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  • ElecEng
  • GC-ElecEng 2020
  • 29.Cnf-1154
ElecEng Congresses with Published Papers
GC-ElecEng 2020, Valencia
GC-ElecEng 2021, Valencia
Papers Published at GC-ElecEng 2020
All 3 Papers
IDAuthors and TitlePages
29.Cnf-105 Dr. Alex Vukovic
Ms. Ayat Alrjoub
Furthering Innovation in Hyper Communication Era
29.Cnf-113 Prof. Càndid Reig
Dr. Maria-Dolores Cubells-Beltran
Mr. Javio Sanchis-Muñoz
Prof. Fernando Pardo
Dr. Jose A. Boluda
Dr. Francisco Vegara
Dr. Susana Cardoso
Address Event Representation (AER) approach to resistive sensor arrays

GS Citations

Prof. Cebrail Ciflikli
Mr. Kadir Aba
Implementing low cost and secure data transmission layer for image transmission in wireless sensor network
29.Cnf-1154 Paper View Page
Title Development of Optical Sensor to detect Industrial Oil in Agricultural Irrigation System
Authors Mr. Daniel Andoni Basterrechea, Universitat Politecnica de Valencia, Valencia, Spain
Mr. Javier Rocher, Universidad Politécnica de Valencia, Grau de Gandia, Spain
Dr. Lorena Parra, Universitat Politecnica de Valencia, Valencia, Spain
Prof. Jaime Lloret, Universitat Politecnica de Valencia, Valencia, Spain
Abstract The increase of the industrial sector and the use of mechanical devices in agriculture causes the increment of oil discharges in water bodies that are used to irrigate agricultural lands. In this context, precision agriculture becomes a critical way to solve these problems. In this paper, we propose an optical sensor to detect and monitor the quantity of oil in the agricultural irrigation system. The sensors use different colour light sources (white, yellow, blue, green, orange, and near-infrared). Moreover, a photoresistor and photodiode are located at 0º and 180º of the light source to measure the light dispersion. This prototype will be part of a wireless sensor network that allows obtaining the values in real-time in river channels. We experimented using different oil concentrations, between 0 and 0.2 ml oil/cm2. In addition, we analyse the output voltage changes between the different light sources for all oil quantities. The results show that the lowest difference is found for the white colour with 0.025 V. Then, the yellow and blue light sources obtained a change of 0.089 and 0.075 V respectively. On the other hand, the highest voltages are found for the green and red clours, with 0.29 and 0.39 V. The mathematical models of the bests Light Sources are calculated, obtaining the correlation coefficients of 0.9604 in the red light and 0.8647 in the green light. Finally, we perform a multirange analysis with the values of the different light sources, verifying that the red and green light sources have the most reliable values.
Track Sensors: Sensors, Sensor Networks, and Applications
Conference 1st Mosharaka International Conference on Emerging Applications of Electrical Engineering (MIC-ElectricApps 2020)
Congress 2020 Global Congress on Electrical Engineering (GC-ElecEng 2020), 4-6 September 2020 (Remotely), Valencia, Spain
Pages --1
Topics Sensors for Agriculture
Sensors for Environmental Monitoring
ISSN 2227-331X
BibTeX @inproceedings{1154ElecEng2020,
title={Development of Optical Sensor to detect Industrial Oil in Agricultural Irrigation System},
author={Daniel Andoni Basterrechea, and Javier Rocher, and Lorena Parra, and Jaime Lloret},
booktitle={2020 Global Congress on Electrical Engineering (GC-ElecEng 2020)},
organization={Mosharaka for Research and Studies} }
Paper Views 460 Paper Views Rank 185/525
Paper Downloads 184 Paper Downloads Rank 155/525
GC-ElecEng 2020 Visits: 19597||MIC-ElectricApps 2020 Visits: 12490||Sensors Track Visits: 2554