New Sensor Based on Magnetic Fields for Monitoring the Concentration of Organic Fertilisers in Fertigation Systems

[EN] In this paper, we test three prototypes with different characteristics for controlling the quantity of organic fertiliser in the agricultural irrigation system. We use 0.4 mm of copper diameter, distributing in different layers, maintaining the relation of 40 spires for powered coil and 80 for the induced coil. Moreover, we develop sensors with 8, 4, and 2 layers of copper. The coils are powered by a sine wave of 3.3 V peak to peak, and the other part is induced. To verify the functioning of this sensor, we perform several simulations with COMSOL Multiphysics to verify the magnetic field created around the powered coil, as well as the electric field, followed by a series of tests, using six samples between the 0 g/L and 20 g/L of organic fertiliser, and measure their conductivity. First, we find the working frequency doing a sweep for each prototype and four configurations. In this case, for all samples, making a sweep between 10 kHz and 300 kHz. We obtained that in prototype 1 (P1) (coil with 8 layers) the working frequency is around 100 kHz, in P2 (coil with 4 layers) around 110 kHz, and for P3 (coil with 2 layers) around 140 kHz. Then, we calibrate the prototypes measuring the six samples at four different configurations for each sensor to evaluate the possible variances. Likewise, the measures were taken in triplicate to reduce the possible errors. The obtained results show that the maximum difference of induced voltage between the lowest and the highest concentration is for the P2/configuration 4 with 1.84 V. Likewise, we have obtained an optimum correlation of 0.997. Then, we use the other three samples to verify the optimum functioning of the obtained calibrates. Moreover, the ANOVA simple procedure is applied to the data of all prototypes, in the working frequency of each configuration, to verify the significant difference between the values. The obtained results indicate that there is a significate difference between the average of concentration (g/L) and the induced voltage, and another with a level of 5% of significance. Finally, we compare all of the tested prototypes and configurations, and have determined that prototype three with configuration 1 is the best device to be used as a fertiliser sensor in water.This work is partially funded by the Conselleria de Educacion, Cultura y Deporte with the Subvenciones para la contratacion de personal investigador en fase postdoctoral, grant number APOSTD/2019/04, by the European Union, through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) project ERANETMED3-227 SMARTWATIR, and by the European Union with the "Fondo Europeo Agricola de Desarrollo Rural (FEADER)-Europa invierte en zonas rurales", the MAPAMA, and Comunidad de Madrid with the IMIDRA, under the mark of the PDR-CM 2014-2020" project number PDR18-XEROCESPED.Basterrechea-Chertudi, DA.; Parra-Boronat, L.; Botella-Campos, M.; Lloret, J.; Mauri, PV. (2020). New Sensor Based on Magnetic Fields for Monitoring the Concentration of Organic Fertilisers in Fertigation Systems. Applied Sciences. 10(20):1-28. https://doi.org/10.3390/app102072221281020World Agriculture 2030: Main Findingshttp://www.fao.org/english/newsroom/news/2002/7833-en.htmlGamarra, C., Díaz Lezcano, M. I., Vera de Ortíz, M., Galeano, M. D. P., & Cabrera Cardús, A. J. N. (2018). Relación carbono-nitrógeno en suelos de sistemas silvopastoriles del Chaco paraguayo. Revista Mexicana de Ciencias Forestales, 9(46). doi:10.29298/rmcf.v9i46.134Too Much Organic Matterhttps://www.mofga.org/Publications/The-Maine-Organic-Farmer-Gardener/Fall-2009/Organic-MatterNasir Khan, M. (2018). OBSOLETE: Fertilizers and Their Contaminants in Soils, Surface and Groundwater. Reference Module in Earth Systems and Environmental Sciences. doi:10.1016/b978-0-12-409548-9.09888-2Gebbers, R., & Adamchuk, V. I. (2010). Precision Agriculture and Food Security. Science, 327(5967), 828-831. doi:10.1126/science.1183899Feng, C., Lü, S., Gao, C., Wang, X., Xu, X., Bai, X., … Wu, L. (2015). «Smart» Fertilizer with Temperature- and pH-Responsive Behavior via Surface-Initiated Polymerization for Controlled Release of Nutrients. ACS Sustainable Chemistry & Engineering, 3(12), 3157-3166. doi:10.1021/acssuschemeng.5b01384Ni, B., Liu, M., Lü, S., Xie, L., & Wang, Y. (2011). Environmentally Friendly Slow-Release Nitrogen Fertilizer. Journal of Agricultural and Food Chemistry, 59(18), 10169-10175. doi:10.1021/jf202131zSouza, C. F., Faez, R., Bacalhau, F. B., Bacarin, M. F., & Pereira, T. S. (2017). IN SITU MONITORING OF A CONTROLLED RELEASE OF FERTILIZERS IN LETTUCE CROP. Engenharia Agrícola, 37(4), 656-664. doi:10.1590/1809-4430-eng.agric.v37n4p656-664/2017Merten, G. H., Capel, P. D., & Minella, J. P. G. (2013). Effects of suspended sediment concentration and grain size on three optical turbidity sensors. Journal of Soils and Sediments, 14(7), 1235-1241. doi:10.1007/s11368-013-0813-0Comsol Multiphysicshttps://www.comsol.com/Kleinberg, R. L., Chew, W. C., & Griffin, D. D. (1989). Noncontacting electrical conductivity sensor for remote, hostile environments. IEEE Transactions on Instrumentation and Measurement, 38(1), 22-26. doi:10.1109/19.19992Parra, L., Marín, J., Mauri, P. V., Lloret, J., Torices, V., & Massager, A. (2019). Scatternet Formation Protocol for Environmental Monitoring in a Smart Garden. Network Protocols and Algorithms, 10(3), 63. doi:10.5296/npa.v10i3.14122Wood, L. T., Rottmann, R. M., & Barrera, R. (2004). Faraday’s law, Lenz’s law, and conservation of energy. American Journal of Physics, 72(3), 376-380. doi:10.1119/1.1646131Parra, L., Sendra, S., Lloret, J., & Bosch, I. (2015). Development of a Conductivity Sensor for Monitoring Groundwater Resources to Optimize Water Management in Smart City Environments. Sensors, 15(9), 20990-21015. doi:10.3390/s150920990Karagianni, E. A. (2015). ELECTROMAGNETIC WAVES UNDER SEA: BOW-TIE ANTENNAS DESIGN FOR WI-FI UNDERWATER COMMUNICATIONS. Progress In Electromagnetics Research M, 41, 189-198. doi:10.2528/pierm15012106https://www.tek.com/signal-generator/afg1022https://www.tek.com/oscilloscope/tbs1104http://www.crisoninstruments.com/es/laboratorio/conductimetro/desobremesa/ec-metro-basic-30https://www.leroymerlin.es/fp/19468554/fertilizante-para-citricos-geolia-uso-ecologico-1lhttps://statgraphics.net/descargas-centurion-xvii/Matsoukis, A., Kamoutsis, A., & Chronopoulou-Sereli, A. (2018). A Note on the Flowering of Ajuga orientalis L. in Relation to Air Temperature in Mount Aenos (Cephalonia, Greece). Current Agriculture Research Journal, 6(3), 261-267. doi:10.12944/carj.6.3.0

