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What data types can i send through UART on STM32 board? 


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On an STM32 board, you can send various data types through UART, including raw sensor data, programming information, and control signals. The STM32 processor-based system is designed for real-time data acquisition on production lines, utilizing UART for communication . Additionally, a programming circuit for the STM32 chip involves UART communication, enabling the transfer of programming data efficiently . Moreover, a multiple-serial-port control circuit based on STM32 facilitates the transmission of integrated data from different equipment to enhance monitoring system reliability, utilizing UART for communication with peripheral devices . Overall, the UART functionality on the STM32 board allows for versatile data transmission, ranging from sensor readings to programming instructions and control signals.

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Papers (5)Insight
Patent
Yin Rongxin, Hui Lyufeng 
19 Apr 2019
1 Citations
The STM32 chip serial ports burns record circuit allows sending various data types through UART on the STM32 board, enhancing resource efficiency.
Patent
Nie Qibiao, Liao Hongfei 
30 Sep 2015
1 Citations
You can send various data types through UART on an STM32 board, such as programming instructions, control commands, and communication data, facilitating efficient programming and communication processes.
The STM32 board can transmit and receive data in various formats such as TTL and RS232 levels through UART, enabling communication with different equipment efficiently.
You can send data frames through UART on the STM32 board, as described in the paper, allowing for efficient transmission of voltage data for the virtual oscilloscope.
The STM32 board supports sending various data types through UART, including raw data from sensor devices on production lines for real-time transmission to the servo computer.

Related Questions

What are some popular STM32 projects among hobbyists and professionals?5 answersPopular STM32 projects among hobbyists and professionals include a diverse range of applications. These projects leverage the STM32 microcontroller for various purposes. Some notable projects include an equipment box controller for monitoring power equipment on light poles, enabling remote parameter modification and fault reporting. Another project involves a real-time controllable multi-channel transcranial DC stimulator system for addressing mental health issues through intelligent treatment parameter adjustments. Additionally, a portable low-power blood oxygen detection device utilizes the STM32 microcontroller for real-time monitoring of human blood oxygen levels, offering portability and stability for mobile medical applications. These projects showcase the versatility of STM32 microcontrollers in enabling innovative solutions across different fields.
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How can STM32L072 MCU be used for smart-grid monitoring?4 answersThe STM32L072 MCU can be used for smart-grid monitoring by implementing a system that synchronizes event counts using one-time passwords. This system initializes an error count, receives a seed value and event count from the MCU, calculates a monitoring key value using a hash function, and compares it with the key value received from the MCU to determine the operation state. Additionally, the STM32L072 MCU can be used as a gateway processor to connect the independent working monitor unit of an electric network to the Ethernet. This allows for the transmission of monitoring data to a control center, updating of server machine data, and display of timely data on a network page. The MCU can also be used to transmit commands to the network MCU for compensating reactive power by connecting relays to the electric network.
What is the best way to use an Arduino microcontroller for remote control?5 answersThe best way to use an Arduino microcontroller for remote control is by utilizing it with various communication systems such as the internet network, SMS (Short Message Service), and GSM (Global System for Mobile Communication) network. Arduino can be used to control electric motor starting, electric lights, environmental variables, and security systems. It can also be integrated with smartphones and wireless technologies to provide user-friendly interfaces for controlling and monitoring power consumption patterns of home appliances remotely. Bylink and RF Remote modules are examples of tools that can be used to control Arduino-based systems.
How IIoT devices interact with PLCs for data collection?4 answersIIoT devices interact with PLCs for data collection by integrating communication technologies and databases with automation. PLC control devices are widely used in industry and can communicate with popular database management systems like SQL Server. General PLCs have gained the ability to process large amounts of industrial data and share the workload of cloud servers, transforming them into edge-PLCs. Machine data acquisition plays a role in bringing factory floor data into the IIoT environment, which can be visualized in real-time through AR and MR-based smart devices. Network communication in Industrial Control Systems (ICSs) is often implemented via an IP-based protocol, allowing IIoT devices like PLCs to communicate and acquire data. A dual Microcontroller Unit (MCU) setup can ensure resilient controlling for IIoT devices like PLCs, providing a possible solution for secure architectures in the IIoT.
What are the different IoT data collection solutions available?5 answersThere are several different IoT data collection solutions available. One approach is to use unmanned aerial vehicles (UAVs) as a platform for gathering data from IoT devices located worldwide. Another solution involves a wireless-powered IoT network that uses a hybrid access point (HAP) to charge devices and facilitate backscattering transmissions. Additionally, integrating homomorphic encryption (HE) algorithms into sensor devices allows for encrypted data transmission in wireless sensor networks. Mobile data collection can also be enhanced by using a learning-based approach for trajectory planning, where a deep Q-learning network (DQN) is trained to maximize data collection and reduce energy consumption. Finally, a method of water data collection can be achieved through the coordination of an unmanned surface vehicle (USV) carrying UAVs, with a heuristic algorithm used to optimize data collection and energy consumption.

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