Analysis of Behavior Trajectory Based on Deep Learning in Ammonia Environment for Fish

Ammonia can be produced by the respiration and excretion of fish during the farming process, which can affect the life of fish. In this paper, to research the behavior of fish under different ammonia concentration and make the corresponding judgment and early warning for the abnormal behavior of fis...

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Bibliographic Details
Main Authors: Wenkai Xu, Zhaohu Zhu, Fengli Ge, Zhongzhi Han, Juan Li
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/16/4425
Description
Summary:Ammonia can be produced by the respiration and excretion of fish during the farming process, which can affect the life of fish. In this paper, to research the behavior of fish under different ammonia concentration and make the corresponding judgment and early warning for the abnormal behavior of fish, the different ammonia environments are simulated by adding the ammonium chloride into the water. Different from the existing methods of directly artificial observation or artificial marking, this paper proposed a recognition and analysis of behavior trajectory approach based on deep learning. Firstly, the three-dimensional spatial trajectories of fish are drawn by three-dimensional reconstruction. Then, the influence of different concentrations of ammonia on fish is analyzed according to the behavior trajectory of fish in different concentrations of ammonia. The results of comparative experiments show that the movement of fish and vitality decrease significantly, and the fish often stagnates in the water of containing ammonium chloride. The proposed approach can provide a new idea for the behavior analysis of animal.
ISSN:1424-8220