The invention relates to the field of building distributed environment monitoring and discloses a building environment sensor measuring point optimization method based on a Gauss process model. The method comprises the steps that a teleoperation moving robot is used for carrying an environment measuring sensor node to be used as a moving measuring platform, and environment parameters and measuring point positions in an unknown building are collected; the environment parameters obtained by collecting are used as data samples, a Gauss process regression model is used for carrying out fitting on continuous probability distribution of the environment parameters, and measured values at unarranged measuring points are predicted; a greedy algorithm is used for solving a group of optimum sensor position set; and the optimum sensor position set and complementary selecting results of the main measuring point positions in a building room are combined, and finally the measuring point distribution results with the limited number and the optimum positions are obtained. According to the method, optimum arranging of environment measuring sensors in a large area of the unknown building can be achieved, the smallest number of sensors are used for reestablishing environment parameter field distribution effectively, and a traditional experience arranging method is replaced.