Long lasting underwater wireless sensors network for water quality monitoring in fish farms

Cario, Gianni; Casavola, Alessandro; Lupia, Petrika Gjanci Marco; Petrioli, Chiara; Spaccini, Daniele

doi:10.1109/oceanse.2017.8084777

Cited by 43 publications

(29 citation statements)

References 7 publications

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“…In recent years, advancements in different Information and Communication Technologies (ICT) along with the development of low-cost small sensors have increased the feasibility of monitoring numerous parameters concurrently through wireless sensor networks (WSN). The applications of WSN include the monitoring of the three vigor [14], greenhouses [15], citrus crops [16], the state of farm animals (goats [17] or cows [18]), and fish farms [19][20][21][22][23][24][25]. WSN is composed of many self-organized sensors deployed in a monitoring region that measure, collect, transmit, and process information in real time.…”

Section: Wirelessmentioning

confidence: 99%

“…Numerous studies have been conducted to study and develop WSN for use in aquaculture [21][22][23][24][25]. Most of these technologies boost the ability to measure the majority of the important physical parameters in real-time and the capability of informing the necessary people at the facility whenever a problem arises, allowing for quick and immediate resolution.…”

Section: Wirelessmentioning

confidence: 99%

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Sensors, Biosensors, and Analytical Technologies for Aquaculture Water Quality

Sutarlie

Loh

2020

Research

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In aquaculture industry, fish, shellfish, and aquatic plants are cultivated in fresh, salt, or brackish waters. The increasing demand of aquatic products has stimulated the rapid growth of aquaculture industries. How to effectively monitor and control water quality is one of the key concerns for aquaculture industry to ensure high productivity and high quality. There are four major categories of water quality concerns that affect aquaculture cultivations, namely, (1) physical parameters, e.g., pH, temperature, dissolved oxygen, and salinity, (2) organic contaminants, (3) biochemical hazards, e.g., cyanotoxins, and (4) biological contaminants, i.e., pathogens. While the physical parameters are affected by climate changes, the latter three are considered as environmental factors. In this review, we provide a comprehensive summary of sensors, biosensors, and analytical technologies available for monitoring aquaculture water quality. They include low-cost commercial sensors and sensor network setups for physical parameters. They also include chromatography, mass spectrometry, biochemistry, and molecular methods (e.g., immunoassays and polymerase chain reaction assays), culture-based method, and biophysical technologies (e.g., biosensors and nanosensors) for environmental contamination factors. According to the different levels of sophistication of various analytical techniques and the information they can provide (either fine fingerprint, highly accurate quantification, semiquantification, qualitative detection, or fast screening), we will comment on how they may be used as complementary tools, as well as their potential and gaps toward current demand of real-time, online, and/or onsite detection.

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Section: Wirelessmentioning

confidence: 99%

Section: Wirelessmentioning

confidence: 99%

Sensors, Biosensors, and Analytical Technologies for Aquaculture Water Quality

Sutarlie

Loh

2020

Research

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“…Such large scale UAN deployments will have a wide range of applications, e.g. water quality monitoring [5], seismic monitoring [6], marine animal tracking [7], off-shore asset monitoring [8], and ocean exploration using autonomous underwater vehicles (AUVs) [9]. However, compared with terrestrial radio systems, the performance of UANs is severely limited by the adverse characteristics of the underwater acoustic (UWA) communication medium [10]: extremely slow propagation (sound speed is approximately 1500 m/s), low available bandwidth (typically on the order of several kHz), large multipath delay spread and Doppler effect.…”

Section: Introductionmentioning

confidence: 99%

Channel Modeling for Underwater Acoustic Network Simulation

Morozs¹,

Gorma²,

Henson³

et al. 2020

Preprint

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This manuscript was submitted to IEEE Access on 12 Jun 2020.<div><br></div><div>Abstract:</div><div><br></div><div>Simulation forms an important part of the development and empirical evaluation of underwater acoustic network (UAN) protocols. The key feature of a credible network simulation model is a realistic channel model. A common approach to simulating realistic underwater acoustic (UWA) channels is by using specialised beam tracing software such as BELLHOP. However, BELLHOP and similar modeling software typically require knowledge of ocean acoustics and a substantial programming effort from UAN protocol designers to integrate it into their research. In this paper, we bridge the gap between low level channel modeling via beam tracing and automated channel modeling, e.g. via the World Ocean Simulation System (WOSS), by providing a distilled UWA channel modeling tutorial from the network protocol design point of view. The tutorial is accompanied by our MATLAB simulation code that interfaces with BELLHOP to produce channel data for UAN simulations. As part of the tutorial, we describe two methods of incorporating such channel data into network simulations, including a case study for each of them: 1) directly importing the data as a look-up table, 2) using the data to create a statistical channel model. The primary aim of this paper is to provide a useful learning resource and modeling tool for UAN protocol researchers. Initial insights into the UAN protocol design and performance provided by the statistical channel modeling approach presented in this paper demonstrate its potential as a powerful modeling tool for future UAN research.<br></div>

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“…Furthermore, the system was able to alarm users when the fish disease was propagated to provide treatment. Cario et al (2017) a water quality monitoring system for fish farms. The system was composed of SUNSET (Software Defined Communication Stack) for networking purposes and Hydrolab Series 5 probes for data acquisition.…”

Section: Monitoring Systems For Fish Farmsmentioning

confidence: 99%

“…We are planning to develop the platform to view the data as it was shown in (Khaleeq et al, 2016) with LabVIEW and include the artificial intelligence for diagnosis with the data from the database as it was done in (Chen et al, 2017). We also plan to apply this system to underwater cages as it was done in (Cario et al, 2017) To close the section, a system to adjust the feed supply velocity was presented. The sensors shown in this section can be used to improve the efficiency of the aquaculture feeding process.…”

Section: Título Del Gráficomentioning

confidence: 99%

Study of requirements and design of sensors for monitoring water quality and feeding process in fish farms and other environments

Boronat¹

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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 develop...

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Long lasting underwater wireless sensors network for water quality monitoring in fish farms

Cited by 43 publications

References 7 publications

Sensors, Biosensors, and Analytical Technologies for Aquaculture Water Quality

Sensors, Biosensors, and Analytical Technologies for Aquaculture Water Quality

Channel Modeling for Underwater Acoustic Network Simulation

Study of requirements and design of sensors for monitoring water quality and feeding process in fish farms and other environments

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