Automatic Monitoring of Fruit Ripening Rooms by UHF RFID Sensors and Machine Learning

C. Occhiuzzi, F. Camera, N. D'Uva, S. Amendola, L. Garavaglia, G. Marrocco
{"title":"Automatic Monitoring of Fruit Ripening Rooms by UHF RFID Sensors and Machine Learning","authors":"C. Occhiuzzi, F. Camera, N. D'Uva, S. Amendola, L. Garavaglia, G. Marrocco","doi":"10.1109/RFID-TA53372.2021.9617278","DOIUrl":null,"url":null,"abstract":"Forced ripening through the exposure of fruits to controlled environmental and gases conditions is nowadays one of the most assessed food technologies especially for climacteric and exotic products. However, a fine granularity control of the ripening process and consequently of the goods quality is still missing, so that the management of the ripening room is mainly based on qualitative estimations only. Following the modern paradigms of Industry 4.0, this contribution proposes a nondestructive RFID-based system for the automatic evaluation of the live ripening of up to 128 avocados inside the ripening room. The system, coupled with a properly trained automatic classification algorithm, is capable to discriminate the early stage of ripening with an accuracy greater than 85%.","PeriodicalId":212607,"journal":{"name":"2021 IEEE International Conference on RFID Technology and Applications (RFID-TA)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on RFID Technology and Applications (RFID-TA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RFID-TA53372.2021.9617278","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Forced ripening through the exposure of fruits to controlled environmental and gases conditions is nowadays one of the most assessed food technologies especially for climacteric and exotic products. However, a fine granularity control of the ripening process and consequently of the goods quality is still missing, so that the management of the ripening room is mainly based on qualitative estimations only. Following the modern paradigms of Industry 4.0, this contribution proposes a nondestructive RFID-based system for the automatic evaluation of the live ripening of up to 128 avocados inside the ripening room. The system, coupled with a properly trained automatic classification algorithm, is capable to discriminate the early stage of ripening with an accuracy greater than 85%.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用超高频RFID传感器和机器学习技术自动监控水果成熟室
通过将水果暴露在受控的环境和气体条件下强制成熟,是当今最受评估的食品技术之一,特别是对于更年期和外来产品。然而,对成熟过程的细粒度控制以及对产品质量的细粒度控制仍然缺失,使得成熟室的管理主要是基于定性的估计。遵循工业4.0的现代范例,该贡献提出了一种基于rfid的无损系统,用于自动评估催熟室内多达128个鳄梨的实时催熟。该系统与经过适当训练的自动分类算法相结合,能够区分成熟的早期阶段,准确率超过85%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Ring-shaped Tri-band Defective Ground Reader Antenna for RFID Applications Planar Endfire CP Antenna with Enhanced Gain and Beamwidth for RFID Applications RFID Labeling of Police Equipment A SLAM algorithm based on range and bearing estimation of passive UHF-RFID tags Performance of PIN diode RF switches within HF RFID reader designs
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1