Construction of Carbon Audit and Verification System Framework Based on Intelligent Wireless Sensor Network

With the large amount of carbon emissions from many enterprises over the years, the global greenhouse effect is getting worse. In order to protect the climate and environment on which we depend, the world is taking active measures to reduce carbon emissions as much as possible. At present, the domestic carbon auditing and verification system is relatively late and immature, and the traditional system efficiency is relatively low. Wireless sensor network (WSN) is a particularly flexible distributed wireless communication network, which can coordinate the perception, processing, transmission, and collection of data of objects perceived within the network until the data content is transmitted to the user terminal. This paper aims to study and design an intelligent network model based on WSN so as to calculate and verify the carbon emissions of enterprises and countries. In this paper, an intelligent WSN model based on ZigBee technology is proposed to build an efficient, low-consumption, and high-precision carbon audit and verification system framework. In this paper, the system framework is referred to as ZWCA for short, that is, the carbon audit and verification system framework of WSN based on ZigBee. In addition, this paper compares the ZWCA framework with the traditional carbon audit and verification system in several groups to analyze the practical feasibility and advantages of the ZWCA framework. The test results show that the ZWCA framework proposed in this paper can audit and verify the carbon emissions of major enterprises very well, and the initial startup power of the ZWCA framework is only 1/2 of the traditional one. At the same time, its actual running power consumption is only 3/4 of that of the traditional audit and verification system framework, and the calculation accuracy is as high as 99%. Moreover, the number of node deaths has decreased, and the system stability has been significantly improved.