Exploration of Blockchain Technology in Trusted atmospheric Environmental Data

In the process of atmospheric environment data monitoring and governance, due to the assessment and ranking of the main governance departments, environmental data are often affected by many objective and subjective factors, resulting in data fraud or loss. Previously, after finding such phenomena through manual comparison, the management department often took the worst value of the environmental data in the day as the environmental data on the assessed area, so as to assess and punish. Although this method can play a certain deterrent effect, it seriously affects the authenticity of data and the fairness of assessment, in the long run, it will bring unpredictable challenges to the authenticity of environmental data. Based on blockchain technology, this paper combines residual network, forward Euler method, and convolutional neural network to calculate the mapping relationship between different monitoring stations through historical environmental data. Based on the training set, the minimum deviation value of distorted data or lost data is obtained, so as to provide key technical support for the trusted management of atmospheric environmental data, realize data trusted management, and ensure the integrity, authenticity and traceability of atmospheric environmental data.