Paper Info
Title
Design Of Medical Cold Chain Information Acquisition System Based On Linear Prediction
Abstract
There are many problems in existing medical cold chain information acquisition system, such as poor mobility of monitoring points, short wireless transmission distance, and frequent data errors. In order to deal with the above problems, a medical cold chain information acquisition system is designed based on 5G technology and LoRa self networking technology. At the same time, a self-adaptive secondary Kalman filter method is proposed to predict the collected information linearly. The system is divided into two parts, which are data acquisition module and coordinator. The collected information of the data acquisition module is reported to the coordinator through LoRa network. After the coordinator performs linear prediction processing on the information, the dada is uploaded to the cloud platform through 5G network, which can realize the monitoring of medical cold chain information at any time and anywhere. The system and the proposed method are simulated and tested. The test results show that the system can complete the data acquisition and processing accurately, the system error is small, and the occasional error can be eliminated in time. The proposed method has smaller prediction error than the traditional filtering method.
Year
DOI
Venue
2020
10.1007/s11277-020-07618-2
WIRELESS PERSONAL COMMUNICATIONS
Keywords
DocType
Volume
Cold chain, Linear prediction, Kalman filter, LoRa, 5G network
Journal
115
Issue
ISSN
Citations 
2
0929-6212
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Peixue Liu100.34
Dong Li247567.20
Aixia Cao300.34