解决养老院的食物浪费问题:使用智能垃圾桶进行测量方法
Zisen Liu1, Kavitha Chelakara Satyanarayana1, Ashok K Chaitanya Koppisetty1
1Swedish Centre for Resource Recovery, University of Borås 501 90 Borås, Sweden; Vepred AB, Sven Hultins Gata 9C, 412 58 Göteborg, Sweden.
Waste management (New York, N.Y.)
|May 6, 2025
概括
这项研究提出了一种智能垃圾箱方法,用于跟踪养老院的食物浪费,揭示了混合菜式和土豆的大量浪费. 这种创新方法使废物减少策略的详细,长期监测成为可能.
科学领域:
- 环境科学 环境科学
- 食品科学 食品科学 食品科学
- 老年学是一门学科.
背景情况:
- 食品浪费是机构食品服务的重大挑战,特别是在养老院.
- 有效的监测系统对于防止食品浪费和回收利用至关重要,但对于长期跟踪通常是很困难的.
研究的目的:
- 引入和评估一种基于智能垃圾桶的新方法,用于量化和描述养老院的食物浪费.
- 评估食品废物分析的自动化数据收集和多层次分类的可行性和多功能性.
主要方法:
- 开发一个智能垃圾箱系统,用于自动收集食品废弃物数据.
- 实施结构化数据处理和多层级废物分类.
- 在瑞典Borås的一家养老院进行案例研究.
主要成果:
- 初步结果表明,该方法在捕获每周在餐点和整体废物分配中的废物方面具有多功能性.
- 平均午餐浪费量为78g/份 (52%的盘子,48%的份量);平均晚餐浪费量为58g/份量 (68%的盘子,31%的份量).
- 混合菜式和土豆被确定为食品浪费的最大贡献者.
结论:
- 智能垃圾箱方法有效地捕捉了高颗粒度的食物浪费动态.
- 该系统显示了在机构环境中可扩展的,长期的食物浪费监测的潜力.
- 这种方法为人工智能驱动的分类和数据驱动的干预措施提供了基础,以减少食物浪费.
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