基于边缘计算平台和彼得里网模型的自动售货机中的智能回收物体识别系统
Yi-Nan Lin1, Hsiao-Chieh Hsu1, Ya-Fen Wu1
1Department of Electronic Engineering, Ming Chi University of Technology, 84, Gongzhuan Rd., Taishan District, New Taipei City, 243, Taiwan.
Journal of environmental management
|March 6, 2026
概括
这项研究介绍了一个由人工智能驱动的系统,用于自动回收分类自动售货机. 利用对象识别,它提高了废物管理的效率,并支持循环经济.
科学领域:
- 环境科学 环境科学
- 计算机科学 计算机科学
- 机器人技术 机器人技术 机器人技术
背景情况:
- 越来越多的全球环境问题需要有效的废物回收解决方案.
- 不断扩大的自动售货机市场产生了大量可回收废物.
- 目前的手动分类方法对于不断增加的废物流是低效的.
研究的目的:
- 开发一种自动化系统,用于从自动售货机中分类可回收材料.
- 利用对象识别技术改善废物管理.
- 为分散的废物管理创建一个可扩展,具有成本效益的解决方案.
主要方法:
- 对象识别模型YOLOv7-tiny经过训练以达到高精度 (98.9% mAP).
- 与HUB8735集成,用于基于摄像头的物体识别和运动控制.
- 培养网建模用于过程验证和确保准确性.
主要成果:
- 成功开发和实施可回收自动售货机原型.
- 在识别和分类可回收材料方面表现出高精度.
- 通过数学建模验证运营过程.
结论:
- 这种由人工智能驱动的系统为人工垃圾分类提供了一个可扩展和具有成本效益的替代方案.
- 提高资源回收的纯度,减少碳足迹.
- 为将人工智能纳入循环经济提供了一个实用的框架.
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