An automated solid waste detection using the optimized YOLO model for riverine management
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2024
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| author | Nur Athirah Zailan Khairunnisa Hasikin Anis Salwa Mohd Khairuddin Uswah Khairuddin Muhammad Mokhzaini Azizan |
| author_facet | Nur Athirah Zailan Khairunnisa Hasikin Anis Salwa Mohd Khairuddin Uswah Khairuddin Muhammad Mokhzaini Azizan |
| author_sort | Nur Athirah Zailan |
| building | USIM Library |
| collection | Institutional Repository |
| content_provider | Universiti Sains Islam Malaysia |
| content_source | USIM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Indexed by WOS/Scopus/ERA |
| format | text::journal::journal article |
| id | my.usim.oarep-6607 |
| institution | Universiti Sains Islam Malaysia |
| language | en |
| publishDate | 2024 |
| publisher | FRONTIERS |
| record_format | dspace |
| spelling | my.usim.oarep-66072025-12-17T07:40:13Z An automated solid waste detection using the optimized YOLO model for riverine management Nur Athirah Zailan Khairunnisa Hasikin Anis Salwa Mohd Khairuddin Uswah Khairuddin Muhammad Mokhzaini Azizan computer vision, image processing, object detection, smart city, urbanization, water quality Indexed by WOS/Scopus/ERA Due to urbanization, solid waste pollution is an increasing concern for rivers, possibly threatening human health, ecological integrity, and ecosystem services. Riverine management in urban landscapes requires best management practices since the river is a vital component in urban ecological civilization, and it is very imperative to synchronize the connection between urban development and river protection. Thus, the implementation of proper and innovative measures is vital to control garbage pollution in the rivers. A robot that cleans the waste autonomously can be a good solution to manage river pollution efficiently. Identifying and obtaining precise positions of garbage are the most crucial parts of the visual system for a cleaning robot. Computer vision has paved a way for computers to understand and interpret the surrounding objects. The development of an accurate computer vision system is a vital step toward a robotic platform since this is the front-end observation system before consequent manipulation and grasping systems. The scope of this work is to acquire visual information about floating garbage on the river, which is vital in building a robotic platform for river cleaning robots. In this paper, an automated detection system based on the improved You Only Look Once (YOLO) model is developed to detect floating garbage under various conditions, such as fluctuating illumination, complex background, and occlusion. The proposed object detection model has been shown to promote rapid convergence which improves the training time duration. In addition, the proposed object detection model has been shown to improve detection accuracy by strengthening the non-linear feature extraction process. The results showed that the proposed model achieved a mean average precision (mAP) value of 89%. Hence, the proposed model is considered feasible for identifying five classes of garbage, such as plastic bottles, aluminum cans, plastic bags, styrofoam, and plastic containers. 2024-05-28T05:49:30Z 2024-05-28T05:49:30Z 2022 2022-11-11 text::journal::journal article Zailan NA, Azizan MM, Hasikin K, Mohd Khairuddin AS and Khairuddin U (2022) An automated solid waste detection using the optimized YOLO model for riverine management. Front. Public Health 10:907280. doi: 10.3389/fpubh.2022.907280 2296-2565 2494-24 10.3389/fpubh.2022.907280 https://www.frontiersin.org/articles/10.3389/fpubh.2022.907280/full https://oarep.usim.edu.my/handle/123456789/6607 1 14 2022 2022 en Frontiers in Public Health application/pdf FRONTIERS |
| spellingShingle | computer vision, image processing, object detection, smart city, urbanization, water quality Nur Athirah Zailan Khairunnisa Hasikin Anis Salwa Mohd Khairuddin Uswah Khairuddin Muhammad Mokhzaini Azizan An automated solid waste detection using the optimized YOLO model for riverine management |
| title | An automated solid waste detection using the optimized YOLO model for riverine management |
| title_full | An automated solid waste detection using the optimized YOLO model for riverine management |
| title_fullStr | An automated solid waste detection using the optimized YOLO model for riverine management |
| title_full_unstemmed | An automated solid waste detection using the optimized YOLO model for riverine management |
| title_short | An automated solid waste detection using the optimized YOLO model for riverine management |
| title_sort | automated solid waste detection using the optimized yolo model for riverine management |
| topic | computer vision, image processing, object detection, smart city, urbanization, water quality |
| url_provider | http://oarep.usim.edu.my/ |