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Scalable real-time position detection based on overlapping neural networks
Scalable real-time position detection based on overlapping neural networks
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机译:基于重叠神经网络的可扩展实时位置检测
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摘要
A method for real-time location detection consists of three groups of components. Mobile subjects to be tracked are equipped with wireless transceivers capable of sending and optionally for receiving data over pre-determined radio frequency (RF) band(s). Router/base station access point devices are equipped with wireless transceivers capable of sending and receiving data over pre-determined radio frequency (RF) band(s) in order to communicate with mobile units. Routers are combined into specific overlapping router groups, with each group forming a spatial sub-network. System central processing and command station(s) perform data processing and implementation of computational models that determine the mobile unit location. System deployment consists of three phases: collection of training and testing data, network training and testing, and network adaptive maintenance.
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