Design of computer vision training kit with machine learning algorithm to overcome distance learning in pandemic COVID-19

D. Kuswardhana; E. Haritman; F. Jabbar; F. Nashrullah

doi:10.1063/5.0139406

← Back to search

Design of computer vision training kit with machine learning algorithm to overcome distance learning in pandemic COVID-19

Closed

D. Kuswardhana, E. Haritman, F. Jabbar, F. Nashrullah

2023 AIP Conference Proceedings Vol. 2646 Conference paper Cited by 0 SDG 4

Abstract

The situation in the pandemic COVID-19 period has forced the education system to come into a different way of learning. This paper has oriented how to present laboratory workouts through a computer vision training kit to overcome distance learning in the pandemic. Thus, students (as the user) can use it anywhere. The environment used is on a Single Board Computer of NVIDIA Jetson Nano. The method is using the waterfall model. The way to access the training kit is to use the camera input on the user camera attached to their device connected through a streaming website. We establish the connection using the Remote Desktop Protocol, and The IoT part of the tool uses Antares Cloud Storage. Thus, the device state in the ESP32 microcontroller could be changed by the computer vision program. The entire process, as a result, can be inspected on another web portal containing the summary of the process on each module. © 2023 Author(s).

Affiliations

Department of Electrical Engineering Education, Universitas Pendidikan Indonesia, Bandung, Indonesia

View full text (DOI) →

Research at a Glance

Research at a Glance

Topics & SDG Alignment

Collaboration

Author Profile (Selected)

References Overview

Journal & Source

Metadata & Integrity