Abstract: In order to quickly detect the moldy state in tobacco storage in all aspects and solve the problem that the traditional moldy detection method is complicated and requires manual judgment, a set of monitoring of specific parameters of the tobacco storage environment was built based on the Internet of things technology and BP neural network algorithm. Platform, so as to realize the intelligent monitoring of the moldy status of the stored tobacco leaves. First, design a tobacco leaf storage environment data collection terminal and a handheld wireless repeater. The handheld wireless repeater was used to wake up the data collection terminal, and use radio frequency transmission to obtain the environmental parameters collected by the terminal, and send the data to the server via GPRS. The server completes data analysis processing. After that, a tobacco leaf status recognition model was established based on the BP neural network algorithm, and the tobacco leaf status was obtained by analyzing and processing the collected environmental parameters, and the effectiveness of the model was verified by experimental simulation. Finally, an intelligent monitoring information management system for tobacco storage environment was developed and completed to realize the visual display and alarm of tobacco environmental parameters and tobacco mildew status. The test results showed that the use of the Internet of things technology combined with the BP neural network algorithm can effectively complete the monitoring of the moldy state of the stored tobacco leaves, which has certain practical application value.

Key words: tobacco storage, BP neural network, Internet of things technology, mildew status monitoring