Design and deployment of a smart system for data gathering in aquaculture tanks using wireless sensor networks

[EN] The design of monitoring systems for marine areas has increased in the last years. One of the many advantages of wireless sensor networks is the quick process in data acquisition. The information from sensors can be processed, stored, and transmitted using protocols efficiently designed to energy saving and establishing the fastest routes. The processing and storing of data can be very useful for taking intelligent decisions for improving the water quality. The monitoring of water exchange in aquaculture tanks is very important to monitor the fish welfare. Thus, this paper presents the design, deployment, and test of a smart data gathering system for monitoring several parameters in aquaculture tanks using a wireless sensor network. The system based on a server is able to request and collect data from several nodes and store them in a database. This information can be postprocessed to take efficient decisions. The paper also presents the design of a conductivity sensor and a level sensor. These sensors are installed in several aquaculture tanks. The system was implemented using Flyport modules. Finally, the data gathering system was tested in terms of consumed bandwidth and the delay Transmission Control Protocol (TCP) packets delivering data from the sensors.This work has been partially supported by the Postdoctoral Scholarship “Contratos Postdoctorales UPV 2014 (PAID‐ 10‐14)” of the “Universitat Politècnica de València,” by the “Programa para la Formación de Personal Investigador— (FPI‐2015‐S2‐884)” of the “Universitat Politècnica de València,” and by the pre‐doctoral student grant “Ayudas para contratos predoctorales de Formación del Profesorado Universitario FPU (Convocatoria 2014)” Reference: FPU14/ 02953 by the “Ministerio de Educación, Cultura y Deporte,” by Instituto de Telecomunicações, Next Generation Networks and Applications Group (NetGNA), and Covilhã Delegation, by the National Funding from the FCT—Fundação para a Ciência e a Tecnologia through the UID/EEA/500008/2013 Project, by the Government of Russian Federation, Grant 074‐U01, and by Finep, with resources from Funttel, Grant No. 01.14.0231.00, under the Radiocommunication Reference Center (Centro de Referência em Radiocomunicações —CRR) project of the National Institute of Telecommunications (Instituto Nacional de Telecomunicações—Inatel), Brazil.Parra-Boronat, L.; Sendra, S.; Lloret, J.; Rodrigues, JJPC. (2017). Design and deployment of a smart system for data gathering in aquaculture tanks using wireless sensor networks. International Journal of Communication Systems. 30(16):1-15. https://doi.org/10.1002/dac.3335S115301

Study of Requirements and Design of Sensors for Monitoring Water Quality and Feeding Process in Fish Farms and Other Environments

