Characterization and Differentiation between Olive Varieties through Electrical Impedance Spectroscopy, Neural Networks and IoT
| Autor: | Antonio Madueño Luna, Rafael Enrique Hidalgo Fernández, José Miguel Madueño Luna |
|---|---|
| Přispěvatelé: | Universidad de Sevilla. Departamento de Ingeniería Aeroespacial y Mecánica de Fluidos, Universidad de Sevilla. AGR280: Ingeniería Rural |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
internet of things (IoT)
Artificial neural networks (ANNs) SoC AD5933 02 engineering and technology lcsh:Chemical technology 01 natural sciences Biochemistry Multiplexer Article Sweep frequency response analysis Analytical Chemistry Internet of things (IoT) System on a chip lcsh:TP1-1185 Electrical and Electronic Engineering Field-programmable gate array Instrumentation Electrical impedance Water content artificial neural networks (ANNs) Mathematics electrical impedance Artificial neural network business.industry 010401 analytical chemistry Temperature temperature 021001 nanoscience & nanotechnology Atomic and Molecular Physics and Optics 0104 chemical sciences 0210 nano-technology Internet of Things business Biological system |
| Zdroj: | Sensors, Vol 20, Iss 5932, p 5932 (2020) Sensors Volume 20 Issue 20 idUS. Depósito de Investigación de la Universidad de Sevilla instname idUS: Depósito de Investigación de la Universidad de Sevilla Universidad de Sevilla (US) Sensors (Basel, Switzerland) |
| ISSN: | 1424-8220 |
| Popis: | Electrical impedance has shown itself to be useful in measuring the properties and characteristics of agri-food products: fruit quality, moisture content, the germination capacity in seeds or the frost-resistance of fruit. In the case of olives, it has been used to determine fat content and optimal harvest time. In this paper, a system based on the System on Chip (SoC) AD5933 running a 1024-point discrete Fourier transform (DFT) to return the impedance value as a magnitude and phase and which, working together with two ADG706 analog multiplexers and an external programmable clock based on a synthesized DDS in a FPGA XC3S250E-4VQG100C, allows for the impedance measurement in agri-food products with a frequency sweep from 1 Hz to 100 kHz. This paper demonstrates how electrical impedance is affected by the temperature both in freshly picked olives and in those processed in brine and provides a way to characterize cultivars by making use of only the electrical impedance, neural networks (NN) and the Internet of Things (IoT), allowing information to be collected from the olive samples analyzed both on farms and in factories |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|