Design and development of low cost smart turbidity sensor for water quality monitoring in fish farms

[EN] Turbidity monitoring is necessary in many cases and several sensors have been developed for this purpose. However, in some cases to quantify the turbidity it is not enough and its characterization is necessary. In fish farms, the increase of sedimentary or phytoplanktonic turbidity requires different actions to prevent further damages. For this reason, a sensor able to differentiate between turbidity sources is necessary. In this paper, a turbidity sensor able to distinguish different types of turbidity is designed, developed and calibrated. The sensor is based on the Beer-Lambert law and it uses four LEDs as light sources with different wavelengths. The sensing elements are located at 180° of the light sources and consist of a photodiode and a photoresistor, sensitive to infrared and visible wavelengths respectively. For the calibration process different turbidity sources were employed, Isochrysis galbana, Tetraselmis chuii and sediment. The results show that it is possible to determine the turbidity using the infrared light and to characterize the origin of that turbidity with the red light. An algorithm was created in order to create a method to process the data from each sample to obtain the turbidity, the origin of this turbidity and the concentration of the turbidity source. With this algorithm, we can create a smart turbidity sensor for water quality monitoring. Our main application is focused on monitoring the water input in fish farm facilities; however, this smart sensor will be useful in many other areas.This work has been partially supported by the "Ministerio de Educacion, Cultura y Deporte", through the "Ayudas para contratos predoctorales de Formacion del Profesorado Universitario FPU (Convocatoria 2014)". Grant number FPU14/02953. This work has been partially supported by the "Conselleria de Educacion, Investigacion, Cultura y Deporte", through the "Subvenciones para la contratacion de personal investigador de caracter (Convocatoria 2017)".Grant number ACIF/2017/069.Parra-Boronat, L.; Rocher-Morant, J.; Escrivá-Perales, J.; Lloret, J. (2018). Design and development of low cost smart turbidity sensor for water quality monitoring in fish farms. Aquacultural Engineering. 81:10-18. https://doi.org/10.1016/j.aquaeng.2018.01.004S10188

Development of Inductive Sensor for Control Gate Opening of an Agricultural Irrigation System

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] The monitoring of water level in the agriculture irrigation channels is essential to control the opening gates of these channels. In this way, WSNs (Wireless Sensor Networks) have high relevance to obtain this kind of data. In this paper, we propose a sensor to measure the depth changes in irrigation channels to control the gates opening. It is connected to an Adafruit Feather HUZZAH based on ESP8266, which allows us to build a mobile edge computing system. The developed sensor is based on two coils. Sinus-wave powers the first one, and the second is induced. The coils are winding over a polyvinyl chloride (PVC) that has high resistance for corrosion and low price. Besides, we use copper wire as a conductive metal. We test two different configurations of coils. P1 has five spires for the powered coil (PC) and ten spires for the induced coil (IC). On the other hand, P2 has 40 spires for the PC and 80 spires for the IC. The two prototypes were coiled in one layer. Then, both sensors are tested using a glass bottle where the water column increased with the target to obtain the information of the depth. In both prototypes, the difference of voltage between the maximum and minimum studied depths is more or less the same, 4.46V for P1 and 4.44V for P2. Nevertheless, during the stabilization test, the P1 showed better adaptation for the turbulences than the P2. The P1 shows an oscillation of 0.48V, where the P2 has a maximum fluctuation of 3.2V.This work has been partially supported by European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) project ERANETMED3-227 SMARTWATIR 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, and through the "Ayudas para contratacion predoctoral de Formacion del Profesorado Universitario FPU (Convocatoria 2016)". Grant number FPU16/05540.Basterrechea-Chertudi, DA.; Rocher-Morant, J.; Parra-Boronat, L.; Lloret, J. (2020). Development of Inductive Sensor for Control Gate Opening of an Agricultural Irrigation System. IEEE. 250-255. https://doi.org/10.1109/FMEC49853.2020.9144810S25025

Testing Existing Prototypes of Conductivity Sensors for Monitoring the Concentration of Organic Fertilizers in Fertigation Systems