Se están realizando muchos esfuerzos en la acuicultura para alcanzar la sostenibilidad, sin embargo aún está lejos de ser sostenible. Sus impactos sobre el medio ambiente pueden prevenirse y corregirse mediante el uso de sensores, desarrollando la conocida como acuicultura de precisión. La calidad del agua afecta el rendimiento de los peces. La temperatura y la salinidad son algunos factores que afectan al crecimiento de los peces. Sin embargo, otros factores como la turbidez, el fotoperíodo y el oxígeno disuelto entre otros pueden afectar a las necesidades nutritivas de los peces. Ajustar la cantidad de alimento necesario es crucial para garantizar la sostenibilidad de la acuicultura y para aumentar el beneficio económico de las instalaciones. Al monitorear la calidad del agua, es posible estimar las necesidades de alimentación. Sin embargo, no es suficiente. El monitoreo del comportamiento de los peces, especialmente durante el período de alimentación, puede ayudar a adaptar el alimento proporcionado. Entonces, si está tan claro que el monitoreo puede ayudar a la producción acuícola, ¿por qué no vemos este sistema de monitoreo en las instalaciones acuícolas? ¿Por qué en la mayoría de las instalaciones la alimentación se da manualmente sin considerar el comportamiento de alimentación de los peces? El precio de los sensores para monitorizar las piscifactorías es extremadamente alto. Los sensores empleados son, en la mayoría de los casos, los mismos que se utilizan para la oceanografía. Los sistemas propuestos en la literatura cubren pocos parámetros de calidad del agua y generalmente no consideran el comportamiento de alimentación de los peces. Son necesarios sensores de bajo costo adecuados para la monitorización de la acuicultura. Esos sensores deben ser de bajo costo, bajo consumo de energía, fáciles de usar y con la posibilidad de incluirlos en una red para enviar los datos. Por lo tanto, podremos utilizar esta red de sensores y sensores para controlar la actividad, enviar alarmas si es necesario y automatizar los procesos. Además, si incluimos Internet, los datos se pueden ver de forma remota. El uso de esos sensores puede ayudar a la producción acuícola. En esta tesis mostramos el estudio de los requisitos y el diseño de sensores para monitorizar la calidad del agua y el proceso de alimentación en piscifactorías y otros entornos. Primero estudiamos en detalle los requisitos de los sensores en acuicultura. Luego mostramos el estado del arte de los sensores actuales para el monitoreo de la calidad del agua y para el monitoreo de la acuicultura. A continuación, presentamos el diseño y desarrollo de nuestros propios sensores de bajo costo y su aplicación en instalaciones de piscifactorías con sistema abierto y sistema de recirculación. Además, mostramos la posibilidad de monitorizar hasta 10 parámetros incluyendo calidad del agua (temperatura, salinidad, turbidez y presencia de hidrocarburo / capa de aceite), ambiente del tanque (nivel de agua, iluminación, presencia de trabajadores) y comportamiento de alimentación de peces (profundidad de natación de bajura, estimación de los cambios en la velocidad de nado de bajíos y la caída de alimento). El sistema propuesto, capaz de monitorear todos estos parámetros, tiene un bajo coste y bajo consumo de energía. El precio estimado es inferior a 100 € por tanque. Además, mostramos el uso de algunos de los sensores antes mencionados para el ajuste automático del proceso de alimentación de peces. Finalmente, mostramos como algunos de los sensores desarrollados se utilizan en otras áreas acuáticas naturales como manglares y estuarios. Además, se presenta un sistema inteligente para monitorear y rastrear la contaminación en los cuerpos de agua.There are many efforts done in the aquaculture to reach its sustainability, although in reality, it is far from being sustainable. Its negative impacts on the environment can be prevented and corrected by the use of sensors, developing precision aquaculture. The water quality affects to the fish performance. The temperature and salinity are some factors that affect to the fish growth. Nevertheless, other factors such as turbidity, photoperiod and dissolved oxygen among other can affect to the fish feeding needs. To adjust the amount of feed needed is crucial to ensure the sustainability of the aquaculture and to increase the economic profit of the facilities. Monitoring the water quality allows estimating the feed needs. However, it is not enough. To monitor the fish behavior, especially during the feeding period can help to adapt the provided feed. Then, if it is so clear that the monitoring can help to the aquaculture production, why we do not see this monitoring systems in the aquaculture facilities? Why in most of the facilities the feed is given manually without considering the fish feeding behavior? Nevertheless, the current price of the sensors for monitoring the fish farms is extremely high. The employed sensors are in most of the cases, the same that are used for oceanography. The proposed systems in the literature only cover some water quality parameters and usually do not consider fish feeding behavior. It is need low-cost sensors suitable for aquaculture monitoring. Those sensors must also be low-energy consumption, easy to use and with the option to include them in a network in order to send the data. Thus, we can use these sensors and sensors network to