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      Implementation of Whale Optimization for Budding Healthiness of Fishes with Preprocessing Approach

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          Abstract

          This article examines distinctive techniques for monitoring the condition of fishes in underwater and also provides tranquil procedures after catching the fishes. Once the fishes are hooked, two different techniques that are explicitly designed for smoking and drying are implemented for saving the time of fish suppliers. Existing methods do not focus on the optimization algorithms for solving this issue. When considering the optimization problem, the solution is adequate for any number of inputs at time t. For this combined new flanged technique, a precise system model has been designed and incorporated with a set of rules using contention protocols. In addition, the designed system is also instigated with a whale optimization algorithm that is having sufficient capability to test the different parameters of assimilated sensing devices using different sensors. Further to test the effectiveness of the proposed method, an online monitoring system has been presented that can monitor and in turn provides the consequences using a simulation model for better understanding. Moreover, after examining the simulation results under three different scenarios, it has been observed that the proposed method provides an enhancement in real-time monitoring systems for an average of 78%.

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          Most cited references17

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          The Whale Optimization Algorithm

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            Tracking Fish Abundance by Underwater Image Recognition

            Marine cabled video-observatories allow the non-destructive sampling of species at frequencies and durations that have never been attained before. Nevertheless, the lack of appropriate methods to automatically process video imagery limits this technology for the purposes of ecosystem monitoring. Automation is a prerequisite to deal with the huge quantities of video footage captured by cameras, which can then transform these devices into true autonomous sensors. In this study, we have developed a novel methodology that is based on genetic programming for content-based image analysis. Our aim was to capture the temporal dynamics of fish abundance. We processed more than 20,000 images that were acquired in a challenging real-world coastal scenario at the OBSEA-EMSO testing-site. The images were collected at 30-min. frequency, continuously for two years, over day and night. The highly variable environmental conditions allowed us to test the effectiveness of our approach under changing light radiation, water turbidity, background confusion, and bio-fouling growth on the camera housing. The automated recognition results were highly correlated with the manual counts and they were highly reliable when used to track fish variations at different hourly, daily, and monthly time scales. In addition, our methodology could be easily transferred to other cabled video-observatories.
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              Fish Processing Wastes as a Potential Source of Proteins, Amino Acids and Oils: A Critical Review

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                Author and article information

                Contributors
                Journal
                J Healthc Eng
                J Healthc Eng
                JHE
                Journal of Healthcare Engineering
                Hindawi
                2040-2295
                2040-2309
                2022
                2 February 2022
                : 2022
                : 2345600
                Affiliations
                1Department of Artificial Intelligence, G.H. Raisoni College of Engineering, Nagpur, India
                2Department of Electronics and Communication Engineering, Audisankara College of Engineering and Technology, Gudur, Andhra Pradesh, India
                3Mechanical Engineering Department, College of Engineering, King Khalid University, Abha 61411, Asir, Saudi Arabia
                4Civil Engineering Department, College of Engineering, King Khalid University, Abha 61411, Asir, Saudi Arabia
                5MCA Department, GL BAJAJ Institute of Technology & Management, Greater Noida, India
                6Department of Computer Science and Engineering, CT Group of Institute (CTIEMT), Shahpur, I.K.Gujral Punjab Technical University, Jalandhar, Pin 144603, India
                7Department of Information Technology, Kongu Engineering College, Perundurai, Tamilnadu, India
                8G.H. Raisoni College of Engineering, Nagpur, India
                9Center of Excellence for Bioprocess and Biotechnology, Department of Chemical Engineering, College of Biological and Chemical Engineering, Addis Ababa Science and Technology University, Addis Ababa, Ethiopia
                Author notes

                Academic Editor: Enas Abdulhay

                Author information
                https://orcid.org/0000-0002-7381-6284
                https://orcid.org/0000-0003-1101-6051
                Article
                10.1155/2022/2345600
                8828318
                931343f1-535a-43cd-a126-4e74618cc101
                Copyright © 2022 Pravin R. Kshirsagar et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 12 November 2021
                : 14 December 2021
                : 18 December 2021
                Funding
                Funded by: King Khalid University
                Award ID: RGP.2/58/42
                Categories
                Review Article

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