Human Behavior Detection Based on RPN Network and Dynamic Image Recognition

Authors

  • Fei Yu Shandong Sport University, Jinan, Shandong, 250000, China
  • Zhaoxia Lu Shandong Sport University, Jinan, Shandong, 250000, China

Abstract


The basis for designing a system for the remote collection of electrical equipment parameters is a miniature high-performance controller and wireless Ethernet technology. At the center of the data collection section is a microprocessor; that can be used in two ways: as a monitor alone, or it can be installed. Using the example of a welding machine, the main functions of the microprocessor are the collection of electrical equipment parameters, processing calculations, displaying parameters, and communication with the PC at the main control center site. ViaYuanline Ethernet, the client/server
mode is used to realize remote communication, andVC++6 is used to develop the related software; this realizes the remote monitoring, measurement and acquisition of the parameters of electrical equipment. Under the Linux STM32 single-chip microcomputer platform, through the layered serial protocol, the serial interface settings of the lower computer iMX and the upper STM32 are realized respectively, so that the upper and lower positions are not synchronized. The basic conditions of the line communication are guaranteed, the specific data packet format and the middle-level transmission protocol are set, and the exact and definite transmission of the aggregate data, composed of a large amount of data, is realized through the STM32 real-time collection of data on the CAN line. Packing these contents in a specific format can reduce the amount of forwarded data, greatly improve the scalability and performance of the device, and creates a specific reference value for the conversion between two communication devices under specific data.

Keywords: Electrical equipment; Wireless Ethernet; STM32; Parameter collection

Cite As

F. Yu, Z. Lu, "Human Behavior Detection Based on RPN Network and Dynamic Image
Recognition", Engineering Intelligent System, vol 29 no 3, pp. 167-173, 2021.






Published

2021-06-01