monitor the activity, to send alarms if it is necessary and to automatize processes. Moreover, including Internet, the data can be seen remotely. The use of those sensors can help to the aquaculture production. In this thesis, we show the study of requirements and design of sensors for monitoring water quality and feeding process in fish farms and other environments. First, we study in detail the requirements of sensors in aquaculture. Then, we show the state of the art of the current sensors for water quality monitoring and for aquaculture monitoring. Following, we present the design and development of some low-cost sensors and their applications in fish farm facilities with open system and recirculating system. Moreover we show a complete system which monitors up to 10 parameters including water quality (temperature, salinity, turbidity and presence of hydrocarbon/oil layer), tank environment (water level, illumination, presence of workers), and fish feeding behavior (shoal swimming depth, estimation of changes on shoal swimming velocity and feed falling). Moreover, it accomplishes the features of low-cost and low energy consumption. The estimated price for proposed system is less than 100€ per tank. In addition, we show the use of some of the aforementioned sensors for automatic adjustment of fish feeding process. Finally, some of the developed sensors are plied in other natural aquatic areas such as mangroves, and estuaries. Moreover, an intelligent system for pollution monitoring and tracking in water bodies are presented.S'estan realitzant molts esforços en l'aqüicultura per assolir la sostenibilitat, malgrat això, encara està lluny de ser sostenible. Els seus impactes sobre el medi ambient es poden prevenir i corregir mitjançant l'ús de sensors, desenvolupant la coneguda com a aqüicultura de precisió. La qualitat de l'aigua afecta el rendiment dels peixos. La temperatura i la salinitat són alguns factors que afecten el creixement dels peixos. A més a més, altres factors com la terbolesa, el fotoperíode i l'oli dissolt entre uns altres poden afectar a les necessitats nutritives dels peixos. Ajustar la quantitat d'aliment necessari és crucial per garantir la sostenibilitat de l'aqüicultura i per augmentar el benefici econòmic de les instal·lacions. Al monitoritzar la qualitat de l'aigua, és possible estimar les necessitats d'alimentació. No obstant això, no és suficient. Monitoritzar el comportament dels peixos, especialment durant el període d'alimentació, pot ajudar a adaptar el subministrament alimentari. Aleshores, si es tan clar que el monitoratge pot ajudar a la producció aqüícola, per què no veiem aquest sistema de monitoratge en les instal·lacions aquàtiques? Per què a la majoria de les instal·lacions la alimentació es dóna manualment sense considerar el comportament alimentari dels peixos? El preu dels sensors per controlar les piscifactories és extremadament alt. Els sensors empleats són, en la majoria dels casos, els mateixos que es fan servir per a l'oceanografia. Els sistemes proposats en la literatura monitoritzen pocs paràmetres de qualitat de l'aigua i generalment no consideren el comportament dels peixos durant l'alimentació. Són necessaris sensors de baix cost adequats per a la monitorització de l'aqüicultura. Aquests sensors han de ser de baix cost, baix consum d'energia, senzills d'usar i amb la possibilitat d'incloure'ls en una xarxa per enviar-los. Per tant, podrem utilitzar aquesta xarxa de sensors i sensors per controlar l'activitat, enviar alarmes si és necessari i automatitzar els processos. A més, si incloem Internet, les dades es podran veure de forma remota. L'ús d'aquests sensors pot ajudar a la producció aqüícola. En aquesta tesi es mostra l'estudi dels requisits i el disseny de sensors per a monitoritzar la qualitat de l'aigua i el procés d'alimentació en piscifactories i altres entorns. Primer, estudiem en detall els requisits dels sensors en aqüicultura. A continuació, es mostra el estat de l'art dels sensors actuals per al monitoratge de la qualitat de l'aigua i per al monitoratge de l'aqüicultura. A continuació, presentem el disseny i desenvolupament dels nostres propis sensors de baix cost i la seva aplicació en instal·lacions d'aqüicultura amb sistema obert i sistema de recirculació. A més, mostrem la possibilitat de monitoritzar fins a 10 paràmetres, incloent-hi la qualitat de l'aigua (temperatura, salinitat, terbolesa i presència d'hidrocarburs / capa d'oli), ambient del tanc (nivell d'aigua, il·luminació, presència de treballadors) i alimentació del consum de peces (profunditat de natació de baix, estimació dels canvis en la velocitat de naixement de baixos i la caiguda d'aliment). El sistema proposat, capaç de controlar tots aquests paràmetres, té un baix cost i baix consum d'energia. El preu estimat és inferior a 100 € per tanc. A més, mostrem l'ús d'alguns dels sensors abans esmentats per a l'ajust automàtic del procés d'alimentació de peces. Finalment, mostrem com alguns dels sensors desenvolupats es fan servir en altres àrees aquàtiques naturals com manglars i estuaris. A més, es presenta un sistema intel·ligent per monitoritzar i rastrejar la contaminació en els cossos d'aigua.Parra Boronat, L. (2018). Study of Requirements and Design of Sensors for Monitoring Water Quality and Feeding Process in Fish Farms and Other Environments [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/106369TESI

