Abstract: The intelligent mine ventilation systems is a key link of advancing intelligent mine construction and ensuring safe mine production. As the fundamental data source, ventilation parameters are essential for the intelligent construction of mine ventilation systems. However, during the development of intelligent wind speed sensing technology for mine tunnels, there are key scientific and technological issues that need to be addressed, such as optimizing sensor accuracy and reliability, correcting sensor wind measurement errors, intelligent and rapid prediction of average wind speed, and optimizing sensor layout. This paper studies the cutting−edge achievements in the field from aspects such as sensor technology and high−precision intelligent wind speed prediction, summarizes the advantages, disadvantages, and applicable scopes of various technologies, and proposes an intelligent prediction model for the average wind speed in tunnel sections based on the PSO−GRU neural network. This model can effectively improve the accuracy of calculating the average wind speed in mine tunnels and provide a theoretical reference for the development of intelligent sensing technology for ventilation parameters.