Affiliation:
1. Kobe City College of Technology, 8-3 Gakuen-higashimachi, Nishi-ku, Kobe, Hyogo 651-2194, Japan
Abstract
The illegal dumping of aluminum and plastic into cities and marine areas leads to negative impacts on the ecosystem and contributes to increased environmental pollution. Although volunteer trash pickup activities have increased in recent years, they require significant effort, time, and money. Therefore, we propose automated trash pickup robot, which incorporates autonomous movement and trash pickup arms. Although these functions have been actively developed, relatively little research has focused on trash detection. As such, we have developed a trash detection function by using deep learning models to improve the accuracy. First, we created a new trash dataset that classifies four types of trash with high illegal dumping volumes (cans, plastic bottles, cardboard, and cigarette butts). Next, we developed a new you only look once (YOLO)-based model with low parameters and computations. We trained the model on a created dataset and a dataset consisting of marine trash created during previous research. In consequence, the proposed models achieve the same detection accuracy as the existing models on both datasets, with fewer parameters and computations. Furthermore, the proposed models accelerate the edge device’s frame rate.
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
Reference50 articles.
1. Organisation for Economic Co-Operation and Development (OECD), “Environment at a glance 2020,” OECD Publishing, 2020. https://doi.org/10.1787/4ea7d35f-en
2. National Oceanic and Atmospheric Administration (NOAA), “What is marine debris?” https://oceanservice.noaa.gov/facts/marinedebris.html [Accessed May 3, 2021]
3. Keep America Beautiful, “Keep America Beautiful’s Volunteer Portal.” https://Volunteer.kab.org [Accessed May 3, 2021]
4. OR&R’s Marine Debris Division, NOAA, “Removal.” https://marinedebris.noaa.gov/our-work/removal [Accessed May 3, 2021]
5. S. Hossain et al., “Autonomous trash collector based on object detection using deep neural network,” 2019 IEEE Reg. 10 Conf. (TENCON 2019), pp. 1406-1410, 2019. https://doi.org/10.1109/TENCON.2019.8929270
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Real-time Detection of Submerged Debris in Aquatic Ecosystems using YOLOv8;2023 26th International Conference on Computer and Information Technology (ICCIT);2023-12-13
2. An Enhanced Algorithm for Marine Litter Detection in YOLOv5;2023 2nd International Conference on Artificial Intelligence, Human-Computer Interaction and Robotics (AIHCIR);2023-12-08