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篇名
A Low-Power Remote Information Monitoring System of Cold Chain Logistic Based on NB-IoT
並列篇名
A Low-Power Remote Information Monitoring System of Cold Chain Logistic Based on NB-IoT
作者 Zhi-Bo Xie (Zhi-Bo Xie)Li-Yuan Zheng (Li-Yuan Zheng)Rui-Hua Zhang (Rui-Hua Zhang)Qiao-Weng Zhang (Qiao-Weng Zhang)Yong-Qiang Bai (Yong-Qiang Bai)
英文摘要

With the development of information technology, cold chain logistics monitoring systems are widely used in transportation of fresh food to detect the quality parameters in real time. Poor network transmission performance, high packet loss rate and high maintenance cost are the main problems in the current cold chain logistics monitoring. To solve these problems, the paper presents a low-power monitoring system based on Narrow Band Internet of Things (NB-IoT). Considering the characteristics of the moving carriage, the polling mode of Bluetooth is proposed for the communication of one sink node to three sensor nodes. An improved working sequence is designed to reduce the power consumption of Bluetooth modules. Subsequently, analyzing the standard NB-IoT terminal state transition diagram, combining with the practical applications of cold chain logistics, an improved terminal state transition diagram is proposed and its terminal power consumption is analyzed. In the experimental test, the packet loss rate is less than 1% within 8 km. And the battery life of improved Bluetooth module is 143 times of that of traditional one. The power consumption of main service of NB-IoT is discussed, the formula is given which includes the transmission quality, random access times, number of concurrent users, sleep interval and other parameters. Through simulation and calculate, the battery life of terminal is up to 17 years. These improvements will greatly reduce the cost of cold chain logistics monitoring system. In addition, the packet loss rate test experiment proves the high reliability of the communication system.

 

起訖頁 095-107
關鍵詞 information monitoring systemNB-IoTlow-power consumption
刊名 電腦學刊  
期數 202210 (33:5期)
該期刊-上一篇 A Domain Generalization Method Based on Hybrid Meta-Learning for Face Anti-Spoofing
該期刊-下一篇 A Super-resolution Reconstruction Method for Underwater Fish Images with Feedback Networks
 

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