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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.