Optimization of Environmental Parameters of Ice and Snow Sports Venues Based on the BP Neural Network and Wireless Communication Technology

Abstract

Ice and snow sports have become a scene of attraction nowadays. It not only encourages sports but also earns more revenue through tourism. Tourists love and admire this kind of sport because of its uniqueness, unlike other sports. The Olympic Games also conduct ice and snow sports under the Winter Olympic Sports. This kind of sport is played in ice rinks. Ice rinks are of two types, namely, natural and artificial. Natural ice rinks are formed in snowy regions, whereas artificial ice rinks can be set up anywhere with the help of technology. An artificial or natural ice rink, a sports venue, or a stadium is constructed accordingly. This research focuses on the optimization of environmental parameters of the ice and snow sports venue based on the BP neural network and wireless communication technology. There are various factors to be monitored when an indoor ice and snow sports venue is being considered. They are temperature monitoring, health monitoring of the audience, natural disaster detection and alarm in the case of natural ice rinks, and building safety concerning the climatic conditions. The proposed methodology uses BP neural networks and wireless communication technology to optimize the environmental parameters of the ice and snow sports venue. It has been demonstrated to have numerous advantages over traditional ice and snow sports methods. In this research, the convolutional BP neural network algorithm was implemented to analyse the environmental parameters of the chosen sport. The proposed algorithm is compared with the existing weighted centroid model. The results show that the proposed model has achieved an accuracy of 99.45%.