Smart Aquaculture: Integration of Sensors, Biosensors, and Artificial Intelligence

Sharma, Dolly; Kumar, Ranjit

doi:10.1007/978-3-030-66165-6_21

Cited by 11 publications

(9 citation statements)

References 40 publications

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“…Through the deployment of advanced sensors, we aim to capture and analyze key parameters such as pH, dissolved oxygen, temperature, turbidity and nutrient levels in real-time. This continuous monitoring allows for a proactive approach to maintaining optimal water conditions, mitigating the risk of adverse effects on aquatic organisms [3].…”

Section: A Real Time Water Quality Monitoringmentioning

confidence: 99%

Real Time Water Quality Based Predictive Alert System for Aquaculture

Devanaboina

2024

IJRASET

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Aquaculture plays a crucial role in addressing the growing worldwide need for seafood. Nevertheless, maintaining ideal water conditions is vital for the well-being and efficiency of aquatic organisms. This initiative presents a holistic remedy for aquaculture activities: the creation of a real time water quality based predictive alert system. This system places specific emphasis on monitoring five crucial parameters: temperature, pH, and dissolved oxygen (DO), Nitrate, Turbidity. It utilizes strategically positioned sensors to provide real-time data. Through advanced analysis and deep learning models, it predicts potential issues, send alerts to the aquatic manager enabling them to proactively optimize conditions, improve aquatic health, and minimize economic losses

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Section: A Real Time Water Quality Monitoringmentioning

confidence: 99%

Real Time Water Quality Based Predictive Alert System for Aquaculture

Devanaboina

2024

IJRASET

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“…Traditional farming as in aquaculture may pose problems with the manual and management operations and the sustainability and/or maintenance of water quality parameters as well (Hu et al, 2019;Eze and Ajmal, 2020;Vo et al, 2021;Rashid et al, 2021). Such existing problems in traditional aquaculture may be solved in a smart aquaculture approach, that is, if several smart devices (Sharma and Kumar, 2021) and other technologies are integrated such as IoT, and artificial intelligence (Imai et al, 2019;Kassem et al, 2021), big data, 5G, cloud computing, and robotics. These technologies would allow a system to be operated automatically, manage facilities and machinery therein and real-time monitor water quality parameters such as temperature, dissolved oxygen, humidity, light and pH.…”

Section: Technological Innovations In Urban Farmingmentioning

confidence: 99%

An Assessment of the Control and Monitoring Functionalities of a Developed Small-Scale Aquaculture System

2022

Int. J. Biosci.

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In smart aquaculture, devices and technologies are integrated to facilitate automated operations, manage facilities and machinery and maintain water quality parameters. This study aimed at assessing control and monitoring functionalities in an automated small-scale aquaculture system. In this work, the requirements to sustain aquaculture systems such as light intensity, humidity, water temperature and dissolved oxygen have been considered in the selection of appropriate sensors for monitoring and control. The controls of the system were able to maintain proper light intensity, water temperature, and humidity. Water aeration also provided enough dissolved oxygen into the system. The outcome of this work indicated the performance and testing of the different sensors for monitoring and controlling parameters to sustain the automated aquaculture system. It can be recommended to include in the study other important parameters such as pH, oxidation-reduction potential, and salinity, among others. It can be recommended to provide more water heaters for fast water heating in the system. And if the system is being applied to a naturally hot area, a cooling study or assessment may also be made.

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“…An intelligent IoT based Aquaculture system can help the farmers by measuring the water parameters continuously using modern IoT sensors in order to monitor and maintain the quality of water, Hence, measuring all the water parameters for the bio floc aquaculture and also a water quality prediction [3] model for the dynamic changes in water parameters are essential. The IoT sensors measure and collect water parameters accurately and transmit them to the base station host computer.…”

Section: Introductionmentioning

confidence: 99%

Smart Prediction of Water Quality System for Aquaculture using Machine Learning Algorithms

Sen¹,

Maiti²,

Manna³

et al. 2023

Preprint

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<p>This article focuses on the importance of the continuous collection of water parameters data from the sensors and also the prediction of water quality using the latest different Machine learning algorithms like Logistic Regression, Random Forest, Support Vector Machine, Decision Tree, K-nearest Neighbour, XGBoost, Gradient Boosting and Naive Bayes. These Machine learning models are implemented and tested to validate and achieve a satisfactory result of water quality prediction in terms of different attributes like pH, hardness, Solids, Chloramines, Sulfate, Conductivity, organic carbon, trihalomethanes, Turbidity and potability.</p>

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Smart Aquaculture: Integration of Sensors, Biosensors, and Artificial Intelligence

Cited by 11 publications

References 40 publications

Real Time Water Quality Based Predictive Alert System for Aquaculture

Real Time Water Quality Based Predictive Alert System for Aquaculture

An Assessment of the Control and Monitoring Functionalities of a Developed Small-Scale Aquaculture System

Smart Prediction of Water Quality System for Aquaculture using Machine Learning Algorithms

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