Most studies on device-free localization currently focus on single-person scenarios.This paper proposes a novel method for device-free localization that utilizes ZigBee received signal strength indication(RSSI)and a T...Most studies on device-free localization currently focus on single-person scenarios.This paper proposes a novel method for device-free localization that utilizes ZigBee received signal strength indication(RSSI)and a Transformer network structure.The method aims to address the limited research and low accuracy of two-person device-free localization.This paper first describes the construction of the sensor network used for collecting ZigBee RSSI.It then examines the format and features of ZigBee data packages.The algorithm design of this paper is then introduced.The box plot method is used to identify abnormal data points,and a neural network is used to establish the mapping model between ZigBee RSSI matrix and localization coordinates.This neural network includes a Transformer encoder layer as the encoder and a fully connected network as the decoder.The proposed method's classification accuracy was experimentally tested in an online test stage,resulting in an accuracy rate of 98.79%.In conclusion,the proposed two-person localization system is novel and has demonstrated high accuracy.展开更多
随着科学技术的不断发展,危险品实验室的安全问题日益引起人们的关注。为了提高实验室的安全性,基于射频识别(Radio Frequency Identification,RFID)技术和紫蜂协议(ZigBee)技术设计了一种危险品实验室安全监测系统,以提高实验室的安全...随着科学技术的不断发展,危险品实验室的安全问题日益引起人们的关注。为了提高实验室的安全性,基于射频识别(Radio Frequency Identification,RFID)技术和紫蜂协议(ZigBee)技术设计了一种危险品实验室安全监测系统,以提高实验室的安全性和管理效率。该系统通过RFID标签对实验室内的危险品进行追踪和管理,利用ZigBee技术实现实时的监测和报警功能。展开更多
基金the National Natural Science Foundation of China(No.U2031208,61571244)。
文摘Most studies on device-free localization currently focus on single-person scenarios.This paper proposes a novel method for device-free localization that utilizes ZigBee received signal strength indication(RSSI)and a Transformer network structure.The method aims to address the limited research and low accuracy of two-person device-free localization.This paper first describes the construction of the sensor network used for collecting ZigBee RSSI.It then examines the format and features of ZigBee data packages.The algorithm design of this paper is then introduced.The box plot method is used to identify abnormal data points,and a neural network is used to establish the mapping model between ZigBee RSSI matrix and localization coordinates.This neural network includes a Transformer encoder layer as the encoder and a fully connected network as the decoder.The proposed method's classification accuracy was experimentally tested in an online test stage,resulting in an accuracy rate of 98.79%.In conclusion,the proposed two-person localization system is novel and has demonstrated high accuracy.
文摘随着科学技术的不断发展,危险品实验室的安全问题日益引起人们的关注。为了提高实验室的安全性,基于射频识别(Radio Frequency Identification,RFID)技术和紫蜂协议(ZigBee)技术设计了一种危险品实验室安全监测系统,以提高实验室的安全性和管理效率。该系统通过RFID标签对实验室内的危险品进行追踪和管理,利用ZigBee技术实现实时的监测和报警功能。
