Reservoir Aquaculture Anti-theft System based on Convolutional Neural Network

Abstract

This paper proposes an Anti-theft system for reservoir aquaculture based on convolutional neural network, including front-end acquisition equipment cloud server and terminal monitoring equipment. The system mainly uses the convolutional neural network image processing unit of the infrared sensor module to find and identify the people who invaded the reservoir, and issue a warning through the audio input and output module, and warn the reservoir manager of the reservoir situation through the terminal monitoring equipment. The purpose is to use the convolutional neural network to flexibly feed back the real-time anti-intrusion dynamics of the reservoir to the reservoir manager, reduce its unnecessary monitoring time, and reduce the input of labor costs.