Where will the next ski injury occur? A system for visual and predictive analytics of ski injuries

Abstract

Ski injury is a rare event with 2‰ rate (2 injuries per 1000 skier days expected). Additionally, injuries are dispersed over a ski resort spatially and temporally, making it harder to predict where the injury will occur. In order to inspect ski-related injuries, we have developed a visual system which allows global and spatial inspection of ski lift transportation RFID data. To enrich the visual environment, we have embedded a predictive lasso regression model which predicts injury occurrence spatially and temporally over a ski resort with an AUC performance of 0.766. We propose the model which allows decision makers to make real-time decisions on allocation of rescue service capacities at a ski resort. Predictive model improves the models existing in literature as it works for various locations at a ski resort, and makes predictions of occurring injuries on an hourly basis.

Sandro Radovanović

Assistant Professor at University of Belgrade

My research interests include machine learning, development and design of decision support systems, decision theory, and fairness and justice concepts in algorithmic decision making.