Design of Medical Cold Chain Information Acquisition System Based on Linear Prediction


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.

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  1. 1.

    Ndraha, N., Hsiao, H. I., Vlajic, J., et al. (2018). Time-temperature abuse in the food cold chain: Review of issues, challenges, and recommendations. Food Control,89, 12–21.

    Article  Google Scholar 

  2. 2.

    Pengcheng, N., Tao, D., Di, W., et al. (2017). Agricultural internet of things technology and its application. Agricultural Engineering, 7(5), 25–30.

    Google Scholar 

  3. 3.

    Carullo, A., Corbellini, S., Parvis, M., et al. (2009). A wireless sensor network for cold-chain monitoring. IEEE Transactions on Instrumentation and Measurement,58(5), 1405–1411.

    Article  Google Scholar 

  4. 4.

    Qian, J., Fan, B., Zhang, X., et al. (2017). Temperature monitoring in cold chain chamber based on temperature sensing RFID labels. Transactions of the Chinese Society of Agricultural Engineering,33(21), 282–288.

    Google Scholar 

  5. 5.

    Lu, S., & Wang, X. (2017). Toward an intelligent solution for perishable food cold chain management. In IEEE international conference on software engineering & service science, IEEE.

  6. 6.

    Qi, L., Han, Y., Zhang, X., et al. (2012). Real time monitoring system for aquatic cold-chain logistics based on WSN. Nongye Jixie Xuebao/Transactions of the Chinese Society of Agricultural Machinery,43(8), 134–140.

    Google Scholar 

  7. 7.

    Jiayang, L., Linan, F., & Dongyan, D. (2018). A new route optimization approach of cold chain logistics distribution based on fresh agricultural products. In The 30th Chinese Control and Decision Conference (CCDC) (pp. 6652–6657). IEEE.

  8. 8.

    Cha, H. J., Yang, H. K., & Song, Y. J. (2018). A study on access structure management of CP-ABTD based blockchain for medical information monitoring system. Advanced Science Letters,24(3), 2026–2030.

    Article  Google Scholar 

  9. 9.

    Kogure, H., Kawasaki, S., Nakajima, K., et al. (2005). Development of a novel microbial sensor with Baker’s Yeast cells for monitoring temperature control during cold food chain. Journal of Food Protection,68(1), 182–186.

    Article  Google Scholar 

  10. 10.

    Wang, L., Kwok, S. K., & Ip, W. H. (2010). A radio frequency identification and sensor-based system for the transportation of food. Journal of Food Engineering,101(1), 120–129.

    Article  Google Scholar 

  11. 11.

    Pengcheng, Xu, Zhibin, Li, Chang, Liu, et al. (2018). Design of control system based on STM32 and LoRa for climbing free wind turbine tower. Instrument Technology and Sensor,8, 108–112.

    Google Scholar 

  12. 12.

    Xuefen, Wan, Jian, Cui, Yi, Yang, et al. (2018). Research on LoRa wireless transmission performance test based on smart phones. Modern Electronic Technology,41(21), 7–11.

    Google Scholar 

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This research was financially supported by Shandong Province key research and development programs of China (2019GGX105001) and the College Science and technology project of Shandong Province of China (J15LN59, J16LN75, and J16LN78).

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Correspondence to Peixue Liu.

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Liu, P., Dong, L. & Cao, A. Design of Medical Cold Chain Information Acquisition System Based on Linear Prediction. Wireless Pers Commun (2020).

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  • Cold chain
  • Linear prediction
  • Kalman filter
  • LoRa
  • 5G network