AI-Powered Tracking for Sustainable Marine Ecosystem Resource Management Projects

IF 0.4 Q4 MANAGEMENT
Toby Chau, Helen Lv Zhang, Yuyue Gui, Man Fai Lau
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引用次数: 0

Abstract

Ecosystems are our planet's life-support systems that facilitate sustainable development. Within the marine ecosystem, oysters serve as a keystone species. Numerous oyster restoration projects have been launched with a crucial element involving precise assessment of oyster population sizes within specific reef areas. However, the current methods of tracking oyster populations are approximate and lack precision. To address this research gap, the authors developed an AI-empowered project for oyster detection. Specifically, they created a dataset of wild oysters, utilized Roboflow for image annotation, and employed image augmentation techniques to augment the training data. Then, they fine-tuned a YOLOv8 computer vision object detection model using their dataset. The results demonstrated a mean average precision (mAP) of 85.2 percent and an accuracy of 87.7 percent for oyster detection. This approach improved upon previous attempts to detect wild oysters, offering a more effective solution for population assessment, which is a fundamental step toward sustainable oyster restoration project management.
人工智能驱动的可持续海洋生态系统资源跟踪管理项目
生态系统是我们这个星球的生命支持系统,有助于可持续发展。在海洋生态系统中,牡蛎是一个关键物种。许多牡蛎恢复项目已经启动,其中一个关键因素是对特定珊瑚礁区域内的牡蛎种群数量进行精确评估。然而,目前跟踪牡蛎种群的方法都是近似的,缺乏精确性。针对这一研究空白,作者开发了一个人工智能赋能的牡蛎检测项目。具体来说,他们创建了一个野生牡蛎数据集,利用 Roboflow 进行图像标注,并采用图像增强技术来增强训练数据。然后,他们利用数据集对 YOLOv8 计算机视觉物体检测模型进行了微调。结果表明,牡蛎检测的平均精度(mAP)为 85.2%,准确率为 87.7%。这种方法改进了之前检测野生牡蛎的尝试,为种群评估提供了更有效的解决方案,而种群评估是实现可持续牡蛎恢复项目管理的基本步骤。
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来源期刊
CiteScore
1.70
自引率
25.00%
发文量
20
期刊介绍: The mission of International Journal of Information Technology Project Management (IJITPM) is to provide a forum for practitioners and researchers from both public and private sectors of project management professionals, along with information systems researchers, software developers and vendors, to contribute and to circulate ground-breaking work, and to shape future directions for research, as well as to help project leaders and managers apply various advanced techniques in information systems. It encourages discussions on how the various information systems can improve project management as well as how advances in project management can affect the growth of information systems.
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