Intelligent Instrumented Belaying System in Sports Climbing

Sport climbing became a more attractive sport to the broad mass over the last decades. An increasing amount of injuries are the consequences. Inattentiveness and untrained belayer are some of the natural causes. In order to improve their experience, we developed an intelligent belaying system monitoring the belayer during his task to secure the climber throughout his ascent. It is supposed to recognize a climbers’ fall if the belayer fails. We specifically designed Machine Learning algorithms in combination with a multi-sensor system for this task. The system is divided in two separate sub-systems, which communicate over wireless LAN protocols in order to keep them synchronized. One of the two subsystems is integrated into a belay device. It records the movement behavior of the device and the rope running through it. In order to generate label data, the second sub-system was attached onto the climber. Based on the information from the belay device alone, we were able to identify a fall with a certainty of 86.21%.