Title :
Towards Automatic Food Prediction During Endurance Sport Competitions
Author :
Fister, Iztok ; Fister, Duan ; Ljubic, Karin ; Yan Zhuang ; Fong, Simon
Author_Institution :
Fac. of Electr. Eng. & Comput. Sci., Univ. of Maribor, Maribor, Slovenia
Abstract :
Endurance sport events have increasingly been gaining the popularity. Every year, more and more amateur athletes decide to participate in such events. During the race, proper eating is one of the most important components for achieving the good finish time and in this respect also the good place. In this paper, we examine possibility to predict what to eat at the moment. In line with this, machine learning method, i.e., decision tree was used that bases on the current athlete performance, his/her feeling, needs, and even weather. First simulations showed that this method may be suitable for future use in endurance events.
Keywords :
decision trees; learning (artificial intelligence); sport; amateur athletes; automatic food prediction; decision tree; endurance sport competitions; machine learning; Current measurement; Decision trees; Heart rate; Meteorology; Smart phones; Training; decision tree; endurance sport event; food; machine learning;
Conference_Titel :
Soft Computing and Machine Intelligence (ISCMI), 2014 International Conference on
DOI :
10.1109/ISCMI.2014.30