Abstract
Background Biological samples and other medical items such as blood and bone marrow need to be kept in an ultra-low temperature environment. A prediction of low-temperature living cell monitoring system was designed, aiming at the current situation of cryogenic temperature.
Methods The system mainly consists of a terminal node, sink node and host computer. By using neural network biofilm, the method predicts the motor speed at the next moment. The terminal node collects the information of the low temperature environment through the sensor and sends the collected information to the sink node regularly. To determine transmission efficiency, the entire system uses a modular structure, based on the scene quickly set up by the application system.
Results The system was tested in a hospital. The test results show that the system, which can measure temperatures between −200°C and −100°C with −0.5° error with high precision and fast response times, and can upload data to the cloud in real time, fully meets the hospital’s needs.
Conclusion We studied intelligent control combined with the remote monitoring system of ultra-low temperature freezer and the implementation of each module. The system provides accurate, convenient and reliable results in real time.
Acknowledgements Supported by the project grant from the National Natural Science Foundation of China (51774088) and Post Subsidy Funds for Sci and Tech Achievements of Northeast Petroleum University (HBZZJ201603).