Open AccessResearch on the Water Quality Intelligent Monitoring System of River Gushing Based on Federal Learning
Author(s) -
Jiasong Zhu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2010/1/012150
Subject(s) - automation , computer science , quality (philosophy) , water quality , identification (biology) , field (mathematics) , convolutional neural network , artificial intelligence , engineering , ecology , philosophy , botany , mathematics , epistemology , pure mathematics , biology , mechanical engineering
Intelligent video surveillance technology is increasingly widely used in social production and life and plays an important role in economic development and environmental protection. This paper focuses on the field of water quality monitoring, and aims at the problems of traditional river gushing including difficulty of water quality monitoring, poor timeliness and insufficient automation, and proposes the intelligent water quality monitoring method from the perspective of intelligent image treatment. A federated learning system combined with a NVIDIA Jetson TX2 edge nodes is constructed by HD cameras deployed at various monitoring points of the gushing. On this basis, based on the convolutional neural network technology, the identification and monitoring of the river gushing water quality can effectively reduce the operation amount and water quality monitoring automation degree under the case of ensuring the accuracy.