19

Online Faculty Development Programs/Webinars are the two buzzing words, which have become viral next to corona among the teaching fraternity during the lockdown period of pandemic situation caused by COVID-19. This work intends to throw light on, the reason for the outbreak of FDPs/ Webinars, their efficiency and the attitude of the participating faculty during the lockdown period from 16th March to 15th June 20. Information is gathered through an online survey having 31 research questions answered by 683 participants across India. The new found tool of online teaching has become the accepted norm and the urge to lead the bandwagon by each and every stakeholder in the education sector resulted in a sudden spurt of webinars and FDPs in such a short period. Study observed that global reach at no cost plus freedom of working from home spurred many faculty to experiment this mode and 40% from them have been found to be juggling with many courses simultaneously for certificate sake only, 45.1% attended on mandatory instructions and 38% have not even initiated the work. Quizzes and Polls during sessions besides assignments were found to be suitable active learning mechanisms to improve the efficacy of the online knowledge transfer methods