Modern housing design is experiencing a shift from single residential function to diversified functional space, especially in the context of globalization, the demand for English learning is increasing, and the traditional housing layout can no longer meet the diversified needs of modern families for learning space. In this paper, a housing functional layout model based on improved adaptive genetic algorithm is proposed for the design of diversified living environments integrating English learning spaces. The spatial point cloud data are collected by Kinect device to establish a three-dimensional spatial feature geometric model, which is combined with the improved adaptive crossover and variance probability formulas to realize the intelligent optimization of housing layout. Multiuser interactive genetic algorithm is used for indoor layout frame extraction, coordinate transformation and visualization. The experimental results show that the algorithm converges after 6810 generations of iterations, and the average fitness is maintained near 0.147; the Pareto-optimal solution set contains 34 solutions, of which the student satisfaction level of the optimal solution reaches 73.005 points and the English improvement level is 78.58 points; the user satisfaction score of the minimalist style objective reaches 4.72 points, and the system reliability is respectively 94% and 98% confidence level The reliability of the system was verified at 94% and 98% confidence levels, respectively. The results of the study proved that the method can effectively realize the functional integration of English learning space and housing design, which provides a scientific basis and technical support for the diversified design of modern housing.
