Author, as appears in the article.: Lazaro, Antonio; Boada, Marti; Villarino, Ramon; Girbau, David
Department: Enginyeria Electrònica, Elèctrica i Automàtica
URV's Author/s: Boada Navarro, Martí / Girbau Sala, David / Lázaro Guillén, Antonio Ramon / Villarino Villarino, Ramón Maria
Keywords: Wireless technology Support vector machine (svm) Radio frequency identification device Radio frequency identification (rfid) Near field communication Machine learning Internet of things (iot) Humans Fruit Foods Food quality Energy harvesting Electric power supplies Color sensor Color Classification Biosensing techniques Battery-less Algorithms
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.
Thematic Areas: Zootecnia / recursos pesqueiros Química Medicine (miscellaneous) Medicina veterinaria Medicina iii Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Linguística e literatura Letras / linguística Interdisciplinar Instruments & instrumentation Instrumentation Information systems Geografía Geociências Farmacia Engineering, electrical & electronic Engenharias iv Engenharias iii Engenharias ii Engenharias i Electrochemistry Electrical and electronic engineering Educação física Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência de alimentos Ciência da computação Chemistry, analytical Biotecnología Biodiversidade Biochemistry Atomic and molecular physics, and optics Astronomia / física Arquitetura, urbanismo e design Analytical chemistry
licence for use: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 14248220
Author's mail: antonioramon.lazaro@urv.cat david.girbau@urv.cat ramon.villarino@urv.cat
Author identifier: 0000-0003-3160-5777 0000-0001-7995-5536 0000-0001-9692-8943
Record's date: 2024-10-26
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://www.mdpi.com/1424-8220/19/7/1741
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Sensors. 19 (7): 1741-
APA: Lazaro, Antonio; Boada, Marti; Villarino, Ramon; Girbau, David (2019). Color Measurement and Analysis of Fruit with a Battery-Less NFC Sensor. Sensors, 19(7), 1741-. DOI: 10.3390/s19071741
Article's DOI: 10.3390/s19071741
Entity: Universitat Rovira i Virgili
Journal publication year: 2019
Publication Type: Journal Publications
Repositori URV