A Novel Methodology for Monitoring and Controlling of Water Quality in Aquaculture using Internet of Things (IoT)

Food security is an issue that arises as a result of the rising population since population growth decreases agricultural land, leading to water scarcity. Agriculture requires large amounts of water, but water scarcity forces farmers to irrigate their crops with little or low-quality water, leading to the idea of developing smart irrigation. The challenge is how to manage the interactions between plants, growing media, microclimate, and water using manufactured systems. Good irrigation management will minimize the occurrence of poor irrigation design. This review is a way to present various methods and approaches for using sensors, controllers, the Internet of Things, and artificial intelligence in irrigation systems with a focus on improving water use efficiency. The study uses SCOPUS indexed publications and proceedings to study the evolution of irrigation information technology over the last eleven years. We hope this review can serve as a source of information to broaden the validity of the findings of irrigation monitoring and control technologies and help researchers identify future research directions on this subject.

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“…Overexploitation of natural resources, rapid industrial development, and agricultural expansion are the leading causes of the problem. [72].…”

Section: Water Quality-basedmentioning

confidence: 99%

An overview of IoT based intelligent irrigation systems for greenhouse: Recent trends and challenges

Ardiansah

Bafdal²,

Bono

et al. 2022

J Appl Eng Science

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“…A hardware is made for monitoring water quality factors including pH, temperature, and dissolved oxygen [11]. An IoT device is proposed for detecting and controlling the water factors including pH, temperature; however, they did not analyze the data [12]. A regression model is utilized for predicting water quality of cultivating fish; however, they did not consider the prediction accuracy [13].…”

Section: Literature Reviewmentioning

confidence: 99%

Fish survival prediction in an aquatic environment using random forest model

Islam

Kashem

Uddin

2021

IJ-AI

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In the real world, it is very difficult for fish farmers to select the perfect fish species for aquaculture in a specific aquatic environment. The main goal of this research is to build a machine learning that can predict the perfect fish species in an aquatic environment. In this paper, we have utilized a model using random forest (RF). To validate the model, we have used a dataset of aquatic environment for 11 different fishes. To predict the fish species, we utilized the different characteristics of aquatic environment including pH, temperature, and turbidity. As a performance metrics, we measured accuracy, true positive (TP) rate, and kappa statistics. Experimental results demonstrate that the proposed RF-based prediction model shows accuracy 88.48%, kappa statistic 87.11% and TP rate 88.5% for the tested dataset. In addition, we compare the proposed model with the state-of-art models J48, RF, k-nearest neighbor (k-NN), and classification and regression trees (CART). The proposed model outperforms than the existing models by exhibiting the higher accuracy score, TP rate and kappa statistics.

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“…Some of the recent papers have underlined different aspects of the implementation of IoT WQMS [3]- [5]. Most of them use inefficient data transfer protocols providing high energy consumption and spectrum exploitation, requiring frequent system maintenance and being non-scalable by their nature [6], [7].…”

Section: Introductionmentioning

confidence: 99%

On the Development of Long-Range Water Quality Monitoring System for Outdoor Aquaculture Objects

Pikuļins

Gotlaufs

Solovjova

et al. 2022

Electrical, Control and Communication Engineering

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The paper is dedicated to the development of hardware and software components for the autonomous water quality monitoring system (WQMS) for fishing farms. The system can measure main water quality parameters, storing and processing data on the remote server. The LoRaWAN technological solutions and infrastructure are utilized, providing the optimal tradeoff between data transmission range and adaptive power consumption. The main implementation and exploitation issues are described, and the proposed solutions are provided.

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A Novel Methodology for Monitoring and Controlling of Water Quality in Aquaculture using Internet of Things (IoT)

Cited by 32 publications

References 4 publications

An overview of IoT based intelligent irrigation systems for greenhouse: Recent trends and challenges

An overview of IoT based intelligent irrigation systems for greenhouse: Recent trends and challenges

Fish survival prediction in an aquatic environment using random forest model

On the Development of Long-Range Water Quality Monitoring System for Outdoor Aquaculture Objects

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