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For the rolling mill torque telemetry system, the battery power supply has a short duration, and the current supply by the collector ring can achieve long-term power supply, but it is difficult to achieve stable power supply for a long time due to limitations such as speed and wear. This paper designs a high-frequency induction power supply system to realize long-term stable power supply of sensors and signal transmitting modules on the measured axis. The WIFI signal transmission technology is used to realize the fast, efficient and stable wireless transmission of torque signals. The embedded programming of STM32F103 chip based on Cortex-M3 kernel architecture realizes the AD conversion, signal processing, WIFI transmitting and receiving control of torque signal. The system has been applied to the monitoring of main drive torque of many continuous rolling mills and achieved good results, which can replace expensive imported products.

It is important to promote the development and application of hospital information system, community health service system, etc. However, it is difficult to realize the intercommunication between various information systems because it is not enough to realize the in-depth management of health information. To address these issues, we design the 5G edge computing-assisted architecture for medical community. Then, we formulate the directional data collection (DDC) problem to gather the EMR/HER data from the medical community to minimize the service error under the deadline constraint of data collection deadline. Moreover, we design the data direction prediction algorithm (DDPA) to predict the data collection direction and propose the data collection planning algorithm (DCPA) to minimize the data collecting time cost. Through the numerical simulation experiments, we demonstrate that our proposed algorithms can decrease the total time cost by 62.48% and improve the data quality by 36.47% through the designed system, respectively.

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