Heterogeneous IoT Information Distributed Collection System Based on Embedded Technology

Abstract

The development of artificial intelligence and Internet of Things technology provides a solution to the data problem of remote data acquisition. It plays a vital role in many application scenarios, such as robot control, industrial automation and so on. How to develop the application results of artificial intelligence and Internet of Things data collection has become an important issue in the current system development. In this paper, a data processing model based on low priority queue and neat queue is proposed. Considering the structural framework of Kafka, the security of database data is guaranteed. The high priority of data and the communication response capability of small data volume are further improved. In the aspect of custom protocol, this paper considers the network setting protocol of device side and server side to solve the problem of packet parsing. On the Netty layer, considering the rule of judging threads established by Netty, this paper designs a judging mechanism for dynamic thread adjustment. Finally, through the simulation test platform, compared with the traditional difference prediction method, it is verified that the transmission model designed in this paper is closer to the actual value. The response effect of data processing in different priority levels is improved, which proves that the transmission scheme established in this paper can better solve the problem of network communication information queue priority sorting, and has higher analytical ability for data weight prediction. It contributes to the application of data communication in the Internet of Things and can be used for reference in the construction of the Internet of Things in different industries.