Design of Iot Data Acquisition System Based on Neural Network Combined with STM32 Microcontroller

Aiming at the low efficiency and high power consumption of data acquisition in the Internet of Things, a data acquisition system based on the combination of neural network and STM32 microcontroller is designed. In the control module, according to the system functional design and performance requirements, the STM32F103C8T6 minimum system module is used as the control core of the system. The data acquisition terminal adopts the baseplate + core board structure, and is composed of high-speed data acquisition module, AT91SAM9X25 platform and various expansion function modules. Eight types of environmental data sensor modules are used to build sensor modules. The k-means convolution neural network is used to realize the data classification of the Internet of Things, and the design of the data classification module is completed. The performance of the system is tested. The test results show that the system can realize the real-time collection of indoor environmental data, the communication rate is higher than 80 mbps, and the power consumption of the data acquisition terminal is low.