A design of Intelligent Public Trash Can based on Machine Vision and Auxiliary Sensors

DOI

10.2991/jrnal.k.211108.009How to use a DOI?

Keywords

Garbage classification; machine vision; deep learning; auxiliary sensors

Abstract

To improve the accuracy of front-end recognition in the garbage classification process, the recognition accuracy of the automatic garbage classification system designed based on machine vision is significantly higher than that of the traditional smart garbage can. However, the recognition accuracy rate for irregular garbage is low. To solve such problems, four types of auxiliary sensors are added to the trash can, through the mutual cooperation between the sensors, combined with the results of machine vision recognition for comprehensive judgment, greatly improving the recognition accuracy of irregular trash. It shows the broad application prospects of the research results of this paper in waste classification and environmental protection.

Copyright

© 2021 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Longyu Gao
AU  - Fengzhi Dai
AU  - Zhiqing Xiao
AU  - Jiangyu Wu
AU  - Zilong Liu
PY  - 2021
DA  - 2021/12/27
TI  - A design of Intelligent Public Trash Can based on Machine Vision and Auxiliary Sensors
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 273
EP  - 277
VL  - 8
IS  - 4
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.k.211108.009
DO  - 10.2991/jrnal.k.211108.009
ID  - Gao2021
ER  -