The Application of Information Classification in Agricultural Production Based on Internet of Things and Deep Learning

Under the China's increasing attention to the technological innovation of agricultural production, all kinds of agricultural information have exploded on the internet, and agricultural informatization has developed rapidly. The related information has spread all over the whole network, which makes it gradually difficult to extract useful information from the network. To solve the deficiency of information classification ability of traditional agricultural information collection methods, the classification method of agricultural information is optimized, to realize searching the required agricultural information quickly. At first, the study introduces Deep Learning (DL) technology and the Internet of Things (IoT) and their advantages. Then, based on Bayesian Networks (BN) and Decision Tree (DT) algorithm, the agricultural information classification model is implemented and trained. Using various agricultural economic development theories, analyzation is made on the present situation of domestic agricultural informatization development. Finally, the advantages are put forward of agricultural production informatization development and economic management development based on IoT technology. The research results show that, the agricultural information classification model based on DL and IoT technology can accurately select the required effective information from the network, and the application of IoT technology in agricultural production big data plays an important role in production and economic management. Therefore, the agricultural information classification model based on DL and IoT technology can make an effective and accurate judgment on the classification of agricultural information, and then provide a focus for agricultural production and economic development. A new idea is provided for the application of new technologies in agricultural production and management.