Varroa mites are the most detrimental external parasites in beekeeping. Monitoring their population is crucial for Integrated Pest Management (IPM). However, their small size makes them difficult to detect with the naked eye, and traditional monitoring methods are labor-intensive. This technology addresses these challenges by utilizing mobile devices to capture images and build a comprehensive dataset of Varroa mite photos. Through the application of deep learning algorithms, an automatic identification software has been developed. By integrating IoT technology and expert-defined parameters, an intelligent monitoring and alert system has been designed, achieving an accuracy rate of 83%.