A wild animal monitoring and analyzing system and method based on a deep convolutional neural network

Abstract

The invention discloses a wild animal wireless monitoring analysis system and method based on a deep convolutional neural network. Image data of a moving object is acquired and a database is established; image calibration and preprocessing are performed; the deep convolutional neural network is trained in combination with an Adam optimization algorithm; wild animals are detected and identified; the appearance time of wild animals is prolonged; statistical analysis is carried out on places and a model is established; the problem of high labor intensity in the traditional method is solved; Artificial analysis time consumption is long, it is difficult to analyze and obtain the current situation of wild animal resources and the accurate situation of dynamic changes due to a large amount of redundant information and false identification information is solved, researchers can remotely obtain the individual characteristics and population distribution situation of wild animals in a monitored area in real time, and the working efficiency and the accuracy of analysis results are improved.

Description

technical field [0001] The invention relates to the field of protection and monitoring of the ecological environment and animals and plants, in particular to a wireless monitoring and analysis system and method for wild animals based on a deep convolutional neural network. Background technique [0002] As an indispensable part of the ecological chain, wild animals play an important role in biodiversity. The protection of wild animals not only plays an important role in maintaining the balance and stability of the ecosystem, but also plays an important role in the survival and development of human beings. significance. Scientific and effective wildlife monitoring is the primary prerequisite for the protection of wildlife resources, which requires real-time acquisition of wild animal picture information and geographic location information during wildlife monitoring, and through these information to obtain the species information, Quantitative information and habitat condition...

AI Technical Summary

Problems solved by technology

[0005] In view of this, the purpose of the present invention is to propose a wild animal analysis monitoring analysis system and method based on a deep convolutional neural network, which solves the problem of high labor intensity, long time-consuming manual analysis, and a large amount of redundant information and errors in the traditional method. Identification information, it is difficult to analyze and obtain accurate information on the status and dynamic changes of wild animal resources

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