| Issue |
MATEC Web Conf.
Volume 173, 2018
2018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
|
|
|---|---|---|
| Article Number | 03027 | |
| Number of page(s) | 5 | |
| Section | Digital Signal and Image Processing | |
| DOI | https://doi.org/10.1051/matecconf/201817303027 | |
| Published online | 19 June 2018 | |
Design of Embedded Network Voice Communication Terminal Based on STM32 and μCOSIII
Aerospace Engineering University, The Bayi Road of Huairou District, Beijing, China
* Corresponding author : l_j2017@163.com
Aiming at the application demand of voice communication between user terminals in the simulated training environment, a design and implementation method of embedded network voice communication terminal based on STM32 and μCOSIII is proposed. The hardware module of communication terminal is based on STM32 microcontroller, voice communication module, LCD display module and SD card storage module. The embedded real-time operating system μCOSIII is transplanted in order to enhance the real time and stability of the control system, and the user interface management system STemWin is used to manage LCD module. The signal exchange protocol of speech communication is designed, and the realization of the communication function software based on TCP/IP protocol is completed. In order to detect the voice communication function of communication terminal, a communication server software based on .NET Framework platform is designed, which is responsible for managing the communication terminal and forwarding the communication data. The experimental results show that the user interface of the communication terminal is good, the data transmission is stable and the communication function is reliable.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.