[EN] Agricultural production has grown in recent years, increasing the use of Organic Fertilizers (OF). For that reason, the use of these compounds must be controlled in fertigation water. In this paper, we test three prototypes, using different combinations of coils, to determine the amount of OF in the water. A coil is powered by a sine wave of 3.3 peak-to-peak Volts for inducing another coil. The objective of this system is to detect different kinds of problems that can cause incorrect fertilization, which affects the sustainability of agriculture. We present the tests to verify the proper functioning of the prototypes. We test our prototypes by means of different dilutions of OF. The used concentrations of OF are between 0 and 20 g/l. We measure the conductivity for each concentration and the output voltage of our prototypes. The results show that prototype 3 is the one that has the best performance, obtaining 1.47 V of difference between the maximum and minimum output voltage and a good correlation coefficient. Finally, a verification test is carried out; the average error in the different samples tested is 0.2212%.This work has been partially supported by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) project ERANETMED3-227 SMARTWATIR, by ¿Ministerio de Educación, Cultura y Deporte¿, through the ¿Ayudas para contratacion pre-doctoral de Formación del Profesorado Universitario FPU (Convocatoria 2016)¿. Grant number FPU16/05540, and by Conselleria de Educación, Cultura y Deporte with the Subvenciones para la contratación de personal investigador en fase postdoctoral, grant number APOSTD/2019/04.Basterrechea-Chertudi, DA.; Rocher-Morant, J.; Parra-Boronat, L.; Lloret, J. (2020). Testing Existing Prototypes of Conductivity Sensors for Monitoring the Concentration of Organic Fertilizers in Fertigation Systems. IARIA XPS Press. 50-55. http://hdl.handle.net/10251/178037S505

Low-Cost System Based on Optical Sensor to Monitor Discharge of Industrial Oil in Irrigation Ditches

[EN] Uncontrolled dumping linked to agricultural vehicles causes an increase in the incorporation of oils into the irrigation system. In this paper, we propose a system based on an optical sensor to monitor oil concentration in the irrigation ditches. Our prototype is based on the absorption and dispersion of light. As a light source, we use Light Emitting Diodes (LEDs) with different colours (white, yellow, blue, green, and red) and a photodetector as a sensing element. To test the sensor's performance, we incorporate industrial oils used by a diesel or gasoline engine, with a concentration from 0 to 0.20 mL(oil)/cm(2). The experiment was carried out at different water column heights, 0 to 20 cm. According to our results, the sensor can differentiate between the presence or absence of diesel engine oil with any LED. For gasoline engine oil, the sensor quantifies its concentration using the red light source; concentrations greater than 0.1 mL(oil)/cm(2) cannot be distinguished. The data gathered using the red LED has an average absolute error of 0.003 mL(oil)/cm(2) (relative error of 15.8%) for the worst case, 15 cm. Finally, the blue LED generates different signals in the photodetector according to the type of oil. We developed an algorithm that combines (i) the white LED, to monitor the presence of oil; (ii) the blue LED, to identify if the oil comes from a gasoline or diesel engine; and (iii) the red LED, to monitor the concentration of oil used by a gasoline engine.This work is partially funded by the "Ayudas para contratacion pre-doctoral de Formacion del Profesorado Universitario FPU (Convocatoria 2016)" grant number FPU16/05540. 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.Basterrechea-Chertudi, DA.; Rocher-Morant, J.; Parra-Boronat, L.; Lloret, J. (2021). Low-Cost System Based on Optical Sensor to Monitor Discharge of Industrial Oil in Irrigation Ditches. Sensors. 21(16):1-21. https://doi.org/10.3390/s21165449S121211

A WSN-based monitoring system to control Sewerage

[EN] The sewerage is a critical infrastructure in cities because of the drainage of the urban runoff and the evacuation of the wastewater. Two types of sewerage, separated sewerage and combined sewerage, can be differentiated. In this paper, we show the application of a level sensor and a rain sensor for monitoring the separated sewerage. The level sensor is used for knowing if there is a critical level of water in the sewerage. The rain sensor is used to know if it is raining. The combination of this information allows the identification of three scenarios. These scenarios are normal situation, low drainage and illicit discharge/blockages in the pipeline. In addition, we study the use of sensors and mathematical models for monitoring the velocity of the wastewater. We concluded that the use of mathematical models is a good option for monitoring the velocity. Because with exception of the thermal sensors the other types of sensors show important gaps. The velocity is used to estimate the flow that is dumping in the water bodies. We use an ESP32 board program with Arduino IDE for data collection and sending the data to a server on the same network via Wi-Fi. The server is a computer that processes the data. We present the programming code and the ports that should be used for transmitting the data from Arduino to computer server.Supported by European Union through the project ERANETMED3-227 SMARTWATIR by the Ministerio de Educación, Cultura y Deporte. Grant number FPU16/05540Rocher-Morant, J.; García-Navas, JL.; Romero Martínez, JO.; Lloret, J. (2019). A WSN-based monitoring system to control Sewerage. IEEE. 277-282. https://doi.org/10.1109/IOTSMS48152.2019.8939269S27728

Development of a Low-Cost Optical Sensor to Detect Eutrophication in Irrigation Reservoirs

