A Self-Powered Sensor Network Data Acquisition, Modeling, and Analysis Method for Cold Chain Logistics Quality Perception

被引:3
|
作者
Ren, Jiajia [1 ,2 ]
Li, Hongxin [1 ]
Zhang, Mengmeng [2 ,3 ]
Wu, Cong [1 ,4 ]
Yu, Xiaosheng [2 ]
机构
[1] Dongbei Univ Finance & Econ, Sch Management Sci & Engn, Dalian, Peoples R China
[2] Henan Univ Anim Husb & Econ, Sch Logist & E Commerce, Zhengzhou, Peoples R China
[3] Univ Cordilleras, Sch Business Adm, Baguio, Philippines
[4] Liaoning Univ Engn & Technol, Inst Optimizat & Decis Anal, Fuxin, Peoples R China
关键词
Cold chain logistics; data acquisition; quality perception; self-powered sensors;
D O I
10.1109/JSEN.2023.3242618
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
It is of great practical significance to design a cold chain logistics temperature monitoring terminal with high performance, low power consumption, low cost, safety, and reliability. Based on the theory of self-powered sensor network, this article designs data acquisition, modeling, and analysis methods for the actual needs of cold chain logistics transportation management and temperature monitoring problems, applying embedded technology, sensor technology, and wireless transmission technology to solve the problem of cold chain logistics. The logistics model is designed for cold chain logistics tracking, and D-Bus technology is introduced to solve the problem of communication between design data communication methods between different nodes and filter redundant sensor data. During the simulation process, we first initialize the monitoring software, set the serial port parameter m_ctrlComm, and then select the serial port through the m_choosecom serial port selection parameter and m_DataList serial port baud rate selection parameter; the experiment proves that the road matching can be well carried out, thus improving the accuracy and value of the trajectory. The experimental results show that about 15 066 times of temperature data can be collected and transmitted, and the frequency of collecting and uploading temperature data reaches 900 s, which verifies the effectiveness of the cold chain logistics middleware and the practicability of the data error correction algorithm.
引用
收藏
页码:20729 / 20736
页数:8
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