Smartphone Zombie Context Awareness at Crossroads: A Multi-Source Information Fusion Approach
Ying Zhuang, Zhixiang Fang
Abstract
“Smartphone Zombie” (or Smombie) is a new term that describes pedestrians playing with their mobile phones while walking. Research has shown that the usage of mobile phone distracts pedestrians, slows walking and increases the risk of car accidents. Relevant measures and laws have been taken to decrease the phenomenon; however, these measures and laws are costly, and the effects are limited. Therefore, the motivation of this study is to develop an efficient approach to identify and remind Smombies at intersections to reduce accident occurrences. In this approach, a framework for Smombie context awareness is proposed that integrates behavior information from pedestrians within physical and virtual space. In the framework, a set of sensors is employed to recognize the gesture of playing mobile phones. A modified multi-information fusion algorithm is developed to make Smombies aware of their physical context by combining fuzzy mathematics and Dempster-Shafer (D-S) evidence theory. Experiments indicate that the recall and precision of the algorithm are above 0.9, which means the proposed methods can effectively identify Smombies at crossroads.