A method of processing temperature sensor data based on edge compression calculations

Abstract

The invention discloses a method for processing temperature sensor data based on edge compression calculation. According to the invention, edge calculation is introduced into a visual platform system,is applied to a sensor data acquisition end to compress data, and then is forwarded to a server by a sending and receiving module; the method comprises the following steps: firstly, processing data at a sensor data acquisition end, and segmenting centralized large-batch data compression calculation into small-granularity single-module compression calculation; and secondly, sending the compresseddata through a sending and receiving module, so that the pressure of the network bandwidth of the server is reduced. According to the method, the pressure of caching the data messages in the message queue is reduced, and information loss caused by full load of the queue easily occurs due to caching and processing of a large amount of data. The data is compressed before being sent, so that the dataacquisition frequency can be improved, the obtained data information is more accurate, the information loss is reduced, and the data accuracy is improved in production.

Description

technical field [0001] The invention relates to the field of temperature sensors for the Internet of Things, in particular to large-scale, large-data-volume temperature sensors and a visualization platform system. Background technique [0002] As one of the three foundations of information technology, sensor technology is a high-tech that is being developed by developed countries. With the advancement of economy and technology, the popularization of the Internet and the development of the information highway, a large number of sensors for various purposes have been deployed in every corner of society to ensure the safety and convenience of people's lives. [0003] Temperature is one of the most closely related physical quantities in human life, and it is also the most commonly used and most important parameter in industrial production processes. Whether it is industrial and agricultural production, or the national defense modernization of scientific research, temperature me...

AI Technical Summary

Problems solved by technology

There are ways to reduce the frequency of data acquisition to reduce the amount of data. Although this reduces the amount of data, it reduces the accuracy of the data change process

In addition, there is also a method of properly compressing the data before storage, but the data of a large number of sensors is processed at the same time, which can achieve the purpose of reducing the amount of data, but there is a high demand for the performance of server data caching and processing

Images