Green Rural Modern Architectural Design Based on Pose Recognition Algorithm of Thermal Discomfort

Abstract

To reduce the energy waste of modern rural buildings caused by over-cold or over-heat supply, this paper presents a method to realize energy-saving design of modern green rural buildings by using thermal decomposition location recognition algorithm. Based on the key points of the human skeleton, the pose recognition framework is constructed, and the deep learning network is combined to detect the human thermal disturbance posture. Furthermore, an end-to-end thermal inauthentic pose recognition algorithm is proposed to establish a green intelligent building energy minimization model considering thermal comfort range. The results show that the recognition rate of 1D convolution +LSTM model is 100%, and the optimal accuracy of 16 frames of image sequence with decoder module is 92.052%. Compared to traditional algorithms, the method can save up to 10% of the total energy cost and reduce the total temperature deviation. This study is of great significance for intelligent control of indoor thermal environment and improvement of energy utilization efficiency.