ArticleSensors (Basel, Switzerland)2019
Color Measurement and Analysis of Fruit with a Battery-Less NFC Sensor.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Impact of Combined Rootstock Cultivar and Grafting Method on Growth, Yield, and Quality of Soilless-Grown Cucumber (Plants (Basel, Switzerland) · 2025Article
- Study of active food processing technology using computer vision and AI in coffee roasting.Food science and biotechnology · 2024Article
- Review
- Near-Field Communication Tag for Colorimetric Glutathione Determination with a Paper-Based Microfluidic Device.Biosensors · 2023Article
- Advancements in CRISPR-Based Biosensing for Next-Gen Point of Care Diagnostic Application.Biosensors · 2023Review
- RFID-based sensing in smart packaging for food applications: A review.Future foods : a dedicated journal for sustainability in food science · 2022Review
- Battery-Less NFC Potentiostat for Electrochemical Point-of-Care Sensors Based on COTS Components.Sensors (Basel, Switzerland) · 2022Article
- A Smart Archive Box for Museum Artifact Monitoring Using Battery-Less Temperature and Humidity Sensing.Sensors (Basel, Switzerland) · 2021Article
- Near-Field Communication in Biomedical Applications.Sensors (Basel, Switzerland) · 2021Review
- Monitoring Transepidermal Water Loss and Skin Wettedness Factor with Battery-Free NFC Sensor.Sensors (Basel, Switzerland) · 2020Article
- Longest-Range UHF RFID Sensor Tag Antenna for IoT Applied for Metal and Non-Metal Objects.Sensors (Basel, Switzerland) · 2019Article
- Near Field Communication-based Agricultural Management Service Systems for Family Farms.Sensors (Basel, Switzerland) · 2019Article
- Radio Frequency Identification and Sensing Techniques and Their Applications-A Review of the State-of-the-Art.Sensors (Basel, Switzerland) · 2019Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper presents a color-based classification system for grading the ripeness of fruit using a battery-less Near Field Communication (NFC) tag. The tag consists of a color sensor connected to a low-power microcontroller that is connected to an NFC chip. The tag is powered by the energy harvested from the magnetic field generated by a commercial smartphone used as a reader. The raw RGB color data measured by the colorimeter is converted to HSV (hue, saturation, value) color space. The hue angle and saturation are used as features for classification. Different classification algorithms are compared for classifying the ripeness of different fruits in order to show the robustness of the system. The low cost of NFC chips means that tags with sensing capability can be manufactured economically. In addition, nowadays, most commercial smartphones have NFC capability and thus a specific reader is not necessary. The measurement of different samples obtained on different days is used to train the classification algorithms. The results of training the classifiers have been saved to the cloud. A mobile application has been developed for the prediction based on a table-based method, where the boundary decision is downloaded from a cloud service for each product. High accuracy, between 80 and 93%, is obtained depending on the kind of fruit and the algorithm used.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.