Issue |
ITM Web Conf.
Volume 56, 2023
First International Conference on Data Science and Advanced Computing (ICDSAC 2023)
|
|
---|---|---|
Article Number | 01002 | |
Number of page(s) | 10 | |
Section | Computational Intelligence and Computing | |
DOI | https://doi.org/10.1051/itmconf/20235601002 | |
Published online | 09 August 2023 |
Articulated Robot Arm for Garbage Disposal in Hospital Environment
Department of Electronics and Communication Engineering, PES University, Bangalore - 560085, India
* shreyanshkumarjain@pesu.pes.edu
† mittapallimonish@pesu.pes.edu
‡ neerajgupta@pesu.pes.edu
§ shivamkumarraj@pesu.pes.edu
fj karpagavallip@pes.edu
The use of robotic arms is crucial in the medical industry, particularly in hospital settings. It can be used for a wide range of things, including as an aide in the operating room or for the removal of medical waste, among many other things. In this work, the robotic arm is designed to segregate medical waste as hazardous or non-hazardous. A dataset with five classes was created because there was no readily available data set for medical waste. The primary challenge in doing so is to programme the robotic arm’s movements and train the image dataset to classify objects as hazardous or non-hazardous. The 3D-printed robotic arm model has 6-Degree of Freedom(DOF) and is coupled with MG996R and SG90 servo motors. The robotic arm that is attached to an Arduino uno board is operated by the Blynk IoT platform. It uses YOLO V5 (You Only Look Once) algorithm to detect objects, and it favours intersection over union (IOU). To demonstrate, static robotic arm model was placed near the pile of medical waste to identify the waste and segregate it accordingly.
Key words: Machine learning / Internet of things (IoT) / Robotic arm / Computer vision
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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