论文标题
UHF RFID传感器网络和机器学习对水果成熟室的自动监视
Automatic Monitoring of Fruit Ripening Rooms by UHF RFID Sensor Network and Machine Learning
论文作者
论文摘要
如今，通过将水果暴露于控制的环境条件和气体中，加速成熟是评估最多的食物技术之一，尤其是对于高潮和外来产品。但是，对过程的精细粒度控制，因此仍然缺少商品质量，因此成熟室的管理主要仅基于定性估计。按照工业4.0的现代范式，这项贡献提出了一种基于RFID的非破坏性系统，用于自动评估鳄梨的实时成熟。该系统以及基于支持矢量机（SVM）的适当训练的自动分类算法，可以以大于85％的精度来区分成熟阶段。
Accelerated ripening through the exposure of fruits to controlled environmental conditions and gases is nowadays one of the most assessed food technologies, especially for climacteric and exotic products. However, a fine granularity control of the process and consequently of the quality of the goods is still missing, so the management of the ripening rooms is mainly based on qualitative estimations only. Following the modern paradigms of Industry 4.0, this contribution proposes a non-destructive RFID-based system for the automatic evaluation of the live ripening of avocados. The system, coupled with a properly trained automatic classification algorithm based on Support Vector Machines (SVMs), can discriminate the stage of ripening with an accuracy greater than 85%.
