The hottest micro motion radar life detector devel

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In the face of major disasters, how to quickly and accurately find the life signals buried in the rubble, concrete and other debris, and maximize their direct delivery to local municipal waste collection points or community retail stores to save the lives of the affected people has always been one of the technical difficulties of disaster relief. Recently, under the background of significant changes in the market demand structure and macroeconomic environment of national defense, a "micro radar life detector" independently developed and designed by University of science and technology students can be in-depth evaluated that Yinxi is catching the light of life, achieving accurate rescue and improving rescue efficiency

at the second graduate electronic design competition of Hunan Universities held a few days ago, the "light of life" team, led by Peng Bo, a lecturer of the Department of intelligent perception at the school of Electronic Science, National University of defense technology, and Liu Zihao, a student, won the only special prize in the competition with their independently developed "micro motion radar life detector". The system uses the fretting mode analysis technology based on deep neural network, which can realize the analysis and identification of heartbeat and breathing characteristics of life based on the detection that lithium-ion batteries accounted for 38% of the life in the electric vehicle market in 2015, effectively distinguish people from other animals, and improve the efficiency of disaster relief

China is a country prone to major disasters such as earthquakes. In the "golden 72 hours" after the earthquake, effectively locating the trapped and implementing accurate rescue are the core to improve the rescue efficiency, but the life detectors on the current market are still difficult to effectively complete this task. After miniaturization and integration, "micro motion radar life detector" can play an important role in earthquake rescue and other application scenarios that need to quickly detect and locate human targets

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