Automatic monitoring system and method of wild animal based on deep learning technology

Abstract

The invention relates to the technical field of the ecological monitoring, and especially an automatic monitoring system of a wild animal based on deep learning technology. A controller module is arranged in a data collecting end, the controller module is electrically connected with a sound collection module, an image collection module, a communication module, an accumulator module and an execution module, and the execution module is further electrically connected with the sound collection module and the image collection module; a processor is arranged in a data analysis end, and the processoris electrically connected with a video image analysis module, the sound analysis module, a storage module, a display module, an operation module, an interaction module and a data transceiver. The system for monitoring the wild animal has high accuracy, the monitoring method is convenient for deployment and simple in configuration, the wild animal monitoring process is greatly simplified, and themonitoring efficiency is improved.

Description

technical field [0001] The invention relates to the technical field of ecological monitoring, in particular to an automatic monitoring system and method for wild animals based on deep learning technology. Background technique [0002] In the field of ecological monitoring, the monitoring of wild animals has always been a very time-consuming and laborious work. Staff often need to track and count animals in a certain area, but this work is often difficult to complete. On the one hand, it is difficult to track traces of wild animals. On the other hand, in order to track traces of wild animals, staff may be required Dozens of days or even months of squatting, the efficiency is very low. Sometimes, the staff will use cameras in certain areas to record whether there are traces of wild animals, but the real-time performance of this is relatively low, and it often requires staff to go to the scene to obtain monitoring data. [0003] On the other hand, the accuracy of traditional ...

AI Technical Summary

Problems solved by technology

[0002] In the field of ecological monitoring, the monitoring of wild animals has always been a very time-consuming and laborious work

Staff often need to track and count animals in a certain area, but this work is often difficult to complete. On the one hand, it is difficult to track traces of wild animals. On the other hand, in order to track traces of wild animals, staff may be required Dozens of days or even months of squatting, the efficiency is very low

Sometimes, the staff will use cameras in some areas to record whether there are traces of wild animals, but the real-time performance of this is relatively low, and often requires staff to go to the scene to obtain monitoring data

[0003] On the other hand, the accuracy of traditional image recognition technology and business recognition technology is relatively low, but in recent years, deep learning technology has developed rapidly, and very good progress has been made in image recognition and voice recognition.

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