[EN] In irrigation ponds, the excess of nutrients can cause eutrophication, a massive growth of microscopic algae. It might cause different problems in the irrigation infrastructure and should be monitored. In this paper, we present a low-cost sensor based on optical absorption in order to determine the concentration of algae in irrigation ponds. The sensor is composed of 5 LEDs with different wavelengths and light-dependent resistances as photoreceptors. Data are gathered for the calibration of the prototype, including two turbidity sources, sediment and algae, including pure samples and mixed samples. Samples were measured at a different concentration from 15 mg/L to 4000 mg/L. Multiple regression models and artificial neural networks, with a training and validation phase, are compared as two alternative methods to classify the tested samples. Our results indicate that using multiple regression models, it is possible to estimate the concentration of alga with an average absolute error of 32.0 mg/L and an average relative error of 11.0%. On the other hand, it is possible to classify up to 100% of the samples in the validation phase with the artificial neural network. Thus, a novel prototype capable of distinguishing turbidity sources and two classification methodologies, which can be adapted to different node features, are proposed for the operation of the developed prototype.This work is partially funded by the Ministerio de Educacion, Cultura y Deporte through the"Ayudas para contratacion pre-doctoral de Formacion del Profesorado Universitario FPU (Convocatoria 2016)" grant number FPU16/05540 and by the Conselleria de Educacion, Cultura y Deporte through the "Subvenciones para la contratacion de personal investigador en fase postdoctoral", grant number APOSTD/2019/04.Rocher-Morant, J.; Parra-Boronat, L.; Jimenez, JM.; Lloret, J.; Basterrechea-Chertudi, DA. (2021). Development of a Low-Cost Optical Sensor to Detect Eutrophication in Irrigation Reservoirs. Sensors. 21(22):1-20. https://doi.org/10.3390/s21227637S120212

Practical Study of the Temperature Effect in Soil Moisture Measurements

[EN] Precision agriculture is a current tendency whose goal is to increase the crop production while reducing the water and fertilization use. The use of low cost sensors and Wireless Sensor Networks (WSNs) are frequently used to implement complex systems to control the irrigation process in crops. Taking into account the importance of developing these low cost systems, in this paper we present a practical study that compares a commercial soil moisture sensor with the prototype of our inductive soil moisture sensor, which is based on two solenoid coils. Additionally, we measure its performance as a function of the soil temperature to quantify the effect of this parameter in the sensor measurements. The results show that the temperature greatly affects the sensors measurements and, although our sensor could be used to measure the soil moisture as a function of the temperature, the configuration of two solenoids is not the most suitable to perform this kind of measurementsThis work has been partially supported by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities 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.García-Navas, JL.; Parra-Boronat, M.; Parra-Boronat, L.; Rocher-Morant, J.; Sendra, S.; Lloret, J. (2019). Practical Study of the Temperature Effect in Soil Moisture Measurements. IARIA XPS Press. 7-13. http://hdl.handle.net/10251/180616S71

Ceratophyllum demersum L. as Phytoindicator and Potential Phytoremediator of Lead Under Hydroponic Conditions

[EN] The contamination of water by heavy metals like Pb is a huge problem for the environment. In this paper, we test Ceratophyllum demersum L. plants as phytoindicator. These were exposed to different concentrations of Pb for 1¿21 days, under hydroponic conditions, where they exhibited both adsorption and absorption efficiency. These efficiencies influenced in concentration and duration in a dependent manner. For the three initial treatments 0.125, 0.250, 0.500 ¿g/ml, the values of regression coefficients described the occurred variance on the rapid decrease in the Pb concentration in the hydroponic media, reflecting highest removal efficiency by C. demersum. Significant variation (P< 0.05) was recorded between the concentration of Pb accumulated in C. demersum at 0.125 and 0.250 ¿g/ml, while a highly significant value (P< 0.01) was recorded between them at 0.500 ¿g/ml. The regression coefficient denotes the pronounced impact of treatment concentration on the accumulation rate (R^2 = 0.9987). The adsorption efficiency of C. demersum appeared to be influenced by the Pb hydroponic media concentration, where after 21 days, the higher Pb adsorption was recorded at 0.125 ¿g/ml and the lowest one was obtained at 0.500 ¿g/ml. Results suggest that plants responded positively to the increase of Pb concentrations and they accumulated a high amount of metal. Due to metal removal coupled with detoxification potential, the plant appears to have potential for its use as phytoremediator species in aquatic environments.This work has been partially supported by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities 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.Fawzy, M.; El-Khatib, A.; Badr, N.; Abo-El-Kasem, A.; Rocher-Morant, J.; Basterrechea-Chertudi, DA. (2019). Ceratophyllum demersum L. as Phytoindicator and Potential Phytoremediator of Lead Under Hydroponic Conditions. IARIA XPS Press. 20-26. http://hdl.handle.net/10251/180618S202

