Aiming at the problem that the traditional monitoring mode of power generation can’t monitor the normative behavior of operators as well as realize the comprehensive monitoring and intelligent decision-making analysis of power generation safety, this paper applies cloud platform, real-time database, OpenPose and TensorFlow to the power generation safety management system to monitor and manage the operation process of staff. The research shows that the application of cloud computing and deep learning technology in power generation safety monitoring system can significantly improve the compatibility, real-time performance and supervision ability of the system, and ensure the accuracy and recognition rate of data.

Power generation safety,Real-Time Monitoring,cloud platform