Enhanced Water Quality Control Based on Predictive Optimization for Smart Fish Farming

作     者：Azimbek Khudoyberdiev Mohammed Abdul Jaleel Israr Ullah DoHyeun Kim 

作者机构：Department of Applied InformaticsKimyo International University in TashkentTashkent100121Uzbekistan Department of Computer ScienceVirtual University of PakistanLahore54000Pakistan Department of Computer EngineeringJeju National UniversityJeju63243Korea 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2023年第75卷第6期

页      面：5471-5499页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 0801[工学-力学（可授工学、理学学位）] 

基　　金：funded by the Ministry of Science,ICT CMC,202327(2019M3F2A1073387) this work was supported by the Institute for Information&communications Technology Promotion(IITP)(NO.2022-0-00980,Cooperative Intelligence Framework of Scene Perception for Autonomous IoT Device) 

主　　题：Smart fish farming internet of things(IoT) predictive optimization objective function fuzzy logic control(FLC) 

摘      要：The requirement for high-quality seafood is a global challenge in today’s world due to climate change and natural resource *** of Things(IoT)based Modern fish farming systems can significantly optimize seafood production by minimizing resource utilization and improving healthy fish *** objective requires intensive monitoring,prediction,and control by optimizing leading factors that impact fish growth,including temperature,the potential of hydrogen(pH),water level,and feeding *** paper proposes the IoT based predictive optimization approach for efficient control and energy utilization in smart fish *** proposed fish farm control mechanism has a predictive optimization to deal with water quality control and efficient energy consumption *** farm indoor and outdoor values are applied to predict the water quality parameters,whereas a novel objective function is proposed to achieve an optimal fish growth environment based on predicted *** logic control is utilized to calculate control parameters for IoT actuators based on predictive optimal water quality parameters by minimizing energy *** evaluate the efficiency of the proposed system,the overall approach has been deployed to the fish tank as a case study,and a number of experiments have been carried *** results show that the predictive optimization module allowed the water quality parameters to be maintained at the optimal level with nearly 30%of energy efficiency at the maximum actuator control rate compared with other control levels.