Indoor localization is very critical for medical care applications, e.g., the patient localization or tracking inside the building of the hospital. Traditional Radio Frequency Identification(RFID) technologies are ver...Indoor localization is very critical for medical care applications, e.g., the patient localization or tracking inside the building of the hospital. Traditional Radio Frequency Identification(RFID) technologies are very popular in this area since their cost is very low. In such technologies, each tag acts as the transmitter and the Radio Signal Strength Indicator(RSSI) information is measured from the readers. However, RSSI information suffers severely from the multi- path phenomenon. As a result, if in a very large area, the localization accuracy will be affected seriously. In order to solve this problem, we introduce Wireless Sensor Networks(WSNs) with only a few nodes, each of which acts as both transmitter and receiver. In such networks, the change of signal strength(referred as dynamic of RSSI) is leveraged to select a cluster of reference tags as candidates. Then the fi nal target location is estimated by using the RSSI relationships between the target tag and candidate reference tags. Thus, the localization accuracy and scalability are able to be improved. We proposed two algorithms, SA-LANDMARC, and COCKTAIL. Experiments show that the localization accuracy of the two algorithms can reach 0.7m and 0.45 m, respectively. Compared to most traditional Radio Frequency(RF)-based approaches, the localization accuracy is improved at least 50%.展开更多
文摘电力设备数字孪生技术的发展推动了各类新型传感技术在电力行业中的应用,并亟需一条稳定、明确的数据上云渠道,以供给电力设备孪生体进行更加深入的状态分析及故障预测。为此,研制了一种带有金属反射板的双天线射频识别(radio frequency identification,RFID)加速度与温度传感器,并设计了RFID传感系统内的数据包格式以及传感数据经由边缘网关通过4G网络以消息队列遥测传输(messagequeuingtelemetrytransport,MQTT)协议上传至物联网云平台的数据传输通道,然后以OFPSZ-150000/220变压器为例进行了传感器测试和数据传输协议的应用。结果表明:所设计的数据传输协议丢包率主要存在于RFID传感器信道内,在2 m内的丢包率为11.3%,在最远通信距离3 m处的丢包率为38.2%,在数据经由边缘网关上云的信道中几乎不存在数据包的丢失问题。研究表明所设计的RFID传感器具有一定的实用性,且数据通信协议通道是稳定可靠的。
基金supported in part by China NSFC Grant 61202377 and 61170076the Guangdong Natural Science Foundation under Grant 2014A030313553+2 种基金the China National High Technology Research and Development Program 863, under Grant 2015AA015305Joint Funds of the National Natural Science Foundation of China under Grant U1301252Guangdong Province Key Laboratory Project under grant 2012A061400024
文摘Indoor localization is very critical for medical care applications, e.g., the patient localization or tracking inside the building of the hospital. Traditional Radio Frequency Identification(RFID) technologies are very popular in this area since their cost is very low. In such technologies, each tag acts as the transmitter and the Radio Signal Strength Indicator(RSSI) information is measured from the readers. However, RSSI information suffers severely from the multi- path phenomenon. As a result, if in a very large area, the localization accuracy will be affected seriously. In order to solve this problem, we introduce Wireless Sensor Networks(WSNs) with only a few nodes, each of which acts as both transmitter and receiver. In such networks, the change of signal strength(referred as dynamic of RSSI) is leveraged to select a cluster of reference tags as candidates. Then the fi nal target location is estimated by using the RSSI relationships between the target tag and candidate reference tags. Thus, the localization accuracy and scalability are able to be improved. We proposed two algorithms, SA-LANDMARC, and COCKTAIL. Experiments show that the localization accuracy of the two algorithms can reach 0.7m and 0.45 m, respectively. Compared to most traditional Radio Frequency(RF)-based approaches, the localization accuracy is improved at least 50%.
