To tackle the problems of large power consumption and intricate design of the automatic control system for air conditioning in a telecommunication room, this study proposes an energy-saving control method based on the Dueling-DQN algorithm and rule constraint for mechanical control system design. With the ability to learn modeling adaptively according to the environments of different computer rooms, this method can save the power consumption of air conditioning while ensuring the indoor temperature in the specified range. Moreover, according to the actual application scenarios of computer rooms, the states, actions and reward functions of the energy-saving control algorithm are designed. Besides, a deep reinforcement learning algorithm Dueling-DQN is used to improve the model expression ability and learning efficiency. The results of actual verification in telecommunication rooms show that the control method can save energy by 18.3% compared with the air conditioning at default parameters. It can be easily extended to machines in different environmental scenarios to provide solutions for energy conservation and emission reduction of telecommuni-cation rooms.