Water Contaminants Detection Using Sensor Placement Approach in Smart Water Networks

Incidents of water pollution or contamination have occurred repeatedly in recent years, causing significant disasters and negative health impacts. Water quality sensors need to be installed in the water distribution system (WDS) to allow real-time water contamination detection to reduce the risk of water contamination. Deploying sensors in WDS is essential to monitor and detect any pollution incident at the appropriate time. However, it is impossible to place sensors on all nodes of the network due to the relatively large structure of WDS and the high cost of water quality sensors. For that, it is necessary to reduce the cost of deployment and guarantee the reliability of the sensing, such as detection time and coverage of the whole water network. In this paper, a dynamic approach of sensor placement that uses an Evolutionary Algorithm (EA) is proposed and implemented. The proposed method generates a multiple set of water contamination scenarios in several locations selected randomly in the WDS. Each contamination scenario spreads in the water networks for several hours, and then the proposed approach simulates the various effect of each contamination scenario on the water networks. On the other hand, the multiple objectives of the sensor placement optimization problem, which aim to find the optimal locations of the deployed sensors, have been formulated. The sensor placement optimization solver, which uses the EA, is operated to find the optimal sensor placements. The effectiveness of the proposed method has been evaluated using two different case studies on the example of water networks: Battle of the Water Sensor Network (BWSN) and another real case study from Madrid (Spain). The results have shown the capability of the proposed method to adapt the location of the sensors based on the numbers and the locations of contaminant sources. Moreover, the results also have demonstrated the ability of the proposed approach for maximising the coverage of deployed sensors and reducing the time to detect all the water contaminants using a few numbers of water quality sensor

Design and Deployment of Low-Cost Sensors for Monitoring the Water Quality and Fish Behavior in Aquaculture Tanks during the Feeding Process

The monitoring of farming processes can optimize the use of resources and improve its sustainability and profitability. In fish farms, the water quality, tank environment, and fish behavior must be monitored. Wireless sensor networks (WSNs) are a promising option to perform this monitoring. Nevertheless, its high cost is slowing the expansion of its use. In this paper, we propose a set of sensors for monitoring the water quality and fish behavior in aquaculture tanks during the feeding process. The WSN is based on physical sensors, composed of simple electronic components. The system proposed can monitor water quality parameters, tank status, the feed falling and fish swimming depth and velocity. In addition, the system includes a smart algorithm to reduce the energy waste when sending the information from the node to the database. The system is composed of three nodes in each tank that send the information though the local area network to a database on the Internet and a smart algorithm that detects abnormal values and sends alarms when they happen. All the sensors are designed, calibrated, and deployed to ensure its suitability. The greatest efforts have been accomplished with the fish presence sensor. The total cost of the sensors and nodes for the proposed system is less than 90  .This work has been partially supported by the “Ministerio de Educación, Cultura y Deporte”, through the “Ayudas para contratos predoctorales de Formación del Profesorado Universitario FPU (Convocatoria 2014)”. Grant number FPU14/02953. The research leading to these results has received funding from “la Caixa” Foundation and Triptolemos Foundation

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

LoRa-based Network for Water Quality Monitoring in Coastal Areas

[EN] Agriculture Farming activity near to rivers and coastal areas sometimes imply spills of chemical and fertilizers products in aquifers and rivers. These spill highly affect the water quality in rivers' mouths and beaches close to those rivers. The presence of these elements can worse the quality for its normal use, even for its enjoying. When this polluted water reaches the sea can also have problematic consequences for fauna and flora. For this reason, it is important to rapidly detect where these spills are taking place and where the water does not have the minimum of quality to be used. In this article we propose the design and implementation of a LoRa (Long Range) based wireless sensor network for monitoring the quality of water in coastal areas, rivers and ditches with the aim to generate an observatory of water quality of the monitored areas. This network is composed by several wireless sensor nodes endowed with several sensors to physically measure parameters of water quality, such as turbidity, temperature, etc., and weather conditions such as temperature and relative humidity. The data collected by the sensors is sent to a gateway that forwards them to our storage database. The database is used to create an observatory that will permit the monitoring of the environment where the network is deployed. We test different devices to select the one that presents the best performance. Finally, the final solution is tested in a real environment for checking its correct operation. Two different tests will be carried out. The first test checks the correct operation of sensors and the network architecture while the second test show us the devices performance in terms of coverage.Sendra, S.; Parra-Boronat, L.; Jimenez, JM.; García-García, L.; Lloret, J. (2023). LoRa-based Network for Water Quality Monitoring in Coastal Areas. Mobile Networks and Applications (Online). 28(1):65-81. https://doi.org/10.1007/s11036-022-01994-8658128

