Project “SafeClimb”

In this project we develop an intelligent belay system for sports climbing that combines outstanding and absolutely reliable mechanical functionality with smart assistance and monitoring functions. This electromechanical belay system not only prevents potentially serious accidents by automatically braking the rope in the event of a fall, but can also detect operating errors via an intelligent sensor system and report them back to the belaying climber. At the heart of the system is a mechanical semi-automatic device which, independently of the power supply and electronics, brakes or stops the rope if too much rope passes through too quickly. The sensor system measures the speed at which the rope passes through and the movement of the belay device. An intelligent classification process can use the measured data to differentiate between a fall and a rapid rope release. Machine learning methods are used for this purpose.

Project partner: Edelrid GmbH, Isny

Funding: BMWK
05/2019 – 10/2022

Publications

Poster at VerticalPro – Halls&Walls platform for vertical professionals 2022

Poster at VerticalPro – Halls&Walls platform for vertical professionals 2024

News

  • Preprint published: IMUDiffusion
    by Michael Munz

    We are very happy that we could now publish a new pre-print publication with the title “IMUDiffusion: A Diffusion Model for Multivariate Time Series Synthetisation for Inertial Motion Capturing Systems” on arxiv here: https://arxiv.org/pdf/2411.02954. The paper describes a new method for the synthetisation of time-series data like Inertial Motion Capturing Systems, which is based on a diffusion model.

    The paper is currently under review in a peer-review journal on AI methods.

  • Poster at VerticalPro 2024
    by Michael Munz

    We are happy to show our latest research from the project SafeClimb at the VericalPro 2024!

Related Publications

Oppel, H., & Munz, M. (2024). IMUDiffusion: A Diffusion Model for Multivariate Time Series Synthetisation for Inertial Motion Capturing Systems (No. arXiv:2411.02954). arXiv. https://doi.org/10.48550/arXiv.2411.02954 Cite
Oppel, H., & Munz, M. (2024). Smart Belay Device for Sport Climbing—An Analysis about Falling. Engineering Proceedings, 68(1), 29. Cite
Oppel, H., & Munz, M. (2023). A Time Window Analysis for Time-Critical Decision Systems with Applications on Sports Climbing. AI, 5(1), 1–16. Cite
Oppel, H., & Munz, M. (2022). Intelligent Instrumented Belaying System in Sports Climbing. Sensors and Measuring Systems; 21th ITG/GMA-Symposium, 1–7. Cite
Oppel, H., & Munz, M. (2021). Analysis of Feature Dimension Reduction Techniques Applied on the Prediction of Impact Force in Sports Climbing Based on IMU Data. AI, 2(4), 662–683. Cite
Munz, M., & Engleder, T. (2019). Intelligent Assistant System for the Automatic Assessment of Fall Processes in Sports Climbing for Injury Prevention based on Inertial Sensor Data. Current Directions in Biomedical Engineering, 5(1), 183–186. https://doi.org/10.1515/cdbme-2019-0047 Cite
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