Material Classification and Accuracy Testing Using Passive CRFID Transponder in Recycle Unit.

International Conferences on Sensing Technology(2023)

引用 0|浏览3
暂无评分
摘要
Inappropriate material management in recycling chains lead to adverse effects of metals and glass inoculation in the plastic-only recyclable units/chains. Despite multiple ways to sort out plastic materials in garbage bins and large scale recycle units, intensive efforts are still needed to map the high cost and optic/light sensors drawbacks. In this paper, we propose a low-cost passive solution to the problem via design and deployment of smart wireless IoT sensor for material identification in huge recycle units. The sensor tag comprises of multi-resonator and slot structure yielding multiple bit response in maximum of 4.3mm radial dimensions. The electromagnetic radar cross section (EM RCS) signature is evaluated at three unique notches 21.4GHz, 23.7GHz, and 27.8GHz frequency, containing 3-unique data bits. The tag is designed using semi-octagonal structure to generate 3-bit EM signature. The resonance frequency and RCS response of tag is analyzed using CST Studio Suit software at far-field distance via incident plain wave. The approach is how accurately the plastic type and other materials are sorted out using single battery-free tag. As proof-of-concept, multiple samples of glass, metals and plastic type-1 and plastic type-2 are tested in the set-up for material classification. PET is used as plastic type-1 and HDPE is used as plastic type-2 material. Whereas, Aluminum is used as metal material, while soda lime material is used for glass classification. By deployment of presented smart sensor in commercial recycling chains/units, this concept can be utilized at huge market level for recycle applications, leading to a hygienic community excelled in all aspects of health safety.
更多
查看译文
关键词
Artificial Intelligence,RFID,IoT,IIOT,IOE,CRFID,ML,EM RCS,Smart sensors
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要