Physical Sensors for Precision Aquaculture: A Review

(c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this[EN] Aquaculture is presented as a sustainable method to provide fish, although in reality, it is far from being sustainable. Its negative impacts on the environment can be prevented and corrected by the use of sensors, developing precision aquaculture. Sensors are widely used in terrestrial applications, but in underwater environments, their use is constrained by a variety of issues. The aim of this paper is to describe the state-of-the-art of the underwater sensors for water quality monitoring. First, the requirements and challenges of underwater sensors for aquaculture monitoring are discussed in detail. The main challenges are the need of a waterproof isolation or the need to avoid corrosion and biofouling, among others. Second, there are some advantages compared with the terrestrial applications, such as no need of minimized systems or the fact that such systems only require low accuracy. Subsequently, we evaluated the different options available to sense each variable, related to the needs of the aquaculture sensors. For temperature monitoring, thermistors, thermocouples or RTC seem to offer similar advantages. In contrast, for dissolved oxygen monitoring, the optical method seems to be the best option. For turbidity, optical methods are the most employed ones, while for conductivity measurements, the inductive coils are a promising option.This work was supported by the pre-doctoral student grant "Ayudas para contratos predoctorales de Formacion del Profesorado Universitario FPU (Convocatoria 2014)" with reference: FPU14/02953 by the Ministerio de Educacion, Cultura y Deporte.Parra-Boronat, L.; Lloret Mauri, G.; Lloret, J.; Rodilla, M. (2018). Physical Sensors for Precision Aquaculture: A Review. IEEE Sensors Journal. 18(10):3915-3923. https://doi.org/10.1109/JSEN.2018.2817158S39153923181

Utilization Of A Large-Scale Wireless Sensor Network For Intrusion Detection And Border Surveillance

To control the border more effectively, countries may deploy a detection system that enables real-time surveillance of border integrity. Events such as border crossings need to be monitored in real time so that any border entries can be noted by border security forces and destinations marked for apprehension. Wireless Sensor Networks (WSNs) are promising for border security surveillance because they enable enforcement teams to monitor events in the physical environment. In this work, probabilistic models have been presented to investigate senor development schemes while considering the environmental factors that affect the sensor performance. Simulation studies have been carried out using the OPNET to verify the theoretical analysis and to find an optimal node deployment scheme that is robust and efficient by incorporating geographical coordination in the design. Measures such as adding camera and range-extended antenna to each node have been investigated to improve the system performance. A prototype WSN based surveillance system has been developed to verify the proposed approach

Controlo remoto de um sistema de aquacultura

Mestrado em Engenharia MecânicaThis thesis covers the automated aquaculture scenario around the world and speci cally Portugal. With research done, a case study and laboratory work, the goal is to create a reliable remote control system capable of not only controlling the physical variables within an aquaculture system but monitor and rectify unwanted situations.Esta tese trata-se de aquacultura pelo mundo e Portugal especi camente. Com uma pesquisa feita, um "case study" e trabalho laboratorial, o objetivo é criar um sistema de controlo remoto capaz de controlar as variáveis físicas dentro de um sistema de aquacultura e monitorizar e reti car situações indesejadas

Digital Twinning of Hydroponic Grow Beds in Intelligent Aquaponic Systems

The use of automation, Internet-of-Things (IoT), and smart technologies is being rapidly introduced into the development of agriculture. Technologies such as sensing, remote monitoring, and predictive tools have been used with the purpose of enhancing agriculture processes, aquaponics among them, and improving the quality of the products. Digital twinning enables the testing and implementing of improvements in the physical component through the implementation of computational tools in a ‘twin’ virtual environment. This paper presents a framework for the development of a digital twin for an aquaponic system. This framework is validated by developing a digital twin for the grow beds of an aquaponics system for real-time monitoring parameters, namely pH, electroconductivity, water temperature, relative humidity, air temperature, and light intensity, and supports the use of artificial intelligent techniques to, for example, predict the growth rate and fresh weight of the growing crops. The digital twin presented is based on IoT technology, databases, a centralized control of the system, and a virtual interface that allows users to have feedback control of the system while visualizing the state of the aquaponic system in real time