Live monitoring of athletes during sporting events can help maximise performance while preventing injury, and enable new applications such as referee-assist and enhanced television broadcast services. A major challenge is the extraction of athlete physiological data in real-time, since the radio range of body-worn sensor devices is limited, necessitating multi-hop routing mechanisms. However, little is known about the highly dynamic operating conditions on a soccer field under which communication protocols need to operate. In this work we conduct field experiments in which we outfit first-division soccer players with sensor devices and record their inter-connectivity during a real game. Our first contribution profiles the key properties of the dynamic wireless topologies arising in the soccer field, and highlights the consequences for routing mechanisms. We show that the topology is in general sparse, with short encounters and power-law distributed inter-encounters. Importantly, the co-ordinated movement of players in the field gives rise to significant correlations amongst links, an aspect that can potentially be exploited by routing. Our second contribution develops a model for generating synthetic topologies that mirror connectivity in a real soccer game, and can be used for simulation studies of routing mechanisms. Its novelty lies in explicitly modelling the underlying auto-correlation and cross-correlation properties of the links, from which derived measures such as inter-encounter times and neighbourhood distributions follow. Our study is an important first step towards understanding and modelling dynamic topologies associated with sports monitoring, and paves the way for the design of real-time routing algorithms for such environments.
展开▼
