The rapid advancement of sensor network technology has paved the way for socioeconomic applications in all areas. Similarly, the addition of new sensors for various characteristics expands the data collecting and manipulation possibilities for making valuable judgments. In order to fully harness the ocean environment’s most underutilised resources, researchers must first identify a sensor network suitable for monitoring fish movements and then determine the most likely area for data exchange beneath. The paper’s main goal is to monitor and evaluate fish movement and behaviour in underwater sensor networks by developing a novel algorithm named AFISH [ARTIFICIAL FISH], which will examine the movement and behaviour of fish in the water using specific parameters. The behaviour is observed using particular under water sensors set along the length, breadth, and depth of the earmarked area, and the information is observed and modified with the help of data fusion to understand the data communication area and the best time for it . The simulation results reveal that under certain assumed conditions, the suggested AFISH algorithm for fish movement monitoring is effective.
Author (S) Details
S. A. Kalaiselvan
Department of Computer Science and Engineering, TKR College of Engineering and Technology, Telangana, India.
Department of AI and ML, School of Engineering, Malla Reddy University, Telangana, India.
Department of Computer Science and Engineering, Symbiosis University of Applied Sciences, Indore, Madhya Pradesh, India.
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