Design and Calibration of Moisture Sensor Based on Electromagnetic Field Measurement for Irrigation Monitoring

[EN] Soil moisture control is crucial to assess irrigation efficiency in green areas and agriculture. In this paper, we propose the design and calibration of a sensor based on inductive coils and electromagnetic fields. The proposed prototypes should meet a series of requirements such as low power consumption, low relative error, and a high voltage difference between the minimum and maximum moisture. We tested different prototypes based on two copper coils divided into two different sets (P1-P15 and NP1-NP4). The prototypes have different characteristics: variations in the number and distribution of spires, existence or absence of casing, and copper wires with a diameter of 0.4 or 0.6 mm. In the first set of experiments carried out in commercial soil, the results showed that the best prototypes were P5, P8, and P9. These prototypes were used in different types of soils, and P8 was selected for the subsequent tests. We carried the second set of experiments using soil from an agricultural field. Based on the data gathered, mathematical models for the calibration of prototypes were obtained and verified. In some cases, two equations were used for different moisture intervals in a single prototype. According to the verification results, NP2 is the best prototype for monitoring the moisture in agricultural lands. It presented a difference in induced voltage of 1.8 V, at 500 kHz, between wet and dry soil with a maximum voltage of 5.12 V. The verification of the calibration determined that the calibration using two mathematical models offers better results, with an average absolute error of 2.1% of moisture.This work is funded by the European Union under ERANETMED (Euro-Mediterranean Cooperation through ERANET joint activities and beyond), project ERANETMED3-227 SMARTWATIR and the European Union, MAPA and Comunidad de Madrid (through IMIDRA), under the project PDR18-XEROCESPED of the PDR-CM 2014-2020 (operative programme of the European Agriculture Fund for Rural Development, EAFRD). L.P. is funded by Conselleria de Educacion, Cultura y Deporte, programme Subvenciones para la contratacion de personal investigador en fase postdoctoral, grant APOSTD/2019/04; J.R. by the Ministerio de Educacion, Cultura y Deporte, through the "Ayudas para contratacion pre-doctoral de Formacion del Profesorado Universitario FPU (Convocatoria 2016)" grant number FPU16/05540; and M.P. by the Universitat Politecnica de Valencia through the pre-doctoral PAID-01-20 programme.Basterrechea-Chertudi, DA.; Rocher-Morant, J.; Parra-Boronat, M.; Parra-Boronat, L.; Marín, JF.; Mauri, PV.; Lloret, J. (2021). Design and Calibration of Moisture Sensor Based on Electromagnetic Field Measurement for Irrigation Monitoring. Chemosensors. 9(9):1-32. https://doi.org/10.3390/chemosensors9090251S1329

Urban Lawn Monitoring in Smart City Environments

[EN] Control over water usage for irrigation purposes is a key factor in order to achieve the sustainability in agriculture. The irrigation of urban lawns represents a high percentage of the urban water usage. The use of information and communication technology (ICT) offers the possibility of monitoring the grass state in order to adjust the irrigation regime. In this paper, we propose an Arduino-based system with a camera set on a drone. The drone flies along the garden taking pictures of the grass. Those pictures are processed with a rule-based algorithm that classifies them according to the grass quality. Pictures can be tagged in three categories: high coverage, low coverage, or very low coverage. After designing our algorithm, twelve pictures are used to verify its correct operation. The results show a 100% hit rate. To analyze the suitability of using drones to perform this task, we carried out a comparative study for gardens with different sizes, where the drone and a similar system mounted on a small autonomous vehicle have been used. The results show that, for gardens bigger than 1000 m(2), the use of drone is needed due to the time consumed by the vehicle to cover the entire surface. Finally, we show the results of sending the image information after processing it in different manners.This work has been partially supported by the "Conselleria de Educacion, Investigacion, Cultura y Deporte," through the "Subvenciones para la contratacion de personal investigador de caracter (Convocatoria 2017)" Grant no. ACIF/2017/069. Finally, the research leading to these results has received funding from "la Caixa" Foundation and Triptolemos Foundation.Marín, J.; Parra-Boronat, L.; Rocher-Morant, J.; Sendra, S.; Lloret, J.; Mauri Ablanque, PV.; Masaguer, A. (2018). Urban Lawn Monitoring in Smart City Environments. Journal of Sensors. 2018. https://doi.org/10.1155/2018/8743179S201