According to statistics, from 2012 to 2020, my country's demand for honey increased from 280800 tons to 418900 tons. However, my country's beekeeping industry relies solely on traditional equipment, and there are problems such as backward breeding technology and inability to break through large-scale and mechanization. The annual economic loss is as high as 3.06 billion yuan. Therefore, the intelligent beehive based on multi-sensor data fusion came into being. The intelligent beehive based on multi-sensor data fusion studied in this work uses temperature and humidity sensors, weighing sensors, image sensors, etc. to collect relevant data, and then transmits the information to STM32. A multi-sensor data fusion algorithm based on D-S evidence theory and BP neural network is built in STM32. The characteristic values of the beehive environment are obtained after the data collected by different types of sensors are fused by BP data, the basic probability distribution function and evidence fusion rules of D-S evidence theory are designed, and the results of the fused beehive environment assessment make comprehensive use of the measured values of various types of sensors, and the accuracy of the beehive environment assessment value is much higher than that based on a single sensor. If the fused environmental evaluation value exceeds the threshold set in STM32, the corresponding device is intelligently controlled to adjust, and the data is transmitted to the cloud server through the narrowband IoT communication module. After the App side obtains the processed data from the server, it can present the environmental information of bee life to the user for observation in the form of image through analysis and analysis. After obtaining the data from the server, the Web side carries out statistical analysis to generate a statistical analysis chart, and fully combines the characteristics of the bee colony, analyzes the relationship between the bee colony and the microclimate, displays the change law of the bee colony in real time, and makes real-time prediction and early warning. Through a series of emerging technologies, the intelligent beehive system can monitor the real-time living status and honey production of the bee colony in the beehive without leaving home, automatically adjust the temperature and humidity in the beehive to provide the most comfortable life and environment for the bee colony, and can provide users with a series of solutions in advance to monitor the disaster situation in real time, thus changing the traditional extensive, low-yield, low-efficiency and low-quality honey production method in the current beehive industry, it provides the possibility for accurate beekeeping and enables the future beekeeping industry to realize intelligent and standardized production.