An Integrated Wireless Multi-Sensor System for Monitoring the Water Quality of Aquaculture (original) (raw)

IoT-Based Real-Time Aquaculture Health Monitoring System

European Journal of Electrical Engineering and Computer Science

Aquaculture fastest growing business worldwide especially in developing countries. Fisheries are marine species and required an oceanic environment where fisheries could grow and live naturally. Off-shore aquaculture businesses need a real-time water quality monitoring system. So, aquafarmers could maintain the required environment for a sustainable and profitable business. This work represents an IoT-based realtime health management system designed for aquaculture and considered the most required health metrics for aquaculture. The proposed system used four primary sensors: water level, temperature, pH, and dissolved oxygen. Sensors connected with microcontroller Arduino Uno R3 and ESP 8266 wi-fi module are used for data transmission to the IoT source ThingSpeak. The designed system could access online through the web interface and phone App for aquafarmers. The sensor data was accurate, and the system worked as designed.

Design and implementation of a distributed IoT system for the monitoring of water quality in aquaculture

2017 Wireless Telecommunications Symposium (WTS), 2017

In this work we present the prototype and proof of concept of a distributed monitoring system of the most important variables in aquaculture water quality. This is of great importance because aquaculture is a lagging area of technology compared to other areas such as agriculture. So it is important to solve the problems that are in this area with the support of technology. Among the problems is the slow response time in the care of water quality, the waste of resources and losses. The system proposed in this work monitors the water quality based on wireless sensor networks and on the Internet of Things (IoT). This information is important for the development of this area, since it allows sharing the different conditions in the breeding of aquatic organisms between different breeders and organizations. This information is useful to know the conditions in which there is a better development of a product, worse development, what conditions can mean a possible disaster in the environment and how to optimize resources for the care of the pond.

Application of the Internet of Things technology (IoT) in Designing an Automatic Water Quality Monitoring System for Aquaculture Ponds

Vietnam Journal of Agricultural Sciences, 2020

The current aims to apply the Internet of Things technology (IoT) in designing an automatic system for measuring and monitoring important parameters of aquaculture ponds such as temperature, pH, and dissolved oxygen (DO). The system includes the Arduino Nano main microcontroller (the device that transmits and pushes data to the Raspberry Pi 3 Web server), the DS18B20 temperature sensor module, the pH sensor module V1.1, and the DO Sensor SKU SEN0237. The system is capable of continuously measuring the above parameters of aquaculture ponds. The measurement results are stored and transmitted wirelessly to smart devices such as computers and mobile phones. Farmers can continuously monitor water quality parameters of aquaculture ponds (pH, DO, temperature) through these smart devices. In addition, a warning message will be sent to the farmer's phone when the DO index of the aquaculture pond falls below the prescribed level. The results of the test evaluation also show the high accur...

Smart measurement and monitoring system for aquaculture fisheries with IoT-based telemetry system

Bulletin of Electrical Engineering and Informatics

The instrumentation design of an online monitoring device for aquaculture media is discussed in this article. The main processor in this internet of things (IoT) real-time telemetry system is an ESP32 board. Temperature, acidity level, conductivity level, dissolved oxygen (DO) level, and degree of oxygen reduction in the water were the aquaculture parameters measured. The ESP32 collects data from each sensor, groups it into a dataset, displays it on the LCD, saves it to the SD card, and then uploads it to the real-time database. In addition, an Android application is being developed for users. This device has been tested to ensure that each measured parameter is accurate and precise. The accuracy test, one of the major results of laboratory scale tests, demonstrates that each parameter has a different measurement error that represents with average error absolute. Six tested sensors/instruments were subjected to the test. Average absolute error for temperature sensor is +0.76%, pH sensor is +1.52%, electrical conductivity (EC) sensor is +10.8%, oxidation reduction potential (ORP) sensor is +14.6%, DO sensor is +9.3%, and total dissolve solids (TDS) sensor is +13.2%. This device is very dependable and convenient for monitoring the condition of aquaculture media in real-time and accurately.

Iot-Based Monitoring of Aquaculture System

MATTER: International Journal of Science and Technology, 2020

Aquaculture is considered to be a station of interest in many different countries, including Malaysia, which has started on developing its aquaculture system since the 1920s. The two main reasons behind this interest are the great food source for locals and a very good source of income that can help in amazingly increasing the economy of a country, so aquaculture should be well-taken care of, especially, in terms of water quality. Therefore, the main focus and goal of this paper are measuring the water quality parameters that can suit many types of aquacultural living species, especially the fish species. Five sensors are positioned in a one-tone fish tank to measure and monitor the water parameters' fluctuations, especially during the feeding time. These smart sensors are a waterproof temperature sensor, water PH sensor, water turbidity sensor, air temperature sensor, and light sensor. These sensors are connected to an Arduino board, which sends the collected data from sensors to the GSM and then to Thing speak cloud, which is an easy way to monitor data fluctuations 24 hours a day. As a result, the collected data of water parameters seem to be slightly fluctuating which does not affect the health of the fish in the tank. The reason of choosing these sensors is to also illustrate the statistical correlation between air temperature and water temperature, light intensity and turbidity, turbidity and PH, especially during feeding time. These IoT sensors are very cheap to

