Ripe or Rotten? Low-Cost Produce Quality Estimation Using Reflective Green Light Sensing

被引:6
|
作者
Zuniga, Agustin [1 ]
Flores, Huber [2 ]
Nurmi, Petteri [3 ]
机构
[1] Univ Helsinki, Dept Comp Sci, Helsinki 00014, Finland
[2] Univ Tartu, Inst Comp Sci, EE-51009 Tartu, Estonia
[3] Univ Helsinki, Helsinki 00014, Finland
关键词
Sensors; Green products; Supply chains; Skin; Temperature measurement; Sensor phenomena and characterization; Power measurement; SYSTEM; TIME;
D O I
10.1109/MPRV.2021.3074474
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We develop an innovative low-cost approach for characterizing fresh produce by repurposing inexpensive commercial-off-the-shelf green light sensors for quality estimation. Our approach has been designed to support all stages of the supply chain while being inexpensive and easy to deploy. We validate our approach through extensive empirical benchmarks, showing that it can correctly distinguish organic produce from nonorganic items, establish unique fingerprints for different produce, and estimate the quality or ripeness of produce. Specifically, we demonstrate that changes in the reflected green light values correlate with the so-called transpiration coefficients of the produce. We also discuss the practicability of our approach and present application use cases that can benefit from our solution.
引用
收藏
页码:60 / 67
页数:8
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