Water Conductivity Sensor based on Coils to Detect Illegal Dumpings in Smart Cities

[EN] The illegal dumpings in sewerage can cause problems in the Wastewater treatment plants. In this paper, we propose a system for detecting these illegal dumpings. We use conductivity sensor for detecting the change in the conductivity of water. Because this change may be due to a dump. The system is based on two coils, a coil is powered by a sinus-wave and induced the other coil. To prevent damaged for water in the copper we encapsulate the coils in a PVC tube. These coils are connected to flyport to send the values and generate alarms. We test with different configurations of coils with encapsulation of 3 and 1 mm. In the different prototypes tested have been seen that with the 3 mm encapsulation no significant differences are observed. The better prototypes are based on 40 spires of the powered coil and 80 spires in the induced coil. The best difference between samples of 0 and 40 g/l of table salt are in the prototype when the spires are distributed in 1 layer (6.06 V). Another prototype test with the same number of turns but distributed in 4 layers has a difference of 4.10 V. But during the verification phase we verified that this last prototype presents a relative error of 2.54% compared to 6.55% of the prototype distributed in a layerThis work has also been partially supported by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activ-ities and beyond) project ERANETMED3-227 SMARTWATIR by the Ministerio de Educación, Cultura y Deporte, through the Ayudas para contratacion predoctoral de Formación del Profesorado Universitario FPU (Convocatoria 2016). Grant number FPU16/05540.Rocher-Morant, J.; Basterrechea-Chertudi, DA.; Taha, M.; Parra-Boronat, M.; Lloret, J. (2019). Water Conductivity Sensor based on Coils to Detect Illegal Dumpings in Smart Cities. IEEE. 324-329. https://doi.org/10.1109/FMEC.2019.8795341S32432