Analysis and Development of IoT-based Aqua Fish Monitoring System

International Journal of Emerging Technology and Advanced Engineering

Water quality is critical in fish farming activities, where criteria must be measured to ensure water quality. Unwanted amounts of water quality factors will affect aquatic life. It has been discovered that some breeders fail to maintain their ponds, causing water quality to worsen and affecting fish hibernation and mortality. Manual pond water quality testing was ineffective and time-consuming, causing the water quality to suffer. This study created a fishpond IoT system to monitor a pond's water quality, temperature, pH level, and ammonia toxicity. A real-time data analytics platform was created to collect data from the water temperature, pH level, and toxicity of ammonia sensors embedded into the IoT system. The NodeMCU ESP32 controller was used to process the data collected from all sensors, and real-time data may be viewed via mobile devices using the Blynk application. Three sensors are embedded to the system which are an ammonia gas sensor, an analog pH sensor, and a temp...

Aqua Fishing Monitoring System Using IoT Devices

2019

In this age of world, everything is going to fourth revolution of industries. According to this, Bangladesh is going to be prompt in every sector. In this paper, we have proposed a system of cultivating fish farming using IoT devices. After simulating design, we implement it by hardware. Here we use water temperature, turbidity, PH, Water Level, CO3 gas. The objective of this research is to design and develop a real-time smart-based water temperature, PH and turbidity monitoring system. The system implementation resulted in a monitoring system that collects the current water temperature, PH, turbidity from the core-controller in real-time. Also, the system provides and displays information that includes normal range, maximum, minimum, average and findings of the collected data which figured by thing speak IoT analytics platform. It provides decision support to assist and guide fisher folks in avoiding distress to grow fish and obtaining the optimum water monitoring data such as temperature, ph and turbidity range.

Water Quality Monitoring and Control System for Fish Farmers Based on Internet of Things

Ingénierie des systèmes d'information/Ingénierie des systèmes d'Information, 2024

Numerous individuals in Riau Province are engaged in the fish cultivation due to the province's ample water supply and the substantial market demand, which generates relatively high selling prices. The significance of water quality issues in fish aquaculture stems from the fact that fish inhabit water. Water quality is determined by a number of parameters, including acidity, temperature, turbidity, and the quantity of dissolved substances. Therefore, this study aimed to develop a device capable of monitoring water quality. The water parameters observed through the utilization of sensors and the Internet of Things were temperature, acidity, dissolved solids concentration, and turbidity. Utilizing the Rapid Application Development (RAD) Method, the research was completed through the following phases: Analysis, design, development, evaluation, implementation, and simulation. A device comprised of electronic components, including a microcontroller and sensors, was the result of this research. Monitoring parameter data was collected in real time via sensors and subsequently stored on a cloud server. The tools developed as a consequence of this research enable fish producers to acquire parameter data in real time. These tools serve the purpose of generating responses to normalize water quality and to facilitate action in response to changes in water quality.

Water Quality Monitoring System with Parameter of pH, Temperature, Turbidity, and Salinity Based on Internet of Things

JISA(Jurnal Informatika dan Sains), 2021

This research aims to monitor the quality of water used for aquariums. The physical parameters used are water pH, water temperature, water turbidity, and water salinity. Using a pH sensor, temperature sensor, turbidity sensor, and salinity conductivity sensor with Arduino as the controller. The prototype method used in this research, starting from the formulation, research, building stages to testing and evaluating the results of the research. The working process of the system is when the system is activated, the sensors will detect and capture the amount of value contained in the water, then the data from the sensor is sent to a database in the cloud using an ethernet shield that is connected to the media router as a liaison for the internet network then displayed on the website dashboard in the form of graphs and monitoring record tables in real time. The sensors function to detect water quality, where quality standards have been set in this system, namely temperature standards of...

Smart Aquaculture: IoT-Enabled Monitoring and Management of Water Quality for Mahseer Fish Farming

Seventh Sense Research Group®, 2024

Aquaculture is essential for meeting the growing global demand for seafood by cultivating aquatic species in controlled environments such as ponds and tanks. This study presents an innovative IoT-based water quality monitoring system designed specifically for Mahseer fish farming. The system utilizes an ESP32 Development Board equipped with sensors to monitor water quality parameters and employs the Blynk 2.0 platform for real-time data visualization. A C/C++ algorithm managed through the Arduino IDE facilitates effective communication between the sensors and the microcontroller. The results demonstrate the system's effectiveness in maintaining optimal water conditions, enabling early detection and timely intervention for potential issues. This approach enhances the sustainability and efficiency of Mahseer fish farming. Future research will focus on refining accuracy, improving scalability, and integrating advanced data analytics to boost predictive capabilities and promote more efficient and profitable